This work highlights the importance of fuzzy-wavelet denoise and fuzzy-wavelet compress in modeling the municipal residential water consumption estimation. To begin, fuzzy logic is used with different rules, membership criteria and fuzzy set. Based on accuracy of the developed model, optimum number of rules and best membership function were selected. To improve the accuracy of the single fuzzy model, wavelets technique (denoise and compress approach) was coupled with fuzzy logic and results were compared to single fuzzy technique. To map the input and output functions, the present research work includes Mamdani fuzzy inference approach based on various climatic input variables like rainfall, maximum temperature, minimum temperature and relative humidity. The models were trained based on climatic data to a certain period, and corresponding estimated models were tested for the same period. Result highlights that models with denoise and compress approach have better accuracy compared to single fuzzy model.

这项工作强调了模糊小波降噪和模糊小波压缩在建模市政居民用水估算中的重要性。首先，将模糊逻辑用于不同的规则，隶属标准和模糊集。根据开发模型的准确性，选择了最佳规则数和最佳隶属函数。为了提高单一模糊模型的准确性，将小波技术（降噪和压缩方法）与模糊逻辑相结合，并将结果与​​单一模糊技术进行了比较。为了映射输入和输出函数，当前的研究工作包括基于各种气候输入变量（如降雨量，最高温度，最低温度和相对湿度）的Mamdani模糊推理方法。这些模型是根据一定时期的气候数据进行训练的，并测试了相应的估计模型。结果表明，与单模糊模型相比，采用降噪和压缩方法的模型具有更好的精度。