中文摘要：

建立了基于遗传学习分类器系统（LCS）的水库供水规则分类系统，通过信任分配（桶链算法，BBA）与规则发现（遗传算法，GA）机制进行学习，提取水库供水调度规则．实例研究得到学习样本识别率接近95％，检验样本识别率为85％．进一步从调度规则的合理性、学习样本对规则集的影响以及该分类系统与人工神经网络对规则提取结果的比较这3个方面分析了系统提取规则的性能与行为．研究表明，利用该分类系统提取水库供水调度规则是可行且有效的．

英文摘要：

An operating rule classification system based on learning classifier system （LCS）, which learns through credit assignment （bucket brigade algorithm, BBA） and rule discovery（genetic algo- rithm, GA）, is established to extract water-supply reservoir operating rules. The proposed system acquires the identification rate 95 % for training samples and 85 % for testing samples in a case study, and further discussions are made about the impacts on the performances or behaviors of the system from three aspects of obtained rules, training or testing samples and the comparisons between the system and the artificial neural network for extracting operating rules. The results indicate the system is feasible and effective to obtain the reservoir supply operating rules.