摘要
随着国民经济的快速发展,工业、农业、水产养殖业以及生活污水排放带来的水体氨氮污染日益加重,如何有效治理氨氮污染,已成为人们关心的热点问题。与实验室取样检测相比,智能算法预测水体氨氮含量的方法由于具有实时性、检测时间短、误差小等优点,正逐步被应用到水体氨氮污染治理中。综述神经网络、粒子群、遗传算法等智能算法在水体氨氮含量预测中的研究进展,指出多种智能算法的组合应用将是预测水体氨氮含量、有效治理氨氮污染的应用发展方向,并提出进一步完善研究方法的建议。
With the rapid development of national economy, ammonia nitrogen pollution in water body caused by industrial, agricultural, aquaculture and domestic sewage discharge is increasing. How to effectively control ammonia nitrogen pollution has become a hot issue of concern. Compared with laboratory sampling and detection, the method of predicting ammonia nitrogen content in water body by intelligent algorithm is gradually applied to the treatment of ammonia nitrogen pollution in water body due to its advantages of online real-time, short time and small error. This paper summarizes the research progress of intelligent algorithms such as artificial neural network, particle swarm optimization and genetic algorithm in predicting ammonia nitrogen content in water body, points out that the combination of several intelligent algorithms will be the application and development direction of predicting ammonia nitrogen content in water body and effectively controlling ammonia nitrogen pollution, and puts forward some suggestions for further improving the research methods.
作者
巫莉莉
黄志宏
何斌斌
曾鸣
Wu Lili;Huang Zhihong;He Binbin;Zeng Ming(Modern Education Technology Center of South China Agricultural University ,Guangzhou, 510642,China)
出处
《中国农机化学报》
北大核心
2019年第6期191-196,共6页
Journal of Chinese Agricultural Mechanization
基金
国家重点研发计划(2017YFD0701702)
关键词
氨氮污染治理
智能算法
神经网络
向量机
水体氨氮预测
实时性
Ammonia Nitrogen pollution control
intelligent algorithms
neural network
vector machine
water ammonia Nitrogen Prediction
real-time
