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Hourly weather forecast analysis.

Rasmidatta, Sothaya.

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Hourly weather forecast analysis.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Hourly weather forecast analysis./
作者:	Rasmidatta, Sothaya.
面頁冊數:	104 p.
附註:	Adviser: Wei-Jen Lee.
Contained By:	Masters Abstracts International44-06.
標題:	Atmospheric Sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1435968
ISBN:	9780542723186

Hourly weather forecast analysis.
Rasmidatta, Sothaya.

Hourly weather forecast analysis. - 104 p.

Adviser: Wei-Jen Lee.

Thesis (M.S.)--The University of Texas at Arlington, 2006.

Today, internet becomes one of the most important resources for useful information. However, since the authentic of the information is difficult to verify, one also has to take precaution when getting information from the internet. Utility companies need to forecast their load for unit commitment scheduling and system planning. The traditional approach for neural network forecasting relies on the temperature forecasting information from a single source. The customer loads are closely correlated with the temperature. Therefore, the accuracy of the load forecasting is affected by the temperature forecasting errors. The objective of this thesis is to reduce the temperature forecasting errors by using artificial neural network (ANN) to preprocessing the temperature forecasting information from various resources. In this thesis, temperature information from five (5) websites have been used for this process. Each website provides hourly forecast temperature of 15 days. A JAVA program is designed to extract the useful temperature information from each individual web site and record them into the database (MySQL). Depends upon the available data, an ANN is then used to forecast hour ahead and day ahead temperatures up to seven days. Through this preprocessing, better weather information is obtained to have more accurate load forecasting results.

ISBN: 9780542723186Subjects--Topical Terms:

1019179
Atmospheric Sciences.

Hourly weather forecast analysis.
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520 $a Today, internet becomes one of the most important resources for useful information. However, since the authentic of the information is difficult to verify, one also has to take precaution when getting information from the internet. Utility companies need to forecast their load for unit commitment scheduling and system planning. The traditional approach for neural network forecasting relies on the temperature forecasting information from a single source. The customer loads are closely correlated with the temperature. Therefore, the accuracy of the load forecasting is affected by the temperature forecasting errors. The objective of this thesis is to reduce the temperature forecasting errors by using artificial neural network (ANN) to preprocessing the temperature forecasting information from various resources. In this thesis, temperature information from five (5) websites have been used for this process. Each website provides hourly forecast temperature of 15 days. A JAVA program is designed to extract the useful temperature information from each individual web site and record them into the database (MySQL). Depends upon the available data, an ANN is then used to forecast hour ahead and day ahead temperatures up to seven days. Through this preprocessing, better weather information is obtained to have more accurate load forecasting results.
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