基于BP神经网络的武汉市生活垃圾清运量预测研究  

Prediction Study on Municipal Solid Waste Yields Based on BP Neural Network in Wuhan

作　　者：夏晶[1] 张旺[1] 

机构地区：[1]湖北工业大学经济与管理学院,湖北武汉430068

出　　处：《湖北工业大学学报》2016年第6期20-22,63,共4页Journal of Hubei University of Technology

摘　　要：以武汉市中心城区垃圾清运量的历年统计数据为例,用熵权法确定其主要影响因素,建立基于BP神经网络的武汉市生活垃圾清运量预测模型,并将实际值与预测值进行比较。结果表明,该模型具有较好的预测性和适用性。用该模型对武汉市未来几年生活垃圾清运量进行了预测,研究发现GDP、居民人均纯收入、第三产业产值、固定资产投资和社会消费总额等5个因素对武汉市生活垃圾清运量影响较大。This paper analyzed the factors that influence the municipal solid waste yields. Taking Wuhan as an example and according to historical statistics of municipal solid waste yields in Wuban, this paper used entropy weight method to determine its main influencing factors and established the BP neural network forecasting model of Wuhan solid waste yields. After comparing the actual value with predicted value, the results show that this model has good predictability and applicability. This paper used the model to predict municipal solid waste yields in Wuhan over the next few years, in order to provide a decision-making reference for municipal solid waste management and environmental planning in Wuhan.

关 键 词：生活垃圾清运量 熵权法 BP神经网络 

分 类 号：X705[环境科学与工程—环境工程]