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工業技術研究院

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技術名稱: 機器學習式用水需量預測技術

技術簡介

本技術主要說明應用SVR(Support Vector Regression)機器學習理論,並利用歷史用水量、溫度及濕度等資訊作為輸入特徵參數,以建構可預測下一日每小時用水需量之預測模型之設計及程式設計方法。

Abstract

This technology depicts the design procedure and software programming guide for designing the machine learning based hourly water demand SVR(Support Vector Regression) forecasting models which utilizes the historical water demand value, temperature value and humidity values as the learning patterns for predicting next day’s hourly load demand.

技術規格

下一日每小時用水量之平均預測誤差率可低於5%

Technical Specification

MAPE can be less than 5% for predicting next day’s hourly water demand

技術特色

可利用歷史用水量、溫度及濕度等資訊作為輸入特徵參數之SVR用水需量預測模型

應用範圍

供水廠之供水量預測,DMA之出水量預測

接受技術者具備基礎建議(設備)

機器學習理論,以及C#程式語言設計能力

接受技術者具備基礎建議(專業)

none

技術分類 02 D民生節能研究

聯絡資訊

聯絡人:林政廷 智慧節能系統技術組

電話:+886-3-5915404 或 Email:tim_lin@itri.org.tw

客服專線:+886-800-45-8899

傳真:+886-3-5820050

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