机译:基于岩石学,近距离和最终分析的神经网络和粒子群优化技术预测煤的可磨性
Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran;
Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology.Shahrood, Iran;
Department of Mining Engineering, Research and Science Campus, Islamic Azad University,Poonak, Hesarak Tehran, Iran;
Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran;
Center for Applied Energy Research, University of Kentucky, 2540 Research Park Drive, Lexington, KY 40511, USA;
hardgrove grindability index; particle swarm optimization; neural networks; coal petrography;
机译:基于岩石学的煤可磨性预测,使用多元回归和人工神经网络模型进行近似和最终分析
机译:基于混合前馈神经网络,粒子群优化和多分辨率技术的利率次日变化预测
机译:基于耦合遗传算法和粒子群优化技术的神经网络拓扑优化(C-GA-PSO-Nn)
机译:基于多群混沌粒子优化和优化灰色神经网络的网络安全态势预测模型
机译:基于粒子群优化的粒子滤波技术在多基地超宽带雷达传感器网络中的目标跟踪
机译:基于TS模糊神经网络和粒子群算法的瓦斯利用率预测。
机译:基于粒子群优化的人工神经网络(IPS-ANN)分类器进行了改进的预测策略,用于混合P2P网络的恶意节点检测