Research Article | OPEN ACCESS
Research on Performance Evaluation of Integrates with Agriculture Food Base and Supermarket
Yongqiang Chen
College of Economics and Management, Huazhong Agricultural University, Wuhan 430070,
School of Business, Jinggangshan University, Ji
Advance Journal of Food Science and Technology 2015 3:210-215
Received: August 31, 2014 | Accepted: October 11, 2014 | Published: February 05, 2015
Abstract
Performance evaluation of integrate with agriculture food base and supermarket is a research hotspot and difficulty in the theory and practice research of agriculture super-docking mode. The study presents an evaluation indicator system and a fuzzy neural network evaluation algorithm for evaluating performance of integrates with agriculture food base and supermarket. Firstly, a performance evaluation indicator system is designed through analyzing the similarities of general performance evaluation and the specialties of the evaluation of integrates with agriculture food base and supermarket; Secondly, the study integrates the advantages of fuzzy evaluation methods and BP neural network evaluation methods, designs a new algorithm structure, selects different learning methods and analyzes the algorithm performance, then presents a new fuzzy neural network evaluation algorithm; Finally, three integrates are taken for experimental examples and the results illustrate that the improved algorithm can be used for evaluating the performance of integrates with agriculture food base and supermarket feasibly and effectively and can provide reference for evaluating other complex systems.
Keywords:
BP neural network, fuzzy evaluation method, integrate with agriculture food base and supermarket, performance evaluation,
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CrossRef
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
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