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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 established a back propagation (BP) neural network tandem cold rolling force prediction model, and optimized by genetic particle swarm algorithm (GPSA). Genetic particle swarm algorithm has the advantage of both genetic algorithm (GA) and particle swarm algorithm (PSO) algorithm, integrates global searching ability with high convergence speed. Taking neural network weights and threshold...
Recently hybrid optimizations algorithm has attracted a lot of attention as a high-performance optimizer. This paper presents a comparison between different hybrid optimization algorithms. The proposed algorithms are used to design a slotted bow-tie antenna for 2.45 GHz Radio Frequency Identification (RFID) readers. The antenna is optimized using different algorithms integrated with the CST Microwave...
The recent emphasis on energy conversion demands an improvement of the efficiency of three-phase induction motors (IM). The high efficiency IM can be achieved by selecting optimum motor design parameters. Therefore, it is necessary to develop an efficient evolutionary approach for optimal design of three-phase IM. This paper presents a bacterial foraging (BF) algorithm for optimizing the IM design...
Image segmentation is a fundamental step for many image analysis and preprocessing tasks. In segmentation, minimum cross entropy (MCE) based multilevel thresholding is regarded as an effective improvement over the bi-level method. However, it is very time consuming for real-time applications. In this paper, a fast threshold selection method based on bacterial foraging optimization (BFO) algorithm...
In this paper we present uniformly excited unequally spaced linear-array synthesis with sidelobe suppression. We apply different evolutionary algorithms like Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) variants to position-only and position-phase synthesis. The DE algorithms include the common DE/rand/1/bin and the Self-adaptive strategies. The results...
A combination of Integer-Coded Genetic Algorithm (ICGA) and Particle Swarm Optimization (PSO), coupled with the neural-network-based Extreme Learning Machine (ELM), is used for gene selection and cancer classification. ICGA is used with PSO-ELM to select an optimal set of genes, which is then used to build a classifier to develop an algorithm (ICGA_PSO_ELM) that can handle sparse data and sample imbalance...
This paper introduces a novel adaptation scheme of mutation step size for the Artificial Bee Colony algorithm and compares its results with a number of swarm intelligence and population based optimization algorithms on complex multimodal benchmark problems. The Artificial Bee Colony (ABC) is a swarm based optimization algorithm mimicking the intelligent food foraging behavior of honey bees. The proposed...
Peer-to-Peer technology is one of the most popular techniques nowadays, and it brings some security issues, so the recognition and management of P2P applications on the internet is becoming much more important. The selection of protocol attributes is significant to the problem of P2P identification. To overcome the shortcomings of current methods, a new P2P identification algorithm based on genetic...
In view of the problem in the practical application of radial basis function (RBF) network, such as the number of nodes in the hidden layer and the parameters (w, c, and σ) are hard to determine, an improved particle swarm optimization (PSO) algorithm which makes use of the advantages of PSO algorithm and genetic algorithm (GA) is proposed, and then optimize the RBF network model with the new algorithm...
Partner selection is a critical issue in formation of virtual enterprises and increasing its operational effectiveness. Such a problem belongs to combinatorial optimization category and known as NP-hard problem. Usually, evolutionary methods are being adopted to obtain near-optimal solutions. In this paper, a variant of swarm optimization is proposed to handle combinatorial problems efficiently compared...
The development of power system video surveillance technology base on the development of image segmentation technology. Maximum variance between clusters (Otsu) is an complex, time-consuming image segmentation method. In light of this character, an optimization method. i. e. GA and PSO hybrid algorithm, which based the genetic algorithm (GA) and particle swarm optimization (PSO) is utilized to optimize...
A intrusion detection system model based on particle swarm reduction was proposed in this paper. Though the experiment of this model, it turns out that the improved algorithm of quantum particle swarm can get the minimal reduction, improve particle convergence and make particles trapped into local minima more difficult. The algorithm is faster than GA and has a high rate of network intrusion detection.
Magnetic Resonance Imaging (MRI) is one of the best technologies currently being used for diagnosing brain tumor. Brain tumor is diagnosed at advanced stages with the help of the MRI image. Segmentation is an important process to extract suspicious region from complex medical images. Automatic detection of brain tumor through MRI can provide the valuable outlook and accuracy of earlier brain tumor...
Outlier is strange data values that stand out from datasets. In some applications, finding outliers are more interesting than finding inliers in datasets, such as fraud detection, network system, financial and others. In this research, an algorithm is proposed to find minimum non-Reduct based on Rough set using Particle Swarm Optimization (PSO) for outlier detection. Like Genetic Algorithm (GA), PSO...
Planetary gear reducer is a typical device of power or motion transmission. The design of power planetary gear reducer may lead to significant effects on manufacturing, maintenance, operation and usability of an entire mechanical system. The optimal design of planetary gear reducer is to improve its loading capacity when its volume is reduced, weight lighted, efficiency raised and its service life...
The biclustering problem consists in simultaneously clustering rows and columns of a data matrix. The aim of this paper is to empirically assess the performance of cooperative coevolution as an alternative approach for coping with the task of discovering good and sizeable biclusters. For this purpose, two cooperative coevolutionary algorithms, one configured with genetic algorithms (GAs) and another...
A portfolio selection problem is about finding an optimal scheme to allocate a fixed amount of capital to a set of available assets. The optimal scheme is very helpful for investors in making decisions. However, finding the optimal scheme is difficult and time-consuming especially when the number of assets is large and some actual investment constraints are considered. This paper proposes a new approach...
To improve the precision of the function prediction, an effective optimization approach is proposed, where genetic algorithm (GA) and self-adaptive particle swarm optimization algorithm are hybridized to enhance the searching ability. Simulation results have shown that the hybrid scheme is effective and efficient for the function prediction.
PSO is a parallel stochastic optimization algorithm with advantages of less parameters and high efficiency. This paper describes the programming problem in the method of two linear tables with discrete and continuous quantity, then uses discrete PSO algorithm to discrete optimization and continuous PSO to optimize continuous quantity in the solving process respectively, based on these proposes the...
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