Application of T-S Fuzzy-Neural Network Model in Water Quality Comprehensive Evaluation

摘要

In order to comprehensively evaluate the water environment quality of Liuxi river Irrigation District in Guangzhou more effectively, the fuzzy neural network based on T-S model was used to evaluate and analyze the water quality characteristics of Liuxi river Irrigation District. Six indexes, including dissolved oxygen, chemical oxygen demand, ammonia nitrogen, permanganate index, total phosphorus and total nitrogen, which have important effects on water quality, were selected to establish an applicable comprehensive evaluation model for water quality. Water quality of two water sampling sections, the upstream Da’ao monitoring section and the downstream Liyuan monitoring section, were sampled and analyzed. The results show that the water quality evaluation results of the upstream Da’ao monitoring section are better than that of the downstream Liyuan monitoring section. The variation trend of water quality grade evaluated by the model is consistent with that of the real index data.