+d TNeioE(iDds2D1ehA/taeεwlrf−meorefi1nwc)eaPhtl/cahtuPeil1vta/taw2elu−doeuεa,locdwcf ohbPree1dr/i2e-f, { }/{ }Π = ∆P1/2/∆H pp P1/2(DPPH)/∆H pp(DPPH) , plwinehaeek-rw-etiodΔ-tph Pe1va/a2klwulieansse, -rcweaslipcduetchlatiotvef...
Domuta et al., 2012 [20] proposed a modified bi-objective Martines' Algorithm to find the optimal route in the intermodal transportation network with the time window and the objective is to minimize the travel time and cost. Lam and Gu, 2016 [7] formulated the port hinterland intermodal ...
3.2.2. Backtracking Search Algorithm (BSA) BSA is a new evolutionary algorithm based on populations [48]. In an iterative process, the objective function is reduced to the minimum possible value. BSA has five evolutionary mechanisms: initialization, selection-I, mutation, crossover, and selection...
A Least Squares Support Vector Machine Optimized by Cloud-Based Evolutionary Algorithm for Wind Power Generation Prediction. Energies 2016, 9, 585. [CrossRef] 12. Hu, Q.; Su, P.; Yu, D.; Liu, J. Pattern-based wind speed prediction based on generalized principal component analysis. IEEE ...
energies Article Optimization of Antenna Array Deployment for Partial Discharge Localization in Substations by Hybrid Particle Swarm Optimization and Genetic Algorithm Method Mingxiao Zhu 1,* ID , Jiacai Li 1, Dingge Chang 2, Guanjun Zhang 2 and Jiming Chen 1 1 College of Information and Control...
The parameters of the IHGA are set as follows: population size N = 200, number of evolutionary iterations G = 100 (according to the results of the previous algorithm, it will converge and find the optimal solution in about 50 iterations; thus, 100 iterations are used as the convergence ...
Finally, a conclusion and outlook are given in Section 4. Appl. Sci. 2022, 12, 10649 veloped with a numerical model (Section 2.1). The approach works by first eliminating low-stressed regions using a stress limit value. All the remaining regions were then grouped by a cluster algorithm ...