Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting
Hybridizing chaotic evolutionary algorithms with support vector regression (SVR) to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS) algorithm. This paper investigates pot...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-10-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1996-1073/9/11/873 |
| _version_ | 1798005820377530368 |
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| author | Cheng-Wen Lee Bing-Yi Lin |
| author_facet | Cheng-Wen Lee Bing-Yi Lin |
| author_sort | Cheng-Wen Lee |
| collection | DOAJ |
| description | Hybridizing chaotic evolutionary algorithms with support vector regression (SVR) to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS) algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory) to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS) to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives. |
| first_indexed | 2024-04-11T12:45:03Z |
| format | Article |
| id | doaj.art-53d34f153d3844e7afca2b6c89e8bc76 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T12:45:03Z |
| publishDate | 2016-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-53d34f153d3844e7afca2b6c89e8bc762022-12-22T04:23:23ZengMDPI AGEnergies1996-10732016-10-0191187310.3390/en9110873en9110873Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load ForecastingCheng-Wen Lee0Bing-Yi Lin1Department of International Business, Chung Yuan Christian University/200 Chung Pei Rd., Chungli District, Taoyuan City 32023, TaiwanPh.D. Program in Business, College of Business, Chung Yuan Christian University/200 Chung Pei Rd., Chungli District, Taoyuan City 32023, TaiwanHybridizing chaotic evolutionary algorithms with support vector regression (SVR) to improve forecasting accuracy is a hot topic in electricity load forecasting. Trapping at local optima and premature convergence are critical shortcomings of the tabu search (TS) algorithm. This paper investigates potential improvements of the TS algorithm by applying quantum computing mechanics to enhance the search information sharing mechanism (tabu memory) to improve the forecasting accuracy. This article presents an SVR-based load forecasting model that integrates quantum behaviors and the TS algorithm with the support vector regression model (namely SVRQTS) to obtain a more satisfactory forecasting accuracy. Numerical examples demonstrate that the proposed model outperforms the alternatives.http://www.mdpi.com/1996-1073/9/11/873support vector regression (SVR)quantum tabu search (QTS) algorithmquantum computing mechanicselectric load forecasting |
| spellingShingle | Cheng-Wen Lee Bing-Yi Lin Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting Energies support vector regression (SVR) quantum tabu search (QTS) algorithm quantum computing mechanics electric load forecasting |
| title | Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting |
| title_full | Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting |
| title_fullStr | Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting |
| title_full_unstemmed | Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting |
| title_short | Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting |
| title_sort | application of hybrid quantum tabu search with support vector regression svr for load forecasting |
| topic | support vector regression (SVR) quantum tabu search (QTS) algorithm quantum computing mechanics electric load forecasting |
| url | http://www.mdpi.com/1996-1073/9/11/873 |
| work_keys_str_mv | AT chengwenlee applicationofhybridquantumtabusearchwithsupportvectorregressionsvrforloadforecasting AT bingyilin applicationofhybridquantumtabusearchwithsupportvectorregressionsvrforloadforecasting |