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基于萤火虫算法的BP神经网络的水质评价 被引量:4
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作者 YAN Jian PAN Zhifu +1 位作者 TAN Jing TIAN Han 《南水北调与水利科技(中英文)》 CAS 北大核心 2020年第4期104-110,共7页
Assessment of water quality by firefly algorithm based on BP neural network model(FA-BP model)is built.In this model,the evaluation index function is constructed by BP Artificial Neural Network Algorithm(BP model),and... Assessment of water quality by firefly algorithm based on BP neural network model(FA-BP model)is built.In this model,the evaluation index function is constructed by BP Artificial Neural Network Algorithm(BP model),and Firefly Algorithm(FA model)is introduced to optimize weight values and thresholds to find the optimal solution.Fuzzy Comprehensive Evaluation method,Grey Incidence Analysis Algorithm and FA-BP model will be applied to evaluate the water quality of the five main rivers in Lianyungang City including Longwei,Yudai,Dapu,Paidan,and Dongyan River.The results show that the Fuzzy Comprehensive Evaluation method is difficult to use for slight pollution rivers with several slightly over standard indexes.It will be easy to ignore the impact of extreme indexes by Grey Incidence Analysis Algorithm.FA-BP model solves the shortcomings of the two methods.The evaluation results provide an important reference for the formulation of reasonable measures.It is a relatively comprehensive evaluation method and has a good application prospect in water quality evaluation. 展开更多
关键词 firefly algorithm BP neural network surface water assessment of water quality
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