[PDF] Top 20 Optimization of Biochemical Systems Production Using Combination of Newton Method and Particle Swarm Optimization
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Optimization of Biochemical Systems Production Using Combination of Newton Method and Particle Swarm Optimization
... Kennedy and Eberhart [23] who were inspired by the natural behavior of animal foraging such as flocks of birds, schools of fish or swarms of bees introduced the PSO algorithm. The PSO algorithm uses the movement of a ... See full document
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Optimization of PID Controller Parameters on Flow Rate Control System Using Multiple Effect Evaporator Particle Swarm Optimization
... a production process by modeling a production system by modeling in mathematical methods, it is also useful to predict the production system work before production systems are used, one ... See full document
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Design and optimization of photovoltaic fed wind driven hybrid energy systems using Newton Raphson and Particle Swarm optimization algorithms
... power will be fed to the battery bank for later usage. When the supply from the sources is insufficient, the energy from the battery pack will assist the PV array to fulfil load requirements until the storage is ... See full document
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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 ... See full document
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Hybrid fuzzy multi-objective particle swarm optimization for taxonomy extraction
... fuzzy systems are ...a combination of Continuous Particle Swarm Optimisation (PSO) and Discrete Binary PSO (BPSO) for the optimisation of fuzzy ...fuzzy systems are respectively ... See full document
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Power Transmission Optimization using Particle Swarm Optimization Method – A Review
... this paper GNA will be discussed and compared with the results of Genetic Algorithm (GA) as an example of another optimization method. In Reference [21] the main aim is to reduce the Real and Reactive Power ... See full document
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Optimal placement of distributed generation in distribution systems by using Shuffled Frog Leaping Algorithm
... In this paper SFLA has been used for DG sizes and locations are obtaining from PLI method to improve the voltage profile improvement, reduction in real power losses and economic benefit. In this paper the analysis ... See full document
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Optimization of hole-making operations for injection mould using particle swarm optimization algorithm Pages 433-444 Download PDF
... In machining process of many industrial parts such as dies and moulds, operations like drilling, reaming or tapping account for a large segment of process. Generally, a part, for e.g. a plastic injection mould may have ... See full document
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Theoretical Investigation of Combined Use of PSO, Tabu Search and Lagrangian Relaxation methods to solve the Unit Commitment Problem
... of production cost over other methods, but is faster than LR, DP, GA, LR-GA and ...total production cost with respecting all the constraints of the specified ...solutions using the tabu list while ... See full document
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Multilevel Thresholding Segmentation based on Otsu’s Method and Autonomous Groups Particle Swarm Optimization for Multispectral Image
... Threshold method is a method that is generally used in image segmentation to separate important targets from the background image. This is the basic principle for dividing image pixels into different ... See full document
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Hybrid Swarm Algorithm for Multiobjective Optimal Power Flow Problem
... problem. Particle Swarm Optimization (PSO) [6] inspires the school of fishes and a flock of birds and trapped in local ...problem using a random selec- tion of starting values of voltage ... See full document
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Comparative Analysis of SPSO and PSO to Optimal Power Flow Solutions
... In this paper, we implemented PSO and SPSO optimization techniques to solve the optimal power flow in steady state condition. The performance of the IEEE 30-bus test system is analysed and obtained fuel cost ... See full document
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Optimum Design of Homopolar Radial Two-Degree-of-Freedom Hybrid Magnetic Bearing
... the particle swarm is easy to fall into local optimum in the optimization ...of particle swarm, genetic algorithm is combined with particle swarm algorithm to generate ... See full document
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Novel Artificial Human Optimization Field Algorithms – The Beginning
... all Particle Swarm Optimization (PSO) algorithms are proposed such that the particles move towards best ...Human Optimization (MSHO)” in ...Thinking Particle Swarm ... See full document
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Neural Network Optimization by Swarm Intelligence for Prediction & Classification of Benchmark Datasets
... The benchmarking datasets [1] are all presented in the same simple format, using an attribute representation that can directly be used for neural network training. Along with the datasets, a set of rules for how ... See full document
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Study on Mutual Funds Trading Strategy Using TPSO and MACD
... The particle swarm optimization concept consists of, at each time step, changing the velocity and updates the location or position of each particle toward its pBest ...by particle ... See full document
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Study on the optimization algorithm of sediment particle Imshanage
... sediment particle image is the main bottleneck restricting river sediment image segmentation algorithm to ...basic particle swarm optimization (PSO) algorithm, a modified particle ... See full document
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Research on Parameter Identification Method of Lithium ion Battery Model Based on Particle Swarm Optimization Algorithm
... Battery model parameters are the vital data of battery characteristics, are the essence to estimate battery real time capacity and life cycle. BMS works effectively based on the battery model parameters identification ... See full document
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Parallel Implementation of Particle Swarm Optimization Variants Using Graphics Processing Unit Platform
... each particle from other particles, velocity, position and pBest update can be executed in parallel, while the tasks which are relevant to gBest update, because of their data dependency,` cannot be run in ... See full document
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MODIFICATION OF NEURAL NETWORK ALGORITHM USING CONJUGATE GRADIENT WITH ADDITION OF WEIGHT INITIALIZATION
... The GA algorithm generates an initial population randomly. A new population will now develop from this initial population using three basic fundamental genetic processes. These are selection based on fitness, ... See full document
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