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A new algorithm based on artificial bee colony algorithm for energy demand forecasting in Turkey

机译:一种基于人工蜂菌落算法的土耳其能源需求预测算法

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In this study, an energy demand forecasting algorithm based on the Artificial Bee Colony with Variable Search Strategies (ABCVSS) method was proposed in order to determine Turkey's long-term energy demand. Linear and quadratic equations were used for energy demand forecasting and the coefficients of the equations were determined by means of the ABCVSS method. With the ABCVSS method, an attempt was made to enhance the local and global searching capacity of the ABC algorithm by using five different search strategies. GDP, population, imports and exports data of the period from 1979 to 2005 were chosen as the input parameters for the proposed method. Long-term energy demand was predicted through one scenario and the obtained performance from the proposed method was compared to those obtained from PSO, ACO and HAP algorithms in the literature. It was determined that the proposed method is statistically more successful than the other methods.
机译:在本研究中,提出了一种基于人造蜂殖民地的能量需求预测算法,具有可变搜索策略(ABCVSS)方法,以确定土耳其的长期能源需求。线性和二次方程被用于能量需求预测,并且通过ABCVSS方法确定方程的系数。使用ABCVSS方法,尝试通过使用五种不同的搜索策略来增强ABC算法的本地和全局搜索容量。选择了1979年至2005年期间的GDP,人口,进出口数据作为所提出的方法的输入参数。通过一种情况预测长期能量需求,并将所得方法从文献中的PSO,ACO和HAP算法中获得的那些。确定所提出的方法比其他方法更成功。

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