基于模糊时间序列的用水量预测&以印尼唐格朗区私营企业为例

Diah Septiyana
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引用次数: 1

摘要

由于人口和出生率的增加,唐格朗县的用水量逐年增加,平均每年增加3%。因此,水需求预测对于满足客户或社区需求至关重要。私营水务公司需要使用一种新的方法来预测未来的月度用水量值,并在使用可见性图预测时间序列时提高准确性,以进行更准确的预测。在本研究中,我们旨在测量模糊时间序列预测用水量的趋势分析量与实际使用量的关系。模糊时间序列(FTS)是一种使用模糊逻辑的概念规划方法,能够提供对未来几个时期的时间序列数据分析的预测(估计)。对于输入集和FTS模型结构的不同配置,获得了平均绝对百分比误差(MAPE)。从结果来看,使用FTS Chen方法的平均值误差准确度仅为4.5%,且包含在低用水量类别中,实际用水量与预测用FTS Chen法显示出相关稳定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WATER CONSUMPTION PREDICTION USING FUZZY TIME SERIES - A CASE STUDY IN PRIVATE COMPANY OF TANGERANG DISTRICT INDONESIA
Consumption of water in the Tangerang Regency continuously increases from year to year due to the increasing population and birth rates an average increase of 3% every year. So, the water demand prediction to be important to meet customer or community needs. The private water utility company needs to use a new method for predicting future monthly water consumption values and improves accuracy when forecasting time series using a visibility graph and presents to make more accurate predictions. In this study, we aim to measure the trend analysis volume of water consumption prediction by Fuzzy Time Series versus actual usage volume.  Fuzzy Time Series (FTS) is a concept plan method that uses fuzzy logic that is able to provide predictions (estimates) of time series data analysis for the next several periods. Mean Absolute Percentage Error (MAPE) is obtained for different configurations of the input sets and of the FTS model structure. From the results of the average value error accuracy was only 4.5% using FTS Chen Method and included in the low category and water consumption actual versus prediction with the FTS Chen method shown related stable.
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