摘要
采用资料完整性、开采潜力、回灌量、平均水压下降速率、地面沉降速率、水温、水质、地热井布局8项指标构建天津地热可持续开发能力评价指标体系;运用层次分析法确定了各项指标的权重,建立起评价因素集和评语集,给出了归一化数值;建立了天津地热可持续开发能力的BP神经网络模型,以层次分析法得出的结果作为样本,对BP网络进行了训练和测试,实例评价结果表明了AHP和BP神经网络方法的可行性,为地热资源的可持续开发能力评价提供了一种新的评价方法。
Eight indicators such as the integrality of the data, exploration potential, the quantity of the irrigation, the descended speed of the average water - pressure, the speed of the land subsidence, the temperature of the water, water quality, the distribution of the Geothermal wells were selected to construct the evaluation index system of the sustainable development ability of geothermal resources in Tianjin. The analytic hierarchy process （AHP） was selected to determine the index weight on every level, the sets of evaluation factors and comments were established, the normalization data of eight indicators were given too. BP neural network model on sustainable development ability of geothermal resources in Tianjin was established, BP network was trained and tested by the sample that was attained by AHP. The example show that the feasibility of AHP and BP neural network evaluation method, and proves a new method for the sustainable development ability assessment of geothermal resotlrce.
出处
《地下水》
2008年第6期46-48,68,共4页
Ground water
基金
河南省重点科技攻关项目(0323030200)
河南理工大学博士基金资助
关键词
层次分析法
BP神经网络
地热
the analytic hierarchy process
back propagation neural network
geothermal energy
