基于 GRNN 网络的苏州市水资源承载能力评价

摘要

基于最严格的水资源管理制度和水资源承载能力的内涵，重新确定水资源承载能力评价的指标体系，构建广义回归神经网络(GRNN)水资源承载能力评价模型，应用于苏州市水资源承载能力评价，并将评价结果与采用模糊综合评价的结果进行比较。结果表明：两种评价结果相符；结合用水总量控制、用水效率控制和限制纳污所建立的指标体系更加科学、更加符合经济社会的发展需求；苏州市水资源承载能力状况由2004年之前的较低水平逐渐恢复，这种变化与苏州市经济增长模式的转变和产业结构的调整密切相关。%Based on the strictest systems for water resources management and the meaning of water resources carrying capacity, an index system was established for evaluation of water resources carrying capacity .The generalized regression neural network (GRNN) was employed to build an evaluation model .This model was applied to the evaluation of the water resources carrying capacity of Suzhou City .The evaluation results were compared with those obtained with the fuzzy comprehensive evaluation model .The comparison shows that the results of the two models were consistent, and the index system that considers the total water consumption control , water utilization efficiency control, and water pollutant admission limitation was more scientific and adaptable to socio -economic development.The water resources carrying capacity of Suzhou City has gradually recovered since 2004, when it was at a low level.This was closely related to the industrial adjustment and economic growth mode transformation in Suzhou City.