An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony
This paper presents an improved building load forecasting method using a combined Least Square Support Vector Machine and modified Artificial Bee Colony. The main contribution of the proposed method is the improvement in the exploitation capability of the standard Artificial Bee Colony, in which a d...
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Penerbit UTM Press
2017
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my.utm.803072019-04-25T01:31:55Z http://eprints.utm.my/id/eprint/80307/ An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony Mat Daut, Mohammad Azhar Hassan, Mohammad Yusri Abdullah, Hayati Abdul Rahman, Hasimah Abdullah, Md. Pauzi Hussin, Faridah TK Electrical engineering. Electronics Nuclear engineering This paper presents an improved building load forecasting method using a combined Least Square Support Vector Machine and modified Artificial Bee Colony. The main contribution of the proposed method is the improvement in the exploitation capability of the standard Artificial Bee Colony, in which a different probability selection has been introduced. This was achieved by changing the standard probability selection with the clonal selection algorithm. The results from two other methods were compared with the results from the proposed method to validate the performance of the proposed forecasting method. The accuracy of the proposed method was evaluated using the Mean Absolute Error, Mean Absolute Percentage Error and Root Mean Square Error. It was found that the proposed method had improved the accuracy by more than 50 % compared to the other methods. The results of the study showed that the proposed method has great potential to be used as an accurate forecasting method. Penerbit UTM Press 2017 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/80307/1/MohammadYusriHassan2017_AnImprovedBuildingLoadForecasting.pdf Mat Daut, Mohammad Azhar and Hassan, Mohammad Yusri and Abdullah, Hayati and Abdul Rahman, Hasimah and Abdullah, Md. Pauzi and Hussin, Faridah (2017) An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony. Elektrika, 16 (1). pp. 1-5. ISSN 0128-4428 https://elektrika.utm.my/index.php/ELEKTRIKA_Journal/article/view/22 |
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TK Electrical engineering. Electronics Nuclear engineering |
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TK Electrical engineering. Electronics Nuclear engineering Mat Daut, Mohammad Azhar Hassan, Mohammad Yusri Abdullah, Hayati Abdul Rahman, Hasimah Abdullah, Md. Pauzi Hussin, Faridah An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| description |
This paper presents an improved building load forecasting method using a combined Least Square Support Vector Machine and modified Artificial Bee Colony. The main contribution of the proposed method is the improvement in the exploitation capability of the standard Artificial Bee Colony, in which a different probability selection has been introduced. This was achieved by changing the standard probability selection with the clonal selection algorithm. The results from two other methods were compared with the results from the proposed method to validate the performance of the proposed forecasting method. The accuracy of the proposed method was evaluated using the Mean Absolute Error, Mean Absolute Percentage Error and Root Mean Square Error. It was found that the proposed method had improved the accuracy by more than 50 % compared to the other methods. The results of the study showed that the proposed method has great potential to be used as an accurate forecasting method. |
| format |
Article |
| author |
Mat Daut, Mohammad Azhar Hassan, Mohammad Yusri Abdullah, Hayati Abdul Rahman, Hasimah Abdullah, Md. Pauzi Hussin, Faridah |
| author_facet |
Mat Daut, Mohammad Azhar Hassan, Mohammad Yusri Abdullah, Hayati Abdul Rahman, Hasimah Abdullah, Md. Pauzi Hussin, Faridah |
| author_sort |
Mat Daut, Mohammad Azhar |
| title |
An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| title_short |
An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| title_full |
An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| title_fullStr |
An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| title_full_unstemmed |
An improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| title_sort |
improved building load forecasting method using a combined least square support vector machine and modified artificial bee colony |
| publisher |
Penerbit UTM Press |
| publishDate |
2017 |
| url |
http://eprints.utm.my/id/eprint/80307/1/MohammadYusriHassan2017_AnImprovedBuildingLoadForecasting.pdf http://eprints.utm.my/id/eprint/80307/ https://elektrika.utm.my/index.php/ELEKTRIKA_Journal/article/view/22 |
| _version_ |
1643658374736248832 |
| score |
13.251813 |