Abstract:A general optimization framework about watershed discharge was established based on artificial neutral network and genetic algorithm. Through simulating and optimizing the sampling data from sewage outlets and monitoring sections, the optimal reducing discharge strategies could be obtained to reach the permitted standards. Then combined with scenario analysis theory, the COD optimization research was studied on Zhushuntun-Dongjiangqiao (S1) and Dongjiangqiao-Dadingzishan (S2) functional areas in Songhua river-Harbin region. The average COD cut rates of Hejiagou and Songbei outlets were 23% and 25% respectively when the S1 was under criterion III for functional areas, while they increased to 64% and 42% when S1 was under criterion II. And when the S2 was under criterion II, the cut rates of Taiping, Ashen River and Hulan River were 18%, 53% and 25%, respectively. The computational intelligence based optimization method has high operability and practicality, and it also could get the optimal discharge strategy of each outlet scientifically and reasonably.
王祎, 李静文, 邵雪, 田在兴, 郭亮, 姜继平, 王鹏. 基于计算智能的流域污染排放优化模式研究[J]. 中国环境科学, 2012, 32(1): 173-180.
WANG Yi, LI Jing-Wen, SHAO Xue, TIAN Zai-Xing, GUO Liang, JIANG Ji-Ping, WANG Peng. Computational intelligence based optimization study on the watershed discharge of sewage. CHINA ENVIRONMENTAL SCIENCECE, 2012, 32(1): 173-180.