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徐州市生活垃圾处理现状及资源化研究
引用本文:王岩,裴宗平,孙晓虎.徐州市生活垃圾处理现状及资源化研究[J].环境科学与管理,2007,32(2):14-17.
作者姓名:王岩  裴宗平  孙晓虎
作者单位:中国矿业大学,环境与测绘学院,江苏,徐州,221008
摘    要:介绍了徐州市生活垃圾的处理现状;对生活垃圾中常见成分比例和垃圾热值进行了测定.应用MATLAB7.0软件,以影响城市生活垃圾产生量的主要因素(人口数量、人均可支配收入、燃气化率、源头减量及资源化利用率)作为输入,来建立预测城市垃圾产量的BP神经网络模型,发现当隐含层的节点数为8时,网络收敛速度较快,预测偏差最小,于是确定预测模型的结构为4-8-1,应用该模型对徐州市生活垃圾产量进行了预测.最后,以所得数据为基础,并结合当地实际情况,提出了徐州市垃圾综合处置和资源化的若干措施.

关 键 词:生活垃圾  热值  BP神经网络  资源化  徐州市  生活垃圾  处理现状  资源化研究  Research  Reutilization  Status  Disposal  处置  综合  情况  结合  数据  预测模型  结构  最小  偏差  收敛速度  网络模型  节点数
文章编号:1673-1212(2007)02-0014-04
修稿时间:2006-09-05

Garbage Disposal Status of Xuzhou and Its Reutilization Research
Wang Yan,Pei Zongping,Sun Xiaohu.Garbage Disposal Status of Xuzhou and Its Reutilization Research[J].Environmental Science and Management,2007,32(2):14-17.
Authors:Wang Yan  Pei Zongping  Sun Xiaohu
Abstract:Garbage Disposal Status of XuZhou is presented in this study,the common Composition and calorific value of MSW were measured.BP neural network based on MATLAB 7.0 is established to predict the production of MSW,with the major factors that influencing the quantity of MSW(population,per capita disposable income,gas using rate,Source reduction and resource utilization rate.) serving as the input.It has been found that the convergence speed of the network is relatively high and prediction error is minimum when hidden nodes total 8 is used.Thus the structure of BP network for predicting production of MSW is made certain 4-8-1.It is applied to the prediction on production of MSW in XuZhou.Finally,base on the data obtained and taking the local conditions into account,comprehensive treatment and reutilization of MSW is put forward.
Keywords:MSW  calorific value  BP neural network  resource recovery
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