摘要
粗糙集和粗糙元神经网络相结合进行三峡库区水质评价。针对评价因子较多,通过粗糙集进行数据预处理,降低模型的复杂性。对于库区数据非精确值或范围值时,采用粗糙元神经网络建立评价模型,提高了系统的正确性和可理解性,并将其应用在三峡库区水环境安全系统中。
Rough set method and roughness element neural network are combined for evaluating water quality aiming at the evaluation issue in Three Gorges Reservoir Area.In light of the problem of too many evaluation factors,the data is processed by rough set in order to reduce the complexity of the model.For those data of the Reservoir Area which are not precise or beyond the range of value,the roughness element neural network is used to set up the evaluation model.These have improved the correctness and comprehension of the system,and are applied to the water environment security system of Three Gorges Reservoir Area.
出处
《计算机应用与软件》
CSCD
2011年第5期193-196,共4页
Computer Applications and Software
关键词
粗糙集
粗糙元神经网络
水质评价
Rough set Roughness element nerual network Water quality evaluation
作者简介
李伟湋，博士生，主研领域：数据挖掘，粗糙集理论。
