simulation with full‐wave algorithm should be combined with numerical optimization for variable structure dimensions of the antenna .In this paper ,with MoM diven by PSO ,the conceptual design of an antenna with special form is optimized .After thousands of iterations ,the design with an optimum...
The performance of the hybrid algorithm is evaluated using the number of alive nodes, number of dead nodes, throughput and residual energy. The proposed hybrid HSA–PSO algorithm shows an improvement in residual energy and throughput by 83.89% and 29.00%, respectively, than the PSO algorithm....
PSO algorithm is a swarm-based search method that operates on a D-dimensional solution space. Each potential solution is represented by a particle that has a position and a velocity and can store the best position of itself and the swarm. At each iteration, the particles update their velocitie...
In view of the shortcomings of existing artificial neural network (ANN) and support vector regression (SVR) in the application of three-dimensional displacement back analysis, Gaussian process regression (GPR) algorithm is introduced to make up for the s
Since the slotted patch resonator cannot be characterized by the closed-form transmission line theory, the particle swarm optimization (PSO) algorithm is constructed and integrated with a full-wave solver to determine the variable parameters of the proposed structure. Finally, a prototype dual-band ...
Full size table The PSO is implemented to find the optimal total costs \(\widetilde{IC_{1}}\) and \(\widetilde{IC_{2}}\) incorporating the generalized neutrosophic cost parameters, the parameters of the PSO algorithm are \(w = 1\), \(\textrm{wdic} = 0.99\), \(c_{1} = 2\)...
Premature convergence detection and correction in the form of particle craziness. Running multiple BPSOs in parallel on different threads (unavailable in WebGL). Takes into consideration realtime market prices. Snapshot system allows visualizing the BPSO algorithm's functioning at each iteration. ...
61. This balance ensures that the algorithm not only explores the solution space thoroughly but also exploits the promising areas identified during the exploration. This trait is particularly valuable when dealing with multifaceted optimization scenarios, where the landscape can be rugged and intricate. ...
Full size image In order to apply the PSO algorithm, several error-related functions are used. The use of these functions is necessary to complete this algorithm to determine the parameter values of the proposed controller. So, to complete this work, we chose to use integral of the absolute ...
The S-DATE algorithm is the pseudo-code for the proposed approach. The proposed approach needs input data in numerical form, which will pass through the Min-Max scaler. Min-Max scalar will do normalization of data between {0,1} range by preserving the original distribution of the data but ...