A new algorithm for real economy benefit evaluation based on big data analysis

• Published in: Open Physics Vol. 16; no. 1; pp. 967 - 977
• Main Authors: Wang, Zhuo, Saedudin, Rd Rohmat
• Format: Journal Article
• Language: English
• Published: De Gruyter 01.01.2018
• Subjects: 07.05.Hd; 87.15.ag; 88.05.Lg; benefit; Big data analysis; evaluation; real economy
• ISSN: 2391-5471; 2391-5471
• DOI: 10.1515/phys-2018-0118

Based on the Sino-foreign petroleum cooperation project, the benefit evaluation algorithm of real economy based on big data analysis is proposed. The investment payback period, net present value, internal rate of return, discounted profit after investment and option value are selected as the benefit evaluation indicators of the real economy. The benchmark yield, discount rate and oil option parameters are defined as the benefits evaluation parameters of the real economy. Through the Delphi method and the analytic hierarchy process, the weight of each factor is specified. The method of expert independent scoring is used to construct the judgment matrix, and the consistency check is performed on the sort. The feature quantity matrix of the evaluation indicator is established to perform dimensionless processing on the original data. The project’s economic benefit indicators are divided into positive indicators of “ideal economic benefits” and negative indicators of “negative economic benefits”, the grey correlations are calculated, and real economic benefits are assessed. The results of project example analysis show that the algorithm not only realizes the whole life cycle management of overseas oil and gas cooperation projects, but also conducts tracking and evaluation of project implementation and economic benefits during the implementation process, and conducts sensitivity analysis on key indicators, that provides effective decision support for managers.