摘要
以供水调度为例对数据挖掘用于水库调度规则提取进行了研究.经分析主要选取了水库蓄水量、调度时段编号、需水量、径流量和水文年型5个特征属性构成数据集,通过数据挖掘从中发掘水库供水调度规则模式.采用径向基函数网络作为数据挖掘算法,将复杂的属性空间上的数据样本,映射为几种离散的供水调度模式,从而完成供水调度规则的模式划分.为了验证数据挖掘方法在调度规则提取上的效果,给出了调度图和调度函数方法用于供水调度的计算结果,三种方法的调度结果对比分析显示,数据挖掘方法在供水调度模式分类正确率和缺水指数两方面都是最好的,这反映出数据挖掘方法用于水库调度是合理有效的.
This paper explores the application of data mining in reservoir operating rules extraction with a case of water supply operation. Five characteristic attributes of reservoir storage, within-year operating period number, water demand, reservoir inflow and hydrologic year type are selected to compose databases from which reservoir operating rule patterns are identified using data mining. Radial basic function （RBF） network is utilized as date mining algorithm to perform mapping of data samples from complex attribute space to several discrete water supply operating patterns, hence completing pattern division of water supply operating rules. To validate the effectiveness of data mining using for operating rules extraction, we also provide operation results of traditional operating chart and operating functions for comparison. And the result comparison analysis shows that data mining is the best method for reservoir operating rules extraction in terms of both correct operating pattern division ratio and water deficiency index, which demonstrates that application of data mining in reservoir operation is practicable and effective.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2006年第8期129-135,共7页
Systems Engineering-Theory & Practice
基金
国家重点基础发展计划(‘973’计划)(2003CB415202-5)
关键词
调度规则
供水
模式划分
数据挖掘
径向基函数网络
reservoir operating rules
water supply
pattern division
data mining
RBF network
