Development of technology predicting based on EEMD-GRU: An empirical study of aircraft assembly technology
Technology prediction has been the subject of many prior studies, which have the issues of the long-term effectiveness, the high uncertainty, and the low predictive accuracy. To address these problems, this study developed a model based on a mixed neural network that combines the Ensemble Empirical...
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Published in | Expert systems with applications Vol. 246; p. 123208 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
15.07.2024
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Abstract | Technology prediction has been the subject of many prior studies, which have the issues of the long-term effectiveness, the high uncertainty, and the low predictive accuracy. To address these problems, this study developed a model based on a mixed neural network that combines the Ensemble Empirical Mode Decomposition (EEMD) signal decomposition method with the Gated Recurrent Unit (GRU) deep learning model. In this study, the literature data is first preprocessed using Latent Dirichlet Allocation (LDA) topic modeling, and clusters of key technology topics are obtained accordingly. Secondly, within the identified technology topics, the EEMD signal processing method is employed to decompose complex time-series data into simpler subsequences, and GRU prediction models are established. Thirdly, the ultimate technological prediction results are obtained by integrating each subsequence's prediction results. In addition, Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) were used to evaluate the prediction results. Finally, the field of aircraft assembly technology is analyzed as a case study. The results show that the EEMD-GRU hybrid model excels in prediction accuracy, and brings a new perspective and method to the field of technological prediction. |
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AbstractList | Technology prediction has been the subject of many prior studies, which have the issues of the long-term effectiveness, the high uncertainty, and the low predictive accuracy. To address these problems, this study developed a model based on a mixed neural network that combines the Ensemble Empirical Mode Decomposition (EEMD) signal decomposition method with the Gated Recurrent Unit (GRU) deep learning model. In this study, the literature data is first preprocessed using Latent Dirichlet Allocation (LDA) topic modeling, and clusters of key technology topics are obtained accordingly. Secondly, within the identified technology topics, the EEMD signal processing method is employed to decompose complex time-series data into simpler subsequences, and GRU prediction models are established. Thirdly, the ultimate technological prediction results are obtained by integrating each subsequence's prediction results. In addition, Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) were used to evaluate the prediction results. Finally, the field of aircraft assembly technology is analyzed as a case study. The results show that the EEMD-GRU hybrid model excels in prediction accuracy, and brings a new perspective and method to the field of technological prediction. |
ArticleNumber | 123208 |
Author | Wang, Jinfeng Zhang, Huyi Feng, Lijie Gao, Na |
Author_xml | – sequence: 1 givenname: Huyi surname: Zhang fullname: Zhang, Huyi email: huyizhang@163.com organization: Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai, China – sequence: 2 givenname: Lijie surname: Feng fullname: Feng, Lijie email: ljfeng@shmtu.edu.cn organization: Logistics Engineering College, Shanghai Maritime University, Shanghai, China – sequence: 3 givenname: Jinfeng orcidid: 0000-0002-3548-2674 surname: Wang fullname: Wang, Jinfeng email: wangjinfeng@shmtu.edu.cn organization: China Institute of FTZ Supply Chain, Shanghai Maritime University, Shanghai, China – sequence: 4 givenname: Na surname: Gao fullname: Gao, Na email: gn09232022@163.com organization: Aeronautical Manufacturing Technology Institute, Shanghai Aircraft Manufacturing Co., Ltd., Shanghai, China |
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Cites_doi | 10.3103/S1068799818020186 10.1016/j.cirp.2015.04.048 10.1016/j.eswa.2009.06.088 10.1016/j.neucom.2018.05.090 10.1109/TIE.2019.2927197 10.1155/2017/6856139 10.1016/j.jmsy.2018.01.008 10.1016/j.iot.2020.100228 10.1109/YAC.2016.7804912 10.1111/exsy.12511 10.1111/exsy.12335 10.3390/en13071543 10.1016/j.techfore.2017.07.022 10.1016/j.rser.2019.01.014 10.1016/j.asoc.2017.01.015 10.1016/j.techfore.2018.12.006 10.1007/s00170-019-04087-1 10.1016/j.cie.2021.107598 10.1109/ACCESS.2021.3070447 10.1016/j.nanoen.2018.02.020 10.1016/j.solener.2019.02.060 10.1016/j.chemosphere.2018.12.128 10.1115/1.4036639 10.1016/j.eswa.2005.12.008 10.1109/ACCESS.2021.3070105 10.1016/j.eswa.2004.08.009 10.3390/en11071636 10.1016/j.techfore.2016.03.006 10.1016/j.procs.2018.04.298 10.1016/j.jhydrol.2020.125188 10.1016/j.ejor.2017.11.054 10.1007/s11356-021-14591-1 10.1016/j.trc.2015.03.014 10.1109/ICRA.2019.8793490 10.1016/j.solener.2019.12.067 10.1016/j.apenergy.2017.12.051 10.1016/j.cie.2022.107966 10.1016/j.cie.2022.108204 10.1016/j.eneco.2020.104827 10.1016/j.cie.2019.106246 10.3390/en12061140 10.1093/bioinformatics/btw678 10.1007/s11517-021-02339-5 10.1016/j.cie.2021.107371 10.1016/j.techfore.2016.01.006 10.1007/s00500-020-04680-7 10.1142/S1793351X16500045 10.1109/TNSM.2021.3056912 10.1016/j.techfore.2016.01.015 10.1016/j.ins.2019.09.039 10.1016/j.techfore.2019.03.002 |
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Keywords | Gated Recurrent Unit (GRU) Aircraft assembly technology Ensemble Empirical Mode Decomposition (EEMD) Technology prediction |
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References | Fischer (b0080) 2018; 270 Lin, Lu, Tsai (b0150) 2019; 36 Hasan (b0125) 2020; 11 Liu, Wang, Sun, Wang, Ding (b0175) 2019; 30 Xu, Li, Ming, Chen (b0300) 2022; 169 Wang, Luo (b0270) 2021; 108 Sun, Ren (b0255) 2021; 28 Punia, Singh, Madaan (b0200) 2020; 149 Apreda, Bonaccorsi, dell'Orletta, Fantoni (b0030) 2019; 141 Liu, W., Li, P., Wang, K., Lu, L., & Zhao, W. (2021). Coal-gangue interface detection based on ensemble empirical mode decomposition energy entropy. IEEE Access (99), 1-1. Yan, Liu, Zhu, Wang, Dai, Cao (b0305) 2020; 20 Yeh, Chi, Hsu (b0310) 2010; 37 Mejia, Avelar-Sosa, Mederos, Santiago Ramirez, Diaz Roman (b0190) 2021; 157 Rahman, A., Srikumar, V., & Smith, A. D. (2018). Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks. Applied Energy PP(99), 1-1. Xie, Hao, Huang (b0295) 2020; 67 Shin, Lee, Hj (b0240) 2005; 28 Qiu, Ren, Suganthan (b0327) 2017; 54 Zhang, Zhang, Chen, Porter, Zhu, Lu (b0320) 2016; 105 Gao, X., Li, X., Zhao, B., Ji, W., Jing, X., & He, Y. (2019). Short-term electricity load forecasting model based on emd-gru with feature selection. Energies 12(6), 1140. Guo, Fang, Zhao, Wang (b0110) 2021; 161 Alade, Abd Rahman, Abbas, Yaakob, Saleh (b0015) 2020; 197 Fu, R., Zhang, Z., & Li, L. (2016). Using LSTM and GRU neural network methods for traffic flow prediction. 2016 31st Youth Academic Annual Conference of Chinese Association of Automation (YAC). IEEE, 7804912. Barnes, Mattsson, Change, Phillips (b0035) 2016; 104 Adamuthe, Thampi (b0005) 2019; 143 Cinar, Mirisaee, Goswami, Gaussier, Ait-Bachir (b0050) 2018; 312 Deng, Z., Shuanggao, H., & Xiang. (2023). Coordinate transformation uncertainty analysis and reduction using hybrid reference system for aircraft assembly. Kang, Tan, Yuan (b0326) 2017; 6856139 Gai, Zhang, Guo, Shi, Wu, Chen (b0090) 2020; 165 Zhao, Deng, Cai, Chen (b0325) 2019; 220 Söderberg, Wärmefjord, Lindkvist (b0245) 2015; 64 Wu, Q., Jiang, Z., Hong, K., Liu, H., & Ding, J. (2021). Tensor-based recurrent neural network and multi-modal prediction with its applications in traffic network management. IEEE Transactions on Network and Service Management (99), 1-1. Bian, Jiang, Ke (b0040) 2019; 104 Ali, Prasad (b0025) 2019; 104 Song, Y., Tian, Y., Gang, W., et al. (2019). 2D LiDAR map prediction via estimating motion flow with GRU. IEEE (99), 1-1. Cho, Yoon, Kim (b0045) 2016; 107 Fang, Guo, Liao, Huang, Yang, Liu (b0075) 2020; 140 Ke, Hongbin, Chengkang, Brown (b0135) 2019; 99 Devi, Maragatham, Boopathi (b0065) 2020; 24 Liu, Xiao, Song (b0180) 2021; 59 Alade, Abd Rahman, Saleh (b0020) 2019; 183 Salah, Ali, Ali, Mohamed (b0215) 2018; 11 Sheikh, Rabiee, Nasir, Oztekin (b0225) 2022; 166 Wen, Yue, Hunt, Shi (b0280) 2018; 46 Terragni, Fersini, Messina (b0260) 2020; 512 Wang, Liu, Zhou, Wen (b0265) 2018; 46 Wang, Wang (b0275) 2020; 90 Shen, Tan, Zhang, Zeng, Xu (b0235) 2018; 131 Pietrobelli, Puppato (b0195) 2015; 110 Wu, Tzeng, Goo, Fang (b0290) 2007; 32 Dakdouk, Xi (b0055) 2017; 139 Gui, Xu (b0105) 2021; 9 Hanson, Yang, Paliwal, Zhou (b0115) 2016; 2016 Ma, Tao, Wang (b0185) 2015; 54 Liu, Lee, Huang, Chiu (b0165) 2020; 37 Ramazan (b0210) 2021; 154 Hao, Zhang, Ma (b0120) 2016; 10 Esmaelian, Tavana, Di Caprio, Ansari (b0070) 2017; 125 Lin, Sun (b0155) 2020; 13 Huang, Li, Zhang, Ren (b0130) 2021; 768 Shen, Neusypin, Selezneva, Proletarskii (b0230) 2018; 61 Gao, Huang, Zhang, Han, Lin (b0100) 2020; 589 Guo (10.1016/j.eswa.2024.123208_b0110) 2021; 161 Lin (10.1016/j.eswa.2024.123208_b0150) 2019; 36 Terragni (10.1016/j.eswa.2024.123208_b0260) 2020; 512 Wang (10.1016/j.eswa.2024.123208_b0265) 2018; 46 Fischer (10.1016/j.eswa.2024.123208_b0080) 2018; 270 Fang (10.1016/j.eswa.2024.123208_b0075) 2020; 140 10.1016/j.eswa.2024.123208_b0160 Ma (10.1016/j.eswa.2024.123208_b0185) 2015; 54 Ali (10.1016/j.eswa.2024.123208_b0025) 2019; 104 Huang (10.1016/j.eswa.2024.123208_b0130) 2021; 768 Barnes (10.1016/j.eswa.2024.123208_b0035) 2016; 104 Wang (10.1016/j.eswa.2024.123208_b0270) 2021; 108 Alade (10.1016/j.eswa.2024.123208_b0020) 2019; 183 Yeh (10.1016/j.eswa.2024.123208_b0310) 2010; 37 Wang (10.1016/j.eswa.2024.123208_b0275) 2020; 90 Yan (10.1016/j.eswa.2024.123208_b0305) 2020; 20 Punia (10.1016/j.eswa.2024.123208_b0200) 2020; 149 Hao (10.1016/j.eswa.2024.123208_b0120) 2016; 10 Cinar (10.1016/j.eswa.2024.123208_b0050) 2018; 312 Adamuthe (10.1016/j.eswa.2024.123208_b0005) 2019; 143 Söderberg (10.1016/j.eswa.2024.123208_b0245) 2015; 64 Zhang (10.1016/j.eswa.2024.123208_b0320) 2016; 105 Devi (10.1016/j.eswa.2024.123208_b0065) 2020; 24 Lin (10.1016/j.eswa.2024.123208_b0155) 2020; 13 Salah (10.1016/j.eswa.2024.123208_b0215) 2018; 11 Shin (10.1016/j.eswa.2024.123208_b0240) 2005; 28 Hanson (10.1016/j.eswa.2024.123208_b0115) 2016; 2016 Liu (10.1016/j.eswa.2024.123208_b0175) 2019; 30 Xie (10.1016/j.eswa.2024.123208_b0295) 2020; 67 10.1016/j.eswa.2024.123208_b0060 Shen (10.1016/j.eswa.2024.123208_b0230) 2018; 61 Gui (10.1016/j.eswa.2024.123208_b0105) 2021; 9 Liu (10.1016/j.eswa.2024.123208_b0180) 2021; 59 Esmaelian (10.1016/j.eswa.2024.123208_b0070) 2017; 125 Bian (10.1016/j.eswa.2024.123208_b0040) 2019; 104 Dakdouk (10.1016/j.eswa.2024.123208_b0055) 2017; 139 Cho (10.1016/j.eswa.2024.123208_b0045) 2016; 107 Wu (10.1016/j.eswa.2024.123208_b0290) 2007; 32 Zhao (10.1016/j.eswa.2024.123208_b0325) 2019; 220 Ramazan (10.1016/j.eswa.2024.123208_b0210) 2021; 154 Sun (10.1016/j.eswa.2024.123208_b0255) 2021; 28 10.1016/j.eswa.2024.123208_b0250 Xu (10.1016/j.eswa.2024.123208_b0300) 2022; 169 Apreda (10.1016/j.eswa.2024.123208_b0030) 2019; 141 Hasan (10.1016/j.eswa.2024.123208_b0125) 2020; 11 Gao (10.1016/j.eswa.2024.123208_b0100) 2020; 589 Wen (10.1016/j.eswa.2024.123208_b0280) 2018; 46 Alade (10.1016/j.eswa.2024.123208_b0015) 2020; 197 10.1016/j.eswa.2024.123208_b0095 Ke (10.1016/j.eswa.2024.123208_b0135) 2019; 99 Shen (10.1016/j.eswa.2024.123208_b0235) 2018; 131 Pietrobelli (10.1016/j.eswa.2024.123208_b0195) 2015; 110 Mejia (10.1016/j.eswa.2024.123208_b0190) 2021; 157 10.1016/j.eswa.2024.123208_b0205 Qiu (10.1016/j.eswa.2024.123208_b0327) 2017; 54 Kang (10.1016/j.eswa.2024.123208_b0326) 2017; 6856139 Sheikh (10.1016/j.eswa.2024.123208_b0225) 2022; 166 Gai (10.1016/j.eswa.2024.123208_b0090) 2020; 165 10.1016/j.eswa.2024.123208_b0085 10.1016/j.eswa.2024.123208_b0285 Liu (10.1016/j.eswa.2024.123208_b0165) 2020; 37 |
References_xml | – volume: 54 start-page: 246 year: 2017 end-page: 255 ident: b0327 article-title: Empirical Mode Decomposition based ensemble deep learning for load demand time series forecasting publication-title: Applied Soft Computing contributor: fullname: Suganthan – volume: 197 start-page: 485 year: 2020 end-page: 490 ident: b0015 article-title: Application of support vector regression and artificial neural network for prediction of specific heat capacity of aqueous nanofluids of copper oxide publication-title: Solar Energy contributor: fullname: Saleh – volume: 6856139 start-page: 1 year: 2017 end-page: 22 ident: b0326 article-title: Short-Term Wind Speed Prediction Using EEMD-LSSVM Model publication-title: Advances in Meteorology contributor: fullname: Yuan – volume: 28 start-page: 56580 year: 2021 end-page: 56594 ident: b0255 article-title: Short-term prediction of carbon emissions based on the EEMD-PSOBP model publication-title: Environmental Science and Pollution Research contributor: fullname: Ren – volume: 10 start-page: 417 year: 2016 end-page: 439 ident: b0120 article-title: Deep learning publication-title: International Journal of Semantic Computing contributor: fullname: Ma – volume: 107 start-page: 1 year: 2016 end-page: 12 ident: b0045 article-title: An industrial technology roadmap for supporting public r&d planning publication-title: Technological Forecasting & Social Change contributor: fullname: Kim – volume: 157 year: 2021 ident: b0190 article-title: Prediction of time series using an analysis filter bank of lstm units publication-title: Computers & Industrial Engineering contributor: fullname: Diaz Roman – volume: 312 start-page: 177 year: 2018 end-page: 186 ident: b0050 article-title: Period-aware content attention rnns for time series forecasting with missing values publication-title: Neurocomputing contributor: fullname: Ait-Bachir – volume: 28 start-page: 127 year: 2005 end-page: 135 ident: b0240 article-title: An application of support vector machines in bankruptcy prediction model publication-title: Expert Systems with Applications contributor: fullname: Hj – volume: 110 start-page: 117 year: 2015 end-page: 125 ident: b0195 article-title: Technology foresight and industrial strategy in developing countries publication-title: Merit Working Papers contributor: fullname: Puppato – volume: 161 year: 2021 ident: b0110 article-title: The hybrid prophet-svr approach for forecasting product time series demand with seasonality publication-title: Computers & Industrial Engineering contributor: fullname: Wang – volume: 141 start-page: 277 year: 2019 end-page: 288 ident: b0030 article-title: Expert forecast and realized outcomes in technology foresight publication-title: Technological Forecasting and Social Change contributor: fullname: Fantoni – volume: 67 start-page: 7034 year: 2020 end-page: 7043 ident: b0295 article-title: Data-driven modeling based on two-stream λ gated recurrent unit network with soft sensor application publication-title: IEEE Transactions on Industrial Electronics contributor: fullname: Huang – volume: 149 year: 2020 ident: b0200 article-title: A cross-temporal hierarchical framework and deep learning for supply chain forecasting publication-title: Computers & Industrial Engineering contributor: fullname: Madaan – volume: 105 start-page: 179 year: 2016 end-page: 191 ident: b0320 article-title: Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research publication-title: Technological Forecasting and Social Change contributor: fullname: Lu – volume: 64 start-page: 17 year: 2015 end-page: 20 ident: b0245 article-title: Variation simulation of stress during assembly of composite parts publication-title: CIRP Annals – Manufacturing Technology contributor: fullname: Lindkvist – volume: 270 start-page: 1 year: 2018 end-page: 16 ident: b0080 article-title: Deep learning with long short-term memory networks for financial market predictions publication-title: European Journal of Operational Research contributor: fullname: Fischer – volume: 220 start-page: 486 year: 2019 end-page: 492 ident: b0325 article-title: Long short-term memory – Fully connected (lstm-fc) neural network for pm 2.5 concentration prediction publication-title: Chemosphere contributor: fullname: Chen – volume: 9 start-page: 53306 year: 2021 end-page: 53316 ident: b0105 article-title: Technology forecasting using deep learning neural network: Taking the case of robotics publication-title: IEEE Access contributor: fullname: Xu – volume: 11 start-page: 1636 year: 2018 ident: b0215 article-title: Optimal deep learning lstm model for electric load forecasting using feature selection and genetic algorithm: Comparison with machine learning approaches publication-title: Energies contributor: fullname: Mohamed – volume: 90 year: 2020 ident: b0275 article-title: Energy futures and spots prices forecasting by hybrid sw-gru with emd and error evaluation publication-title: Energy Economics contributor: fullname: Wang – volume: 13 start-page: 1 year: 2020 end-page: 21 ident: b0155 article-title: Crude oil prices forecasting: An approach of using ceemdan-based multi-layer gated recurrent unit networks publication-title: Energies contributor: fullname: Sun – volume: 46 start-page: 272 year: 2018 end-page: 281 ident: b0280 article-title: Feasibility analysis of composite fuselage shape control via finite element analysis publication-title: Journal of Manufacturing Systems contributor: fullname: Shi – volume: 125 start-page: 188 year: 2017 end-page: 205 ident: b0070 article-title: A multiple correspondence analysis model for evaluating technology foresight methods publication-title: Technological Forecasting and Social Change contributor: fullname: Ansari – volume: 108 year: 2021 ident: b0270 article-title: An intelligent quantitative trading system based on intuitionistic-gru fuzzy neural networks publication-title: Applied Soft Computing contributor: fullname: Luo – volume: 183 start-page: 74 year: 2019 end-page: 82 ident: b0020 article-title: Predicting the specific heat capacity of alumina/ethylene glycol nanofluids using support vector regression model optimized with Bayesian algorithm publication-title: Solar Energy contributor: fullname: Saleh – volume: 139 start-page: 1 year: 2017 end-page: 8 ident: b0055 article-title: Tool accessibility analysis for robotic drilling and fastening publication-title: Journal of Manufacturing Science & Engineering contributor: fullname: Xi – volume: 589 year: 2020 ident: b0100 article-title: Short-term runoff prediction with gru and lstm networks without requiring time step optimization during sample generation publication-title: Journal of Hydrology contributor: fullname: Lin – volume: 99 year: 2019 ident: b0135 article-title: Short-term electrical load forecasting method based on stacked auto-encoding and gru neural network publication-title: Evolutionary Intelligence contributor: fullname: Brown – volume: 131 start-page: 895 year: 2018 end-page: 903 ident: b0235 article-title: Deep learning with gated recurrent unit networks for financial sequence predictions publication-title: Procedia Computer Science contributor: fullname: Xu – volume: 36 start-page: 1 year: 2019 end-page: 8 ident: b0150 article-title: Feature selection in single and ensemble learning-based bankruptcy prediction models publication-title: Expert Systems contributor: fullname: Tsai – volume: 30 start-page: 461 year: 2019 end-page: 466 ident: b0175 article-title: Motion simulation technology for automatic drilling and riveting off-line programming systems publication-title: Zhongguo Jixie Gongcheng/China Mechanical Engineering contributor: fullname: Ding – volume: 165 start-page: 1 year: 2020 end-page: 10 ident: b0090 article-title: Construction and uncertainty evaluation of large-scale measurement system of laser trackers in aircraft assembly publication-title: Measurement contributor: fullname: Chen – volume: 11 year: 2020 ident: b0125 article-title: A methodological approach for predicting covid-19 epidemic using eemd-ann hybrid model publication-title: Internet of Things contributor: fullname: Hasan – volume: 140 year: 2020 ident: b0075 article-title: A parallel gated recurrent units (p-grus) network for the shifting lateness bottleneck prediction in make-to-order production system publication-title: Computers & Industrial Engineering contributor: fullname: Liu – volume: 37 start-page: 1 year: 2020 end-page: 16 ident: b0165 article-title: Air pollution forecasting based on attention-based lstm neural network and ensemble learning publication-title: Expert Systems contributor: fullname: Chiu – volume: 154 year: 2021 ident: b0210 article-title: Cost-oriented lstm methods for possible expansion of control charting signals publication-title: Computers & Industrial Engineering contributor: fullname: Ramazan – volume: 61 start-page: 279 year: 2018 end-page: 286 ident: b0230 article-title: Research on high-precision measurement systems of modern aircraft publication-title: Russian Aeronautics contributor: fullname: Proletarskii – volume: 166 year: 2022 ident: b0225 article-title: An integrated decision support system for multi-target forecasting: A case study of energy load prediction for a solar-powered residential house publication-title: Computers & Industrial Engineering contributor: fullname: Oztekin – volume: 768 year: 2021 ident: b0130 article-title: Pm2.5 concentration forecasting at surface monitoring sites using gru neural network based on empirical mode decomposition publication-title: Science of The Total Environment contributor: fullname: Ren – volume: 37 start-page: 1535 year: 2010 end-page: 1541 ident: b0310 article-title: A hybrid approach of DEA, rough set and support vector machines for business failure prediction publication-title: Expert Systems with Applications contributor: fullname: Hsu – volume: 104 start-page: 200 year: 2016 end-page: 211 ident: b0035 article-title: Understanding current and future issues in collaborative consumption: A four-stage delphi study publication-title: Technological Forecasting and Social Change contributor: fullname: Phillips – volume: 32 start-page: 397 year: 2007 end-page: 408 ident: b0290 article-title: A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy publication-title: Expert Systems with Applications contributor: fullname: Fang – volume: 2016 start-page: 685 year: 2016 end-page: 692 ident: b0115 article-title: Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks publication-title: Bioinformatics contributor: fullname: Zhou – volume: 104 start-page: 1521 year: 2019 end-page: 1530 ident: b0040 article-title: End stiffness modeling for automatic horizontal dual-machine cooperative drilling and riveting system publication-title: International Journal of Advanced Manufacturing Technology contributor: fullname: Ke – volume: 512 start-page: 581 year: 2020 end-page: 594 ident: b0260 article-title: Constrained relational topic models publication-title: Information Sciences contributor: fullname: Messina – volume: 169 start-page: 1 year: 2022 end-page: 14 ident: b0300 article-title: A novel multi-scale cnn and attention mechanism method with multi-sensor signal for remaining useful life prediction publication-title: Computers & Industrial Engineering contributor: fullname: Chen – volume: 104 start-page: 281 year: 2019 end-page: 295 ident: b0025 article-title: Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition publication-title: Renewable and Sustainable Energy Reviews contributor: fullname: Prasad – volume: 59 start-page: 721 year: 2021 end-page: 731 ident: b0180 article-title: Precise detection of early breast tumor using a novel EEMD-based feature extraction approach by UWB microwave publication-title: Medical and Biological Engineering and Computing contributor: fullname: Song – volume: 54 start-page: 187 year: 2015 end-page: 197 ident: b0185 article-title: Long short-term memory neural network for traffic speed prediction using remote microwave sensor data publication-title: Transportation Research Part C Emerging Technologies contributor: fullname: Wang – volume: 20 start-page: 49 year: 2020 end-page: 56 ident: b0305 article-title: Real-time abnormal light curve detection based on a gated recurrent unit network publication-title: Research in Astronomy and Astro-Physics contributor: fullname: Cao – volume: 24 start-page: 12391 year: 2020 end-page: 12411 ident: b0065 article-title: Hourly day-ahead wind power forecasting with the EEMD-CSO-LSTM-EFG deep learning technique publication-title: Soft Computing contributor: fullname: Boopathi – volume: 46 start-page: 322 year: 2018 end-page: 330 ident: b0265 article-title: Emerging nanogenerator technology in china: A review and forecast using integrating bibliometrics, patent analysis and technology roadmapping methods publication-title: Nano Energy contributor: fullname: Wen – volume: 143 start-page: 181 year: 2019 end-page: 189 ident: b0005 article-title: Technology forecasting: A case study of computational technologies publication-title: Technological forecasting and social change contributor: fullname: Thampi – volume: 61 start-page: 279 issue: 2 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0230 article-title: Research on high-precision measurement systems of modern aircraft publication-title: Russian Aeronautics doi: 10.3103/S1068799818020186 contributor: fullname: Shen – volume: 64 start-page: 17 issue: 1 year: 2015 ident: 10.1016/j.eswa.2024.123208_b0245 article-title: Variation simulation of stress during assembly of composite parts publication-title: CIRP Annals – Manufacturing Technology doi: 10.1016/j.cirp.2015.04.048 contributor: fullname: Söderberg – volume: 37 start-page: 1535 issue: 2 year: 2010 ident: 10.1016/j.eswa.2024.123208_b0310 article-title: A hybrid approach of DEA, rough set and support vector machines for business failure prediction publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2009.06.088 contributor: fullname: Yeh – volume: 312 start-page: 177 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0050 article-title: Period-aware content attention rnns for time series forecasting with missing values publication-title: Neurocomputing doi: 10.1016/j.neucom.2018.05.090 contributor: fullname: Cinar – volume: 67 start-page: 7034 issue: 8 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0295 article-title: Data-driven modeling based on two-stream λ gated recurrent unit network with soft sensor application publication-title: IEEE Transactions on Industrial Electronics doi: 10.1109/TIE.2019.2927197 contributor: fullname: Xie – volume: 6856139 start-page: 1 year: 2017 ident: 10.1016/j.eswa.2024.123208_b0326 article-title: Short-Term Wind Speed Prediction Using EEMD-LSSVM Model publication-title: Advances in Meteorology doi: 10.1155/2017/6856139 contributor: fullname: Kang – volume: 46 start-page: 272 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0280 article-title: Feasibility analysis of composite fuselage shape control via finite element analysis publication-title: Journal of Manufacturing Systems doi: 10.1016/j.jmsy.2018.01.008 contributor: fullname: Wen – volume: 11 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0125 article-title: A methodological approach for predicting covid-19 epidemic using eemd-ann hybrid model publication-title: Internet of Things doi: 10.1016/j.iot.2020.100228 contributor: fullname: Hasan – ident: 10.1016/j.eswa.2024.123208_b0085 doi: 10.1109/YAC.2016.7804912 – volume: 99 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0135 article-title: Short-term electrical load forecasting method based on stacked auto-encoding and gru neural network publication-title: Evolutionary Intelligence contributor: fullname: Ke – volume: 108 issue: 3 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0270 article-title: An intelligent quantitative trading system based on intuitionistic-gru fuzzy neural networks publication-title: Applied Soft Computing contributor: fullname: Wang – volume: 37 start-page: 1 issue: 3 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0165 article-title: Air pollution forecasting based on attention-based lstm neural network and ensemble learning publication-title: Expert Systems doi: 10.1111/exsy.12511 contributor: fullname: Liu – volume: 36 start-page: 1 issue: 1 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0150 article-title: Feature selection in single and ensemble learning-based bankruptcy prediction models publication-title: Expert Systems doi: 10.1111/exsy.12335 contributor: fullname: Lin – volume: 768 issue: 3 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0130 article-title: Pm2.5 concentration forecasting at surface monitoring sites using gru neural network based on empirical mode decomposition publication-title: Science of The Total Environment contributor: fullname: Huang – volume: 30 start-page: 461 issue: 4 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0175 article-title: Motion simulation technology for automatic drilling and riveting off-line programming systems publication-title: Zhongguo Jixie Gongcheng/China Mechanical Engineering contributor: fullname: Liu – volume: 13 start-page: 1 issue: 7 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0155 article-title: Crude oil prices forecasting: An approach of using ceemdan-based multi-layer gated recurrent unit networks publication-title: Energies doi: 10.3390/en13071543 contributor: fullname: Lin – volume: 125 start-page: 188 year: 2017 ident: 10.1016/j.eswa.2024.123208_b0070 article-title: A multiple correspondence analysis model for evaluating technology foresight methods publication-title: Technological Forecasting and Social Change doi: 10.1016/j.techfore.2017.07.022 contributor: fullname: Esmaelian – volume: 104 start-page: 281 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0025 article-title: Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition publication-title: Renewable and Sustainable Energy Reviews doi: 10.1016/j.rser.2019.01.014 contributor: fullname: Ali – volume: 54 start-page: 246 year: 2017 ident: 10.1016/j.eswa.2024.123208_b0327 article-title: Empirical Mode Decomposition based ensemble deep learning for load demand time series forecasting publication-title: Applied Soft Computing doi: 10.1016/j.asoc.2017.01.015 contributor: fullname: Qiu – volume: 141 start-page: 277 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0030 article-title: Expert forecast and realized outcomes in technology foresight publication-title: Technological Forecasting and Social Change doi: 10.1016/j.techfore.2018.12.006 contributor: fullname: Apreda – volume: 104 start-page: 1521 issue: 4 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0040 article-title: End stiffness modeling for automatic horizontal dual-machine cooperative drilling and riveting system publication-title: International Journal of Advanced Manufacturing Technology doi: 10.1007/s00170-019-04087-1 contributor: fullname: Bian – volume: 161 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0110 article-title: The hybrid prophet-svr approach for forecasting product time series demand with seasonality publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2021.107598 contributor: fullname: Guo – volume: 110 start-page: 117 issue: 3 year: 2015 ident: 10.1016/j.eswa.2024.123208_b0195 article-title: Technology foresight and industrial strategy in developing countries publication-title: Merit Working Papers contributor: fullname: Pietrobelli – ident: 10.1016/j.eswa.2024.123208_b0160 doi: 10.1109/ACCESS.2021.3070447 – volume: 46 start-page: 322 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0265 article-title: Emerging nanogenerator technology in china: A review and forecast using integrating bibliometrics, patent analysis and technology roadmapping methods publication-title: Nano Energy doi: 10.1016/j.nanoen.2018.02.020 contributor: fullname: Wang – volume: 183 start-page: 74 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0020 article-title: Predicting the specific heat capacity of alumina/ethylene glycol nanofluids using support vector regression model optimized with Bayesian algorithm publication-title: Solar Energy doi: 10.1016/j.solener.2019.02.060 contributor: fullname: Alade – volume: 220 start-page: 486 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0325 article-title: Long short-term memory – Fully connected (lstm-fc) neural network for pm 2.5 concentration prediction publication-title: Chemosphere doi: 10.1016/j.chemosphere.2018.12.128 contributor: fullname: Zhao – volume: 139 start-page: 1 year: 2017 ident: 10.1016/j.eswa.2024.123208_b0055 article-title: Tool accessibility analysis for robotic drilling and fastening publication-title: Journal of Manufacturing Science & Engineering doi: 10.1115/1.4036639 contributor: fullname: Dakdouk – volume: 32 start-page: 397 issue: 2 year: 2007 ident: 10.1016/j.eswa.2024.123208_b0290 article-title: A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2005.12.008 contributor: fullname: Wu – volume: 20 start-page: 49 issue: 1 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0305 article-title: Real-time abnormal light curve detection based on a gated recurrent unit network publication-title: Research in Astronomy and Astro-Physics contributor: fullname: Yan – volume: 165 start-page: 1 issue: 1 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0090 article-title: Construction and uncertainty evaluation of large-scale measurement system of laser trackers in aircraft assembly publication-title: Measurement contributor: fullname: Gai – volume: 9 start-page: 53306 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0105 article-title: Technology forecasting using deep learning neural network: Taking the case of robotics publication-title: IEEE Access doi: 10.1109/ACCESS.2021.3070105 contributor: fullname: Gui – volume: 154 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0210 article-title: Cost-oriented lstm methods for possible expansion of control charting signals publication-title: Computers & Industrial Engineering contributor: fullname: Ramazan – volume: 28 start-page: 127 issue: 1 year: 2005 ident: 10.1016/j.eswa.2024.123208_b0240 article-title: An application of support vector machines in bankruptcy prediction model publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2004.08.009 contributor: fullname: Shin – volume: 11 start-page: 1636 issue: 7 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0215 article-title: Optimal deep learning lstm model for electric load forecasting using feature selection and genetic algorithm: Comparison with machine learning approaches publication-title: Energies doi: 10.3390/en11071636 contributor: fullname: Salah – volume: 107 start-page: 1 year: 2016 ident: 10.1016/j.eswa.2024.123208_b0045 article-title: An industrial technology roadmap for supporting public r&d planning publication-title: Technological Forecasting & Social Change doi: 10.1016/j.techfore.2016.03.006 contributor: fullname: Cho – volume: 131 start-page: 895 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0235 article-title: Deep learning with gated recurrent unit networks for financial sequence predictions publication-title: Procedia Computer Science doi: 10.1016/j.procs.2018.04.298 contributor: fullname: Shen – volume: 589 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0100 article-title: Short-term runoff prediction with gru and lstm networks without requiring time step optimization during sample generation publication-title: Journal of Hydrology doi: 10.1016/j.jhydrol.2020.125188 contributor: fullname: Gao – volume: 270 start-page: 1 issue: 2 year: 2018 ident: 10.1016/j.eswa.2024.123208_b0080 article-title: Deep learning with long short-term memory networks for financial market predictions publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2017.11.054 contributor: fullname: Fischer – volume: 28 start-page: 56580 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0255 article-title: Short-term prediction of carbon emissions based on the EEMD-PSOBP model publication-title: Environmental Science and Pollution Research doi: 10.1007/s11356-021-14591-1 contributor: fullname: Sun – volume: 54 start-page: 187 year: 2015 ident: 10.1016/j.eswa.2024.123208_b0185 article-title: Long short-term memory neural network for traffic speed prediction using remote microwave sensor data publication-title: Transportation Research Part C Emerging Technologies doi: 10.1016/j.trc.2015.03.014 contributor: fullname: Ma – ident: 10.1016/j.eswa.2024.123208_b0060 – ident: 10.1016/j.eswa.2024.123208_b0250 doi: 10.1109/ICRA.2019.8793490 – volume: 197 start-page: 485 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0015 article-title: Application of support vector regression and artificial neural network for prediction of specific heat capacity of aqueous nanofluids of copper oxide publication-title: Solar Energy doi: 10.1016/j.solener.2019.12.067 contributor: fullname: Alade – ident: 10.1016/j.eswa.2024.123208_b0205 doi: 10.1016/j.apenergy.2017.12.051 – volume: 166 year: 2022 ident: 10.1016/j.eswa.2024.123208_b0225 article-title: An integrated decision support system for multi-target forecasting: A case study of energy load prediction for a solar-powered residential house publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2022.107966 contributor: fullname: Sheikh – volume: 169 start-page: 1 year: 2022 ident: 10.1016/j.eswa.2024.123208_b0300 article-title: A novel multi-scale cnn and attention mechanism method with multi-sensor signal for remaining useful life prediction publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2022.108204 contributor: fullname: Xu – volume: 90 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0275 article-title: Energy futures and spots prices forecasting by hybrid sw-gru with emd and error evaluation publication-title: Energy Economics doi: 10.1016/j.eneco.2020.104827 contributor: fullname: Wang – volume: 140 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0075 article-title: A parallel gated recurrent units (p-grus) network for the shifting lateness bottleneck prediction in make-to-order production system publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2019.106246 contributor: fullname: Fang – ident: 10.1016/j.eswa.2024.123208_b0095 doi: 10.3390/en12061140 – volume: 2016 start-page: 685 issue: 5 year: 2016 ident: 10.1016/j.eswa.2024.123208_b0115 article-title: Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks publication-title: Bioinformatics doi: 10.1093/bioinformatics/btw678 contributor: fullname: Hanson – volume: 59 start-page: 721 issue: 3 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0180 article-title: Precise detection of early breast tumor using a novel EEMD-based feature extraction approach by UWB microwave publication-title: Medical and Biological Engineering and Computing doi: 10.1007/s11517-021-02339-5 contributor: fullname: Liu – volume: 157 year: 2021 ident: 10.1016/j.eswa.2024.123208_b0190 article-title: Prediction of time series using an analysis filter bank of lstm units publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2021.107371 contributor: fullname: Mejia – volume: 104 start-page: 200 year: 2016 ident: 10.1016/j.eswa.2024.123208_b0035 article-title: Understanding current and future issues in collaborative consumption: A four-stage delphi study publication-title: Technological Forecasting and Social Change doi: 10.1016/j.techfore.2016.01.006 contributor: fullname: Barnes – volume: 24 start-page: 12391 issue: 16 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0065 article-title: Hourly day-ahead wind power forecasting with the EEMD-CSO-LSTM-EFG deep learning technique publication-title: Soft Computing doi: 10.1007/s00500-020-04680-7 contributor: fullname: Devi – volume: 10 start-page: 417 issue: 03 year: 2016 ident: 10.1016/j.eswa.2024.123208_b0120 article-title: Deep learning publication-title: International Journal of Semantic Computing doi: 10.1142/S1793351X16500045 contributor: fullname: Hao – ident: 10.1016/j.eswa.2024.123208_b0285 doi: 10.1109/TNSM.2021.3056912 – volume: 149 issue: 3 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0200 article-title: A cross-temporal hierarchical framework and deep learning for supply chain forecasting publication-title: Computers & Industrial Engineering contributor: fullname: Punia – volume: 105 start-page: 179 year: 2016 ident: 10.1016/j.eswa.2024.123208_b0320 article-title: Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research publication-title: Technological Forecasting and Social Change doi: 10.1016/j.techfore.2016.01.015 contributor: fullname: Zhang – volume: 512 start-page: 581 year: 2020 ident: 10.1016/j.eswa.2024.123208_b0260 article-title: Constrained relational topic models publication-title: Information Sciences doi: 10.1016/j.ins.2019.09.039 contributor: fullname: Terragni – volume: 143 start-page: 181 year: 2019 ident: 10.1016/j.eswa.2024.123208_b0005 article-title: Technology forecasting: A case study of computational technologies publication-title: Technological forecasting and social change doi: 10.1016/j.techfore.2019.03.002 contributor: fullname: Adamuthe |
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