In this study, a novel artificial neural network (ANN)-Jaya algorithm hybrid artificial intelligence model was developed to estimate Turkey’s future energy use. The model estimates energy consumption based on gross domestic product (GDP), population, import data, and export data. The Jaya algorithm used in our model’s development is a simple and powerful metaheuristic algorithm that overcomes the complexity of difficult optimization problems; it provides optimal results quickly owing to its ease of applicability and simple structure. Our ANN-Jaya model’s performance was compared with the performance of artificial bee colony (ABC) and teaching learning based optimization (TLBO) algorithm-trained ANN models. According to the root mean square error (RMSE) values obtained for the test set, the proposed ANN-Jaya model performed 36.7% and 46.2% better than the ANN-ABC and ANN-TLBO models, respectively. After defining the optimal configurations, three energy consumption prediction scenarios were developed and compared with previously published forecasts.

在这项研究中，开发了一种新型的人工神经网络（ANN）-Jaya算法混合人工智能模型来估算土耳其的未来能源使用。该模型根据国内生产总值（GDP），人口，进口数据和出口数据估算能源消耗。在模型开发中使用的Jaya算法是一种简单而强大的元启发式算法，它克服了困难的优化问题的复杂性。由于它的易用性和简单的结构，它可以快速提供最佳结果。将我们的ANN-Jaya模型的性能与人工蜂群（ABC）和基于教学学习的优化（TLBO）算法训练的ANN模型的性能进行了比较。根据从测试集获得的均方根误差（RMSE）值，所提出的ANN-Jaya模型的执行率为36.7％和46。比ANN-ABC和ANN-TLBO模型分别好2％。在定义最佳配置后，开发了三种能耗预测方案并将其与以前发布的预测进行比较。