Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model
Accurate energy consumption forecasting can provide reliable guidance for energy planners and policy makers, which can also recognize the economic and industrial development trends of a country. In this paper, a hybrid PSOCA-GRNN model was proposed for the annual energy consumption forecasting. The...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/217630 |
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| _version_ | 1832556943940517888 |
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| author | Huiru Zhao Sen Guo |
| author_facet | Huiru Zhao Sen Guo |
| author_sort | Huiru Zhao |
| collection | DOAJ |
| description | Accurate energy consumption forecasting can provide reliable guidance for energy planners and policy makers, which can also recognize the economic and industrial development trends of a country. In this paper, a hybrid PSOCA-GRNN model was proposed for the annual energy consumption forecasting. The generalized regression neural network (GRNN) model was employed to forecast the annual energy consumption due to its good ability of dealing with the nonlinear problems. Meanwhile, the spread parameter of GRNN model was automatically determined by PSOCA algorithm (the combination of particle swarm optimization algorithm and cultural algorithm). Taking China’s annual energy consumption as the empirical example, the effectiveness of this proposed PSOCA-GRNN model was proved. The calculation result shows that this proposed hybrid model outperforms the single GRNN model, GRNN model optimized by PSO (PSO-GRNN), discrete grey model (DGM (1, 1)), and ordinary least squares linear regression (OLS_LR) model. |
| format | Article |
| id | doaj-art-2f05c15e6ae94d1585d03b6cde8f6b7c |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-2f05c15e6ae94d1585d03b6cde8f6b7c2025-02-03T05:44:01ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/217630217630Annual Energy Consumption Forecasting Based on PSOCA-GRNN ModelHuiru Zhao0Sen Guo1School of Economics and Management, North China Electric Power University, Beijing 102206, ChinaSchool of Economics and Management, North China Electric Power University, Beijing 102206, ChinaAccurate energy consumption forecasting can provide reliable guidance for energy planners and policy makers, which can also recognize the economic and industrial development trends of a country. In this paper, a hybrid PSOCA-GRNN model was proposed for the annual energy consumption forecasting. The generalized regression neural network (GRNN) model was employed to forecast the annual energy consumption due to its good ability of dealing with the nonlinear problems. Meanwhile, the spread parameter of GRNN model was automatically determined by PSOCA algorithm (the combination of particle swarm optimization algorithm and cultural algorithm). Taking China’s annual energy consumption as the empirical example, the effectiveness of this proposed PSOCA-GRNN model was proved. The calculation result shows that this proposed hybrid model outperforms the single GRNN model, GRNN model optimized by PSO (PSO-GRNN), discrete grey model (DGM (1, 1)), and ordinary least squares linear regression (OLS_LR) model.http://dx.doi.org/10.1155/2014/217630 |
| spellingShingle | Huiru Zhao Sen Guo Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model Abstract and Applied Analysis |
| title | Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model |
| title_full | Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model |
| title_fullStr | Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model |
| title_full_unstemmed | Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model |
| title_short | Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model |
| title_sort | annual energy consumption forecasting based on psoca grnn model |
| url | http://dx.doi.org/10.1155/2014/217630 |
| work_keys_str_mv | AT huiruzhao annualenergyconsumptionforecastingbasedonpsocagrnnmodel AT senguo annualenergyconsumptionforecastingbasedonpsocagrnnmodel |