A new intelligence fuzzy-based hybrid metaheuristic algorithm for analyzing the application of tea waste in concrete as natural fiber

• Published in: Computers and electronics in agriculture Vol. 190; p. 106420
• Main Authors: Cao, Yan, Zandi, Yousef, Rahimi, Abouzar, Wu, Yujia, Fu, Leijie, Wang, Qiangfeng, Denić, Nebojša, Amine Khadimallah, Mohamed, Milič, Momir, Paunović, Marija
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.11.2021; Elsevier BV
• Subjects: Adaptive systems; agriculture; Algorithms; Carbon dioxide; cement; compression strength; Compressive strength; Concrete; Concrete industry; electronics; Flexural strength; Fuzzy logic; Fuzzy-based hybrid; Heuristic methods; Hybrid systems; manufacturing; modulus of rupture; Natural Fiber; Pollution abatement; pollution control; Reinforced concrete; tea; Tea Waste; wastes; water requirement; Tea Waste; Concrete; Natural Fiber; Fuzzy-based hybrid
• ISSN: 0168-1699; 1872-7107
• DOI: 10.1016/j.compag.2021.106420

•Black tea production.•Fermentation is a crucial processing technique.•Black tea fermentation on the basis of convolutional neural network (CNN). Concrete is an ecologically friendly substance in which green concrete is a revolutionary subject in concrete industry records. The emphasis of this study was on the impact of Tea Waste (CA) as natural fiber onhardened concrete characteristics as a substitution for cement. Taking account of CO2 generation in cement manufacture, green concrete decreases emissions of CO2 into environmental production to an environmentally-friendly technique of pollution prevention. C1, C2, C3, C4 were then made of concrete of a class of 1, 2, 3, 4 kg reinforced in 1 m3 mix, then prepared and molded 4 distinct concrete types. After 28 days, the flexural and compressive strength tests have been carried out in a proper curing environment on the concrete. The findings were evaluated using the adaptive inference system neuro-fuzzy (ANFIS) to accurately predictthe concrete flexural and compressive strengthwith low error rates. Finally, the reinforced concrete with tea wastes raised the water requirement, but reduced the compressive and flexural strength compared to control mix, however, it was raised while using up to 5.4 kg waste in 1 m3 concrete. The result showed that up to 5 kg of tea wastes in 1 m3 of concrete could also be utilized as natural fibers. Also, ANFIS could show its outperformance in analyzing test results in predicting the compressive and flexural strength.