Quantum Particle Swarm Optimization
Enhancement of quantum particle swarm optimization in elman recurrent network with bounded VMAX function
... Quantum Particle Swarm Optimization in Elman Recurrent Neural Network (QPSOERN) with bounded Vmax function are developed and tested on XOR, Cancer and Iris ...
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EFFICIENT SCHEDULING OF WORKFLOW IN CLOUD ENVIORNMENT USING BILLING MODEL AWARE TASK CLUSTERING
... rules, Particle Swarm Optimization (PSO) algorithm is projected, which gives feasible threshold values for minimum support and ...each particle and then finds their corresponding support and ...
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Novel Adaptive Neural Controller Design Based on HVDC Transmission System to Damp Low Frequency Oscillations and Sub Synchronous Resonance
... This paper presents the effect of the high voltage direct current (HVDC) transmission system based on voltage source converter (VSC) on the sub synchronous resonance (SSR) and low fre- quency oscillations (LFO) in power ...
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Hybrid Intuitionistic Fuzzy Fused Quantum Particle Swarm Intelligence for the Prediction of Dyslexia
... the quantum particle swarm optimization which involves in the assignment of weights to those instances with multi-class labels, more ...
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The planing of distribution generation (dg) based on multi objective quantum particle swarms optimization (qpso)
... of quantum system, and has high computing capability beyond the classical calculation and great potential in the aspect of information ...the quantum particle swarm optimization (QPSO) ...
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Biologically Inspired Dictionary Learning for Visual Pattern Recognition
... Holonomic brain theory provides an understanding of neural system behaviour. It is argued that recognition of objects in mammalian brain follows a sparse representation of responses to bar-like structures. We considered ...
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Quantum behaved Particle Swarm Optimization for Economic/Emission Dispatch Problem of Power System
... [3] T. Niknam, H.D. Mojarrad, B.B. Firouzi, A new optimization algorithm for multi-objective economic/emission dispatch Int. J. Electrical Power and Energy Systems, 46 (2013) 283-293. [4] D. Aydin, S. Őzyőn, C. ...
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A Survey on Economic Load Dispatch Problem Using Particle Swarm Optimization Technique
... a quantum inspired particle swarm optimization ( QPSO) is proposed, which has stronger search ability and quicker convergence speed, not only because of the introduction of computing theory, ...
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Design and Analysis of an Improved MPPT for Photovoltaic Grid-Connected Inverter Based
... Abstract: One of the major drawbacks of photovoltaic (PV) systems is represented by the effect of module mismatching and of partial shading of the PV field. This paper proposes a method of maximum power point tracking ...
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Improved Quantum Behaved Particle Swarm Optimization
... The QPSO Improvement Based on Quantum Computing In this section, we propose a Bloch sphere-based quantum-behaved particle swarm optimization algorithm called BQPSO... The Spherical Descr[r] ...
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4968938.pdf
... nature, particle swarm optimization (PSO) has been widely applied to address the multiobjective optimization problems ...of quantum-behaved particle swarm ...
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A Novel PSO Algorithm Model Based on Population Migration Strategy and its Application
... From Table 2, It is easy to see that there are higher convergence accuracy and success rate for PM-CPSO than that for PSO, AM-PSO, AF-PSO, SM-PSO, from the mean and deviation in Table 2, PM-CPSO has a better stability ...
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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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Deep Learning Methods and Optimization Algorithms in Bioinformatics Field: A Review
... Binary Particle Swarm Optimization (EPSO) Enhanced binary particle swarm optimization (EPSO), basically is an enhancement algorithm version made from binary particle ...
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Fusion global-local-topology particle swarm optimization for global optimization problems
... fuzzy particle swarm optimization (AFPSO) [19] was proposed to utilize fuzzy inferences for adjusting acceleration ...adaptive particle swarm optimization (APSO) [18] using a ...
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A. Particle Swarm Optimization
... which the genome is split into mutually exclusive blocks, each with a haplotype block that defines 80 percent of variation in the swarm. This decreases the variability of each block resulting in a high degree of ...
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Optimal Capacitor Allocation in 69-bus Radial Distribution System to Improve Annual Cost Savings for Dynamic Load Sarath Bapu R S S 1, Chandra Prakash V2 , Dr. S.M.Kannan 3
... This paper has discussed the optimal placement of capacitors in 69-bus RDF system considering the dynamic loaded conditions or load levels and provided the considerable improvement of voltage profile and the reduction of ...
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Parallel Implementation of Particle Swarm Optimization Variants Using Graphics Processing Unit Platform
... Particle Swarm Optimization (PSO) has been successfully applied to a lot of difficult and complex optimization problems such as artificial neural network training, function optimization ...
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Parameter optimization of evolving spiking neural networks using improved firefly algorithm for classification tasks
... with particle swarm optimization (PSO) and angle-driven dependency learning rate has been presented for different methods for classification problems (Ahmed et ...
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EHPSO: An Enhanced Hybrid Particle Swarm Optimization Algorithm for Internet of Things
... The Particle Swarm Algorithm, an evolutionary intelligence algorithm, was first proposed by Kennedy and Eberhart in 1995 . Comparing to other algorithms, it has many advantages. For instance, it is not easy ...
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