Vector Optimization of Particle Swarm Optimization (VEPSO)
Features selection for intrusion detection system using hybridize PSO-SVM
... Support vector machine (SVM) is a popular machine learning technique which successfully has been applied to construct an intrusion detection ...combinatorial optimization in machine ...(hybridize ...
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Optimizing blasting’s air overpressure prediction model using swarm intelligence
... Support Vector Machines (SVM) and Genetic Algorithms (GA)) to predict AOp ...on swarm intelligence (SI) algorithm; particle swarm optimization (PSO) and multi swarm ...
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PID Controller Optimization for Rotational Inverted Pendulum System Using Particle Swarm Optimization and Differential Evolution Algorithms
... The DE algorithm is a population based algorithm like genetic algorithm which applies the three operators; crossover, mutation and selection. The main dissimilarity DE with GA is in finding better solutions as genetic ...
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Ensemble learning particle swarm optimization for real time UWB indoor localization
... Particle swarm optimization (PSO) is a population-level intelligent algorithm firstly proposed by Kennedy and Eberhart in 1995 [8, 9], which is originally from artificial intelligence and ...
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Fuzzy Particle Swarm Optimization Based Feature Learning Vector
... feature-weight vector cannot be adaptively adjusted during the training phase and also the update formulas of a feature-weight vector cannot be derived ...
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Automatic Image Annotation Based on Particle Swarm Optimization and Support Vector Clustering
... support vector clustering related information is ...support vector description ...single vector cluster- ing, the training data contains 𝑛 image clustering, each clus- tering contains 𝑥 𝑖 = {img 𝑖1 , ...
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Hybridizing PSO With SA for Optimizing SVR Applied to Software Effort Estimation
... investigates Particle Swarm Optimization (PSO) hybridization with Simulated Annealing (SA) to optimize Support Vector Machine ...The optimization of SVR consists of two sub-problems ...
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Feature Extraction Techniques Based on Swarm Intelligence in OCR
... Abstract: Optical Character Recognition is a most recent field in area of pattern recognition and machine learning in last decade. In this article, the suitable techniques are designated for better character recognition ...
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Comparative Analysis of Meta-Heuristic Algorithms based on their Application Areas in SRGM
... normal particle swarm optimization ...the particle swarm optimization approach in discovering the universal best possible solutions relies prominently on the introductory values ...
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Radial Basis Function Neural Network Trained by Adaptive Chaotic Particle Swarm Optimization to Control Nonlinear Systems
... Chaotic particle swarm optimization (CPSO) is a newly developed optimization technique which combines the benefits of particle swarm optimization (PSO) and the chaotic ...
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A. Particle Swarm Optimization
... [11], particle swarm optimization (PSO) simulates the social behavior of ...each particle will calculate the fitness value by a designed ...considers particle speed and best fitness ...
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A Review on Clustering Web data using PSO
... as Particle Swarm Optimization ...bio-inspired swarm intelligence algorithm introduced by Kennedy and Eberhart in 1995 as a population-based stochastic search and optimization process ...
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MFS PSO: A Modified PSO Method for Optimizing Gene Selection
... Particle Swarm Optimization (PSO) is an evolutionary method which simulates the social behavior of living organisms like: bird flocking and fish ...Each particle uses its individual memory and ...
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Particle swarm optimization application in optimization
... A multilayer perceptron model of beltline moulding was used to determine the optimal number of hidden units to represent the model and particle swarm optimization was used to minimize th[r] ...
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Belief Value Development In Dempster-Shafer With Particle Swarm Optimization(PSO) For Determining Of The Provision On Cases Of Persecution
... Abstract. The problem of uncertainty often becomes an obstacle, especially in terms of diagnosing the provision in this study. There is an algorithm that can solve this problem is Dempster-shafer (D-S), this algorithm ...
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Parallel Implementation of Particle Swarm Optimization Variants Using Graphics Processing Unit Platform
... of Particle Swarm Optimization (PSO) algorithm such as Adaptive Particle Swarm Optimization (APSO) and Particle Swarm Optimization with an Aging Leader and ...
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Multidimensional Particle Swarm Optimization for Machine Learning
... Particle swarm optimization (PSO) was introduced by Kennedy and Eberhart (1995) in 1995 as a population based stochastic search and optimization ...a swarm of particles, each of which ...
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Neural Network Optimization by Swarm Intelligence for Prediction & Classification of Benchmark Datasets
... output cannot be expected due to initial weights, epochs or network architecture at the first execution. And thus any of the parameters except weights and biases need to be altered and again training is required and the ...
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SENSOR DEPLOYMENT USING PARTICLE SWARM OPTIMIZATION
... Particle Swarm Optimization (PSO) is a population based stochastic search technique introduced by Kennedy and Eberhart in 1995 [Eberhart ...on particle swarm and parallel global random ...
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A Novel PSO Algorithm Model Based on Population Migration Strategy and its Application
... global optimization problem of the objective function having nonlinear or multipeaked ...global optimization algorithms were proposed mainly through the simulation of the evolution process of a group with ...
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