机译:预测用电量:回归分析,神经网络和最小二乘支持向量机的比较
Gazi University, Faculty of Engineering, Electrical & Electronics Engineering Department, 06750 Maltepe, Ankara, Turkey;
Gazi University, Faculty of Engineering, Electrical & Electronics Engineering Department, 06750 Maltepe, Ankara, Turkey;
Kirikkale University, Faculty of Engineering, Electrical & Electronics Engineering Department, 71450 Kirikkale, Turkey;
Gazi University, Faculty of Engineering, Electrical & Electronics Engineering Department, 06750 Maltepe, Ankara, Turkey;
Electricity consumption forecasting; Regression analysis; Artificial neural network; Least square support vector machines;
机译:用神经网络和支持向量回归预测用电量
机译:线性和非线性条件下每月流量预测的人工神经网络,广义回归神经网络,最小二乘支持向量回归和K最近邻回归的比较评估
机译:使用局部最小二乘,人工神经网络和支持向量回归技术的区域供热系统热量消耗预测
机译:使用最小二乘支持向量机预测葡萄牙电消耗
机译:最小二乘支持向量机在中期负荷预测中的应用。
机译:痴呆症预测中的数据挖掘方法:线性判别分析逻辑回归神经网络支持向量机分类树和随机森林的准确性敏感性和特异性的真实数据比较
机译:用神经网络和支持向量回归预测用电量