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首页> 外文期刊>Journal of Solid Waste Technology and Management >ARTIFICIAL NEURAL NETWORKS FOR ASSESSING WASTE GENERATION FACTORS AND FORECASTING WASTE GENERATION: A CASE STUDY OF CHILE
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ARTIFICIAL NEURAL NETWORKS FOR ASSESSING WASTE GENERATION FACTORS AND FORECASTING WASTE GENERATION: A CASE STUDY OF CHILE

机译：人工神经网络评估废物产生因子并预测废物产生：以智利为例

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摘要

One of the bottlenecks in implementing waste management policies in Chile is the lack of information on factors correlating with waste generation. Recognising these factors is essential for implementing policies to reduce waste generation. From over 40 global variables indicating demographic, socio-economic and climatic conditions, Population, Percentage of Urban Population, Years of Education, Number of Libraries, and Number of Indigents were identified as the most important factors correlating with waste generation in Chile, all relating positively. Using these variables, communes were clustered into groups from which representative communes were selected for further data collection for forecasting waste generation at a communal level. Artificial Neural Networks were used for identifying factors, clustering communes and forecasting waste generation. The model is designed to represent most of the communes of a country. In this study, the best scenario represents 67.3% of the communes, based on the representativeness of each selected representative. However, due to lack of information, this rate decreased to 48.8%. Forecasted rates show that by 2010, representative communes will generate 100, 240 and 2,900 tonnes/month, with yearly variation rates of less than 1%. These predictions will be used to obtain estimates for each represented group and a significant portion of Chile.
机译：智利实施废物管理政策的瓶颈之一是缺乏与废物产生相关因素的信息。认识到这些因素对于实施减少废物产生的政策至关重要。智利的40多个全球变量表明人口，社会经济和气候状况，人口，城市人口百分比，受教育年限，图书馆数量和贫困人口数量是与废物产生相关的最重要因素，所有这些因素积极地。使用这些变量，将公社分为几类，从中选择代表公社进行进一步的数据收集，以预测公社一级的废物产生。人工神经网络用于识别因素，聚类公社和预测废物产生。该模型旨在代表一个国家的大多数公社。在本研究中，基于每个选定代表的代表性，最佳方案代表了67.3％的公社。但是，由于缺乏信息，该比率下降到48.8％。预测的速度表明，到2010年，有代表性的公社将产生100、240和2900吨/月，年变化率不到1％。这些预测将用于获取每个代表组和智利很大一部分的估计。

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