Temat: PSO - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: The influence of inertia weight on the Particle Swarm Optimization algorithm
Autorzy:: Cekus, D.
Skrobek, D.
Tematy:: particle swarm optimization (PSO)
PSO algorithm
inertia weight
trajectory
optymalizacja rojem cząstek
PSO
algorytm PSO
metoda PSO
algorytm optymalizacji rojem cząstek
trajektoria
współczynnik wagowy; Pokaż więcej
Wydawca:: Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Powiązania:: https://bibliotekanauki.pl/articles/122644.pdf Link otwiera się w nowym oknie
Opis:: The paper presents the use of the Particle Swarm Optimization (PSO) algorithm to find the shortest trajectory connecting two defined points while avoiding obstacles. The influence of the inertia weight and the number of population adopted in the first iteration of the PSO algorithm was examined for the length of the sought trajectory. Simulation results showed that the proposed method achieved significant improvement compared to the linearly decreasing method technique that is widely used in literature.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 2.

Tytuł:: Storage allocation in automated container terminals: the upper level
Autorzy:: Xia, M.
Zhao, N.
Mi, W.
Tematy:: storage allocation
automated container terminal
upper level model
PSO algorithm; Pokaż więcej
Wydawca:: Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Powiązania:: https://bibliotekanauki.pl/articles/258912.pdf Link otwiera się w nowym oknie
Opis:: Nowadays automation is a trend of container terminals all over the world. Although not applied in current automated container terminals, storage allocation is indispensable in conventional container terminals, and promising for automated container terminals in future. This paper seeks into the storage allocation problem in automated container terminals and proposed a two level structure for the problem. A mixed integer programming model is built for the upper level, and a modified Particle Swarm Optimization (PSO) algorithm is applied to solve the model. The applicable conditions of the model is investigated by numerical experiments, so as the performance of the algorithm in different problem scales. It is left to future research the lower level of the problem and the potential benefit of storage allocation to automated container terminals.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 3.

Tytuł:: Particle Swarm Optimization Algorithm for Leakage Power Reduction in VLSI Circuits
Autorzy:: Leela Rani, V.
Madhavi Latha, M.
Tematy:: leakage power
PSO algorithm
genetic algorithm
minimum leakage vector
Verilog-HDL implementation; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/225990.pdf Link otwiera się w nowym oknie
Opis:: Leakage power is the dominant source of power dissipation in nanometer technology. As per the International Technology Roadmap for Semiconductors (ITRS) static power dominates dynamic power with the advancement in technology. One of the well-known techniques used for leakage reduction is Input Vector Control (IVC). Due to stacking effect in IVC, it gives less leakage for the Minimum Leakage Vector (MLV) applied at inputs of test circuit. This paper introduces Particle Swarm Optimization (PSO) algorithm to the field of VLSI to find minimum leakage vector. Another optimization algorithm called Genetic algorithm (GA) is also implemented to search MLV and compared with PSO in terms of number of iterations. The proposed approach is validated by simulating few test circuits. Both GA and PSO algorithms are implemented in Verilog HDL and the simulations are carried out using Xilinx 9.2i. From the simulation results it is found that PSO based approach is best in finding MLV compared to Genetic based implementation as PSO technique uses less runtime compared to GA. To the best of the author’s knowledge PSO algorithm is used in IVC technique to optimize power for the first time and it is quite successful in searching MLV.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 4.

Tytuł:: Surface-to-air missile path planning using genetic and PSO algorithms
Autorzy:: Zandavi, S. M.
Tematy:: path planning
genetic algorithm
PSO algorithm
surface-to-air missile
3DOF simulation; Pokaż więcej
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Powiązania:: https://bibliotekanauki.pl/articles/280277.pdf Link otwiera się w nowym oknie
Opis:: Optimization algorithms use various mathematical and logical methods to find optimal points. Given the complexity of models and design levels, this paper proposes a heuristic optimization model for surface-to-air missile path planning in order to achieve the maximum range and optimal height based on 3DOF simulation. The proposed optimization model involves design variables based on the pitch programming and initial pitch angle (boost angle). In this optimization model, we used genetic and particle swarm optimization (PSO) algorithms. Simulation results indicated that the genetic algorithm was closer to reality but took longer computation time. PSO algorithm offered acceptable results and shorter computation time, so it was found to be more efficient in the surface-to-air missile path planning.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 5.

Tytuł:: Optimal allocation of reliability improvement target based on multiple correlation failures and risk uncertainty
Autorzy:: Jia, Shuoguo
Yan, Changfeng
Kang, Jianxiong
Xie, Heping
Wei, Yongqiao
Tematy:: multi-objective optimal allocation
reliability improvement
correlation failure
risk uncertainty
probability measure
cooperation game theory
PSO algorithm; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Powiązania:: https://bibliotekanauki.pl/articles/24200787.pdf Link otwiera się w nowym oknie
Opis:: Optimal allocation of the reliability improvement target is essential for the system optimization design. In order to solve the problems that the optimization model is with loss of generality and the validity of the optimal solution is weakened, an optimal allocation method is proposed by considering multiple correlation failures and risk uncertainty in this paper. Two new concepts are presented, such as independent failure results in basic risk, and correlation failure leads to disturbance risk. A risk assessment machinery of “actual risk = basic risk + disturbance risk” is proposed. The action mechanisms of the three correlation failures are studied based on the cooperation game theory, and the generalized risk models are given under probability measure. Considering the improvement cost, the expectation and the variance of the reduction of system risk, a multi-objective optimal allocation model is developed, which is solved by using the PSO algorithm. Finally, the proposed optimal allocation is implemented at the 2-stage NGW planetary reducer, and the results show that it is more efficient and feasible for engineering practice.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Skocz do pozycji: 6.

Tytuł:: Novel Speed Sensorless DTC Design for a Five-Phase Induction Motor with an Intelligent Fractional Order Controller Based-MRAS Estimator
Autorzy:: Guedida, Sifelislam
Tabbache, Bekheira
Benzaoui, Khaled Mohammed Said
Nounou, Kamal
Nesri, Mokhtar
Tematy:: sensorless speed
PSO algorithm
particle swarm optimization algorithm
model reference adaptive system
direct torque control
fractional-order proportional-integral controller; Pokaż więcej
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:: https://bibliotekanauki.pl/articles/58970776.pdf Link otwiera się w nowym oknie
Opis:: This paper presents a fractional-order adaptive mechanism-based model reference adaptive system (MRAS) configuration for speed estimation of sensorless direct torque control (DTC) of a five-phase induction motor. In effect, the fractional-order proportional-integral (FOPI) controller parameters are obtained by the particle swarm optimisation (PSO) algorithm to enhance the MRAS observer response. Thus, the developed algorithm in the speed loop control of the DTC strategy to increase its robustness against disturbances. Moreover, a comparative study has been done of the proposed MRAS-PSO/FOPI speed estimator with the conventional MRAS-proportional-integral (PI) and the PSO-based MRAS-PI. Simulation results have carried out of the different controllers used in the adaptation mechanism of the MRAS estimator, to show the performance and robustness of the proposed MRAS-PSO/FOPI algorithm in use.
Dostawca treści:: Biblioteka Nauki

Artykuł

na półce

Informacja

Wyszukujesz frazę "PSO" wg kryterium: Temat