In order to realize fast infrared image segmentation, an improved general particle swarm optimization algorithm is proposed. The algorithm is based on general particle swarm optimization, and it makes use of adaptive balance searching strategy. When the evolution stops, simulated annealing algorithm is ...
multi-objective optimizationprincipal component analysisdeep belief networkwing designmulti-objective particle swarm optimization algorithmFor the purpose of reducing the number of the design variables of the wing, the PCA (principal component analysis) technique is employed to improve the CST ...
Li, “On convergence and parameter selection of an improved particle swarm optimization,” International Journal of Control, Automation, and Systems, vol. 6, no. 4, pp. 559–570, Aug. 2008. Google Scholar J. H. Friedman, “Multivariate adaptive regression splines,” Annals of Statistics, ...
A general approach to approximate solutions of nonlinear differential equations using particle swarm optimization 来自 Semantic Scholar 喜欢 0 阅读量: 64 作者: Babaei,M.摘要: A general algorithm is presented to approximately solve a great variety of linear and nonlinear ordinary differential equations (...
On this basis, together with the KM algorithm, α-plane representation and interpolation conclusions of interval type-2 fuzzy systems, three types of interpolation functions of general type-2 fuzzy systems are obtained. In the meantime, all of the interpolation functions have been proved as ...
6.Particle Swarm Optimization Algorithm for Traveling Salesman Problem Program Design粒子群算法求解旅行商问题程序设计 7.The use of matrices systematizes the calculation procedure and adapts the problem to a computer solution.应用矩阵可以使计算程序系统化,并可使问题适于用计算机求解。
An algorithm based on particle swarm optimization (PSO) is proposed for multiple base stations under general power-consumption constraints. The proposed approach can search for nearly optimal BS locations in heterogeneous sensor networks, where application nodes may own different data transmission rates, ...
To overcome this limitation, a novel general-purpose repowering model via bioinspired optimization is discussed in this text. The model proposes design of a genetic algorithm that considers inflow wind speed, wind direction angle, height of hub, surface roughness, horizontal-axis wind turbine rotor ...
Once the algorithm has been trained, the ML system creates a predictive function that is able to estimate the right label from a random input. A variety of algorithms can be used for supervised learning tasks, including decision trees, decision forests, logistic regression, support vector machines...
All the parameters of the RBFNN are derived and optimized via particle swarm optimization (PSO) algorithm and genetic algorithm (GA). In order to increase the robustness of the controller, in the second method, an integral term is added to the RBF neural network gives an integral RBFNN (I...