1.PSO-BP粒子群优化神经网络+NSGAII多目标优化算法,工艺参数优化、工程设计优化!(Matlab完整源码和数据) 在构建PSO-BP神经网络模型时,首先需要设计神经网络的结构,包括输入层、隐藏层和输出层的节点数。输入层节点数通常由输入数据的维度决定,输出层节点数由待解决的问题类型决定。隐藏层节点数的选择则较为复杂,需要...
To address these issues, this research introduces an optimization strategy that utilizes advanced algorithms such as Particle Swarm Optimization (PSO) and traditional non-dominated sorting genetic algorithm-II (NSGA-II). By leveraging these algorithms, this study aims to optimize the performance of ...
A python library for the following Multiobjective Optimization Algorithms or Many Objectives Optimization Algorithms: C-NSGA II; CTAEA; GrEA; HypE; IBEA-FC; IBEA-HV; MOEA/D; NAEMO; NSGA II; NSGA III; OMOPSO; PAES; RVEA; SMPSO; SMS-EMOA; SPEA2; U-NSGA II
1.PSO-BP粒子群优化神经网络+NSGAII多目标优化算法,工艺参数优化、工程设计优化!(Matlab完整源码和数据) 在构建PSO-BP神经网络模型时,首先需要设计神经网络的结构,包括输入层、隐藏层和输出层的节点数。输入层节点数通常由输入数据的维度决定,输出层节点数由待解决的问题类型决定。隐藏层节点数的选择则较为复杂,需要...
通过Matlab仿真对比PSO,NSGA-Ⅱ和NSGA-Ⅱ-PSO算法的适应度收敛曲线,验证所提算法具有收敛速度快,全局和局部搜索能力强的优点,较单一的PSO算法和NSGA-Ⅱ算法具有更优的特点;结合经典微网系统进行算例仿真,通过对单目标与多目标的分析,结果表明该算法能有效降低经济成本和使环境效益达到最优;并且进一步验证所提算法的...
本发明公开了基于PSOBP神经网络和NSGAII的激光切割加工建模及参数优化选择方法,通过已有的激光切割加工数据,利用经过PSOBP优化后的BP神经网络建立神经网络模型,并通过NSGAII多目标优化算法优化选择激光加工参数.将构建的建模样本集进行归一化处理,获得归一化样本集;根据归一化样本集,利用粒子群优化算法(PSO)优化BP神经网络...
Terrab, Hard turning behavior improvement using NSGA-II and PSO-NN hybrid model, Int. J. Adv. Manuf. Technol. (2016). http://dx.doi.org/ 10.1007/s00170-016-8479-6.Bouacha K, Terrab A (2016) Hard turning behavior improvement using NSGA-II and PSO-NN hybrid model. Int J Adv ...
Although, the GAs and PSO are applied for moment resisting steel structures, the concepts can be extended for other structural systems. It is concluded that the use of NSGA-II and PSO reduce the structural weight and they are a very useful tools to improve the structural performance of the ...
Proxy modelNSGA-IISingle-objective well control problems have been studied for many years as one of the most typical optimization problems by researchers worldwide. However, single-objective optimization often could not meet the needs in practical application processes leading to multi-objective ...
Furthermore, the NSGA-II exhibits better performance when compared to the PSO-NN methodology. However, the PSO-NN has been shown to outperform the NSGA-II methodology in computational time. 展开 关键词: ANN PSO NSGA-II Hard turning Tool wear Surface roughness ...