Suppr超能文献

基于模糊规则的溪流中农业面源污染浓度估算

Fuzzy rule based estimation of agricultural diffuse pollution concentration in streams.

作者信息

Singh Raj Mohan

机构信息

Department of Civil Engineering, Motilal Nehru National Institute of Technology, Allahabad-211 004, India.

出版信息

J Environ Sci Eng. 2008 Apr;50(2):147-52.

Abstract

Outflow from the agricultural fields carries diffuse pollutants like nutrients, pesticides, herbicides etc. and transports the pollutants into the nearby streams. It is a matter of serious concern for water managers and environmental researchers. The application of chemicals in the agricultural fields, and transport of these chemicals into streams are uncertain that cause complexity in reliable stream quality predictions. The chemical characteristics of applied chemical, percentage of area under the chemical application etc. are some of the main inputs that cause pollution concentration as output in streams. Each of these inputs and outputs may contain measurement errors. Fuzzy rule based model based on fuzzy sets suits to address uncertainties in inputs by incorporating overlapping membership functions for each of inputs even for limited data availability situations. In this study, the property of fuzzy sets to address the uncertainty in input-output relationship is utilized to obtain the estimate of concentrations of a herbicide, atrazine, in a stream. The data of White river basin, a part of the Mississippi river system, is used for developing the fuzzy rule based models. The performance of the developed methodology is found encouraging.

摘要

农田径流携带营养物质、农药、除草剂等扩散性污染物,并将这些污染物输送到附近的溪流中。这是水资源管理者和环境研究人员严重关切的问题。在农田中施用化学品以及这些化学品向溪流中的输送情况是不确定的,这给可靠的溪流质量预测带来了复杂性。所施用化学品的化学特性、化学品施用面积的百分比等是导致溪流中污染浓度作为输出的一些主要输入因素。这些输入和输出中的每一个都可能包含测量误差。基于模糊集的模糊规则模型适合通过为每个输入纳入重叠的隶属函数来处理输入中的不确定性,即使在数据可用性有限的情况下也是如此。在本研究中,利用模糊集处理输入 - 输出关系中不确定性的特性来获得溪流中一种除草剂阿特拉津浓度的估计值。密西西比河系统一部分的怀特河流域的数据被用于开发基于模糊规则的模型。所开发方法的性能令人鼓舞。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验