Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Urban congestion in major cities of Malaysia is getting severe over decades with increasing active vehicles and travelling time on the road. Part of Intelligent Transportation Systems development involves advanced computation in traffic management to cope for the projecting congestion trend. This work simulates traffic system and develop an optimising algorithm to instruct the traffic signal timing...
A gene regulatory network reveals the regulatory relationships among genes at a cellular level. The accurate reconstruction of such networks using computational tools, from time series genetic expression data, is crucial to the understanding of the proper functioning of a living organism. Investigations in this domain focused mainly on the identification of as many true regulations as possible. This...
Here, we have proposed a statistical framework based on a novel bat algorithm inspired particle swarm optimisation algorithm for the reconstruction of gene regulatory networks from temporal gene expression data. The recurrent neural network formalism has been implemented to extract the underlying dynamics from time series microarray datasets accurately. The proposed swarm intelligence framework has...
In multi-robot exploration operation, each robot has to continuously decide which place to move next, after exploring their current location. In this paper we use the extended version of Particle Swarm Optimization (PSO) to robotic application, which is referred to as Robotic Particle Swarm Optimization (RPSO), a technique to compute robots' new location. To better adapt this technique to the collective...
This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper...
The fuzzy c-partition entropy approach for threshold selection is one of the best image thresholding techniques, but its complexity increases with the number of thresholds. In this paper we applied fuzzy entropy in image segmentation, used it to select the fuzzy region of membership function automatically so that an image can be transformed into fuzz domain with maximum fuzzy entropy, and implemented...
This paper presents the use of a bio-inspired method in robotics research. We discuss the Particle swarm optimization (PSO) for two ground robots: an omnidirectional rolling robot and a biped walker robot. For the wheeled robot, we studied the navigation in a flat environment with eventual obstacles. Thus, for the biped robot, we applied on the gesture of the straight walk. The PSO algorithm shows...
Power system structure is undergoing through restructuring process since a decade. Everyday a bulk amount of power is generated, transmitted and distributed via transmission network. The active power or the real power generated from the generator needs the reactive power for supporting its own transmission. This reactive power generation has some minimum limit which if generator fails to produce it...
Particle Swarm Optimisation (PSO) algorithm is known to be better than Genetic Algorithm (GA) as fewer operators are needed in its algorithm. However, it still has some weaknesses such as immature convergence; a condition whereby PSO tends to get trapped in a local optimum. This condition prevents them from being converged towards a better position. Various techniques have been proposed to tackle...
Particle swarm optimization (PSO) algorithms are now being practiced for more than a decade and have been extended to solve various types of optimization problems. However, straightforward application of PSO suffers from premature convergence and lacks of intensification around the local best locations. In this paper, we propose a new particle swarm optimization strategy, namely, particle swarm optimization...
This paper proposes new optimization algorithms for the optimal tuning of PI controllers dedicated to a class of second-order processes with integral component and variable parameters. The sensitivity analysis with respect to the parametric variations of the controlled process leads to the sensitivity models. The augmentation of the output sensitivity functions over the integral of absolute error...
A multi-objective daily generation scheduling model for the hydropower stations is established, in which two objective functions including maximization of peak-energy capacity benefits and maximization of power generation are involved, and the hierarchy particle swarm optimization (HPSO) algorithm solving the model is proposed, the algorithm can handle the level multi-objective optimization problem...
This paper applies Particle Swarm Optimization algorithm (PSO) in a Multi-objective Vehicle Routing Problem with Time Window (MVRPTW). Firstly, through the problem analysis, establish a versatile mathematical model. Secondly, introduce an effective particle code to successfully implement the algorithm. Finally, examples prove that PSO can be obtained the optimal solution quickly and efficiently of...
Two-ray model is the basic line-of-sight propagation model for radio-wave propagation. Fermat's principle of Geometrical optics theory shows that the optical ray path is the minimum distance, which can make the propagation problem of radio-wave into the optimization problem of path function. Particle Swarm Optimization (PSO) with the characteristic of better searching optimization, was used to calculate...
An improved particle swarm optimization algorithm (PSO) combined with quantum genetic algorithm is proposed, to solve the problems that the PSO is difficult to converge for benchmark complex problems and it's parameters are hard to define. The new algorithm is used for submersible path planning and simulation on some standard test functions. The results show that the improved is superior to the standard...
Due to the fast convergence, Particle swarm optimization (PSO) has been advocated to be especially suitable for multiobjective optimization. However, there is no information-sharing of with other particles in the population, except that each particle can access the global best. Thus, the premature convergence and lacks of intensification around the local best locations are inevitable during extending...
Recent research on particle swarm optimization (PSO) emphasizes the need to simply this algorithm. This paper is a short study on finding the minimal number of particles in a simplified PSO. We have taken into consideration a social-only variant, Pedersen's simplified PSO, and tested it with four popular optimization benchmark functions in order to discover which is the minimal number of particles...
In this paper, the optimal cross-sectional area of medium voltage feeder will be designed based on particle swarm optimization (PSO) so as to reduce power and energy losses and improve voltage profile in distribution system. To analyze the network status in any step, DC power flow is utilized which is done robustly and with high convergence rate of the system. In the proposed method, medium voltage...
Economic Load Dispatch is one of the most important tasks to be performed in the operation and planning of a power system that decides the generation schedule of generating units with an objective of minimizing the total fuel cost. Normally, the fuel cost of generators can be treated as a quadratic function of real power generation. In fact, valve point loading effect in thermal power plants introduces...
Pixel-level image fusion is widely used in many fields. We proposed a pixel-level image fusion algorithm based on particle swarm optimization with local search, that is, PSO-LS, which improves performance further. PSO-LS integrated the self-improvement mechanisms from memetic algorithms and can avoid local minimum in PSO. Experiments were carried out on two real world images. It is shown that fusion...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.