基于免疫原理的城市用水量预测模型
首发时间:2006-12-28
摘要:为提高城市用水量预测的精度,提出了一种新的基于免疫原理的城市用水量预测模型(UWBI),给出了模型中抗原、B细胞、记忆细胞的定义及UWBI的形式化描述,并进行了仿真实验,结果表明UWBI比基于BP神经网络的方法更有效。UWBI具有非线性,以及克隆选择、免疫网络和免疫记忆等生物免疫系统特征,为城市日用水量预测提供了一种较好的解决方案。
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Urban Water Demand Prediction Model Based on Immunity
Abstract:In order to improve the prediction precision of urban water demand, an urban water demand prediction model based on artificial immune, referred to as UWBI, is proposed. The definitions of antigen, antibody, memory cell, and model formalization are given. The emulation experiments results indicate that UWBI is more effective than BP neural network. UWBI possesses biological immune system properties such as clonal selection, immune network, and immune memory, which provide a preferable solution for urban water demand prediction.
Keywords: artificial immune system machine learning urban water demand prediction model
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