摘要
首先采用随机函数生成训练样本,并利用'比例压缩法'进行预处理;而后采用'试错法'确定隐含层神经元数,最终建立了结构为7∶8∶1的BPANN的土壤环境质量评价模型,并采用Matlab6.0进行模拟计算。模型检验结果表明:所建模型的拟合精度、检验精度以及实际评价效果均较好,能够比较客观、准确地对城市土壤环境质量进行评价。对长春市城市表层土壤的评价结果表明,其总体环境质量较好,约81%的土壤面积符合国家一级土壤标准,但局部重金属污染不容忽视,应注意控制重金属污染物排放,以保证土壤资源的可持续利用。
The input and output samples for the network are determined through random function and preprocessed with scaling in interval （0.2, 0.8）. The neutral units in the hidden layer is decided by the trial- and-error method and an a model of artificial neural network （ANN） with a structure of 7 ： 8 ： 1 are established for the assessment of environment quality of urban soils. BPANN model is simulated through programming in Matlab 6. 0. It is found that the BPANN model is reliable for assessing accurately and objectively the environment quality of the urban soils. With Changchun as a case study, it is concluded that the environment quality of urban topsoil is generally good and about 81 % of the area reached the first level of national environmental quality standard for soils. It should be mentioned that the heavy metals pollution in local area is serious and should not be neglected, and some effective control measures of reducing heavy metal pollutants discharges should be put forward to ensure the sustainable use of urban soil resources.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2010年第2期98-103,109,共7页
Journal of Chongqing University
基金
中国地质调查局资助项目(基[2005]011-08)
重庆大学高层次人才科研启动基金资助项目(0903005104779)
关键词
人工神经网络
改进BP算法
环境质量评价
土壤
artificial neural network （ANN）
improved BP algorithm
environmental quality assessment
soil
