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In this paper a hybrid model which is a combination of Memetic algorithm, cellular learning automata (CLA) and PSO is proposed. The proposed algorithm in addition to maintaining diversity; largely reduces the probability of getting trap in local optima. Experimental results on eight optimization problems show the superiority of the proposed algorithm.
In concern with the slow-convergence disadvantage of GA, PSO is combined with GA in this paper for a load distribution optimization among turbine-generators. By comparison with GA method, it is shown that PSO-GA is better than the GA method in the aspect of calculation speed, bearing excellent stability and fast convergence.
The Combined cooling, heating and power (CCHP) system should be operated under the optimal scheme to meet the varying demand for cooling, heating and electricity and to reduce cost and save energy for buildings. Based on the analysis of the energy flow, a mixed integer linear program (MILP) optimal model has been developed. The objectives are to minimize the annual total cost, primary energy consumption...
This paper presents an improved particle swarm optimization algorithm (IPSO) to optimal reactive power dispatch and voltage control of power system. The improved particle swarm optimization algorithm introduces the adaptive inertia factor into the classical swarm algorithm to improve the global search capability and accelerate the searching speed. Study the DPSO algorithm to construct the collection...
To reflect the bilateral transaction's uncertain impact on the grid, the effective reserve and the reserve channel margin are defined. And reserve capacity is modeled based on stochastic simulation and bi-level programming considering the congestion risk, which the reserve services are regarded as object of study in the open power market environment. The upper optimization level is to maximize the...
The aerodynamic optimization design and calculation of a 2MW horizontal axial wind turbine (HAWT) rotor are carried out based on particle swarm optimization (PSO) and the HAWT blade theory, which adopts wind velocity correction produced by the complicated wake vortexes and alterable circulation along the wind rotor blade axis, and combines the aerodynamic features of a horizontal axial wind turbine...
Automated Complementary Metal Oxide Semiconductor (CMOS) logic circuit design leads to the reduction in costs associated with manpower and manufacturing time. Conventional methods use repetitive manual testing guided by Logical Effort (LE). Our previous works have shown the applicability of the Particle Swarm Optimization (PSO) algorithm guided by LE in searching for optimal gate widths for CMOS design...
This paper investigates an identification approach of nonlinear system. Its basic idea of the method adopts a system model composed with classical models so as to change the system structure identification problem into a combinational problem. The hybrid algorithm of bacterial foraging optimization and particle swarm optimization technique is then applied to implement the identification on the system's...
The Artificial Bee Colony (ABC) algorithm is a new swarm optimization algorithm with good numerical optimization results. This paper presents an improved algorithm called fast mutation artificial bee colony algorithm or FMABC. During choosing food sources, the onlookers use the pheromone and the sensitivity model in Free Search algorithm to replace the traditional roulette wheel selection model. Then,...
This paper introduces dynamic distributed resource management in a Demand-Side Management (DSM) based simulation tool. The principle purpose of the simulation tool is to illustrate customer-driven DSM operation, and evaluate an estimate for home electricity consumption while minimizing the customer's cost. The tool simulates the operation of household appliances as a Hybrid Renewable Energy System...
Elevators play an important role in today urban life. The elevator group control (EGC) problem is related to many factors, such as stochastic traffic states, the number of customers, running condition, and it is difficulties in analysis, design and control. In order to increase the elevators running efficiency and quality of service, the optimizing control strategy of elevators is studied in this...
Normalized radial basis function (NRBF) neural network is presented to directly approach the Q-value function and generalize the information learnt by learning agent in continuous space. The action which impacts on environment is the one with maximum output of NRBF in the current state, and generated through Quantum-Behaved Particle Swarm Optimizer based on the current state. The effectiveness of...
The future marine traffic accident situation is shown by using the marine traffic accident prediction method. Thus, marine traffic accident prediction method based on particle swarm optimization-based RBF neural network is presented in the paper. Particle swarm optimization algorithm, a kind of population-based optimization algorithm, is used to adjust the connection weights and the center and width...
In this paper, we propose a fast and novel probabilistic fiber tracking method for DTI data using the particle swarm tracking technique, which considers both the local fiber orientation distribution and the global fiber path in collaborative manner. We first construct a global optimization model that captures both global fiber path and the uncertainties in local fiber orientation. Then, a global fiber...
This paper presents an improved method for capacitor placement in radial distribution feeders to reduce the real power loss and to improve the voltage profile. The location of the nodes where the capacitors should be placed is decided by a set of rules given by the fuzzy expert system. The sizing of the capacitors is modeled by the objective function to obtain maximum savings using Differential Evolution...
In this paper the synthesis of linear array geometry with minimum side lobe level using a new class of Particle Swarm Optimization technique namely Improved Particle Swarm Optimization (IPSO) is described. The IPSO algorithm is a newly proposed, high-performance evolutionary algorithm capable of solving general N-dimensional, linear and nonlinear optimization problems. Compared to other evolutionary...
The Inverse Fast Fourier technique (IFFT) combined with Artificial Bees Colony (ABC) and Modified Particle Swarm Optimization (MPSO) is used for the synthesis of thinned mutually coupled linear array with uniform element spacing. Coupling effect has been taken into account via induced EMF method and used to calculate the induced current on each element. Proposed technique is employed to thin the array...
This paper presents a novel method for design of circularly polarized axial mode helical antenna with maximum directive gain. In this work helical antenna is compactly modeled by the following parameters - helix radius (a), number of turns (N) and nonlinear pitch profile represented by a Catmull-Rom spline curve. This spline curve consists of six pitch angles α1, α2, α3, α4, α5 and α6 at six equidistant...
A novel null steering method depending on position perturbation of selected elements in circular arrays using new proposed optimization algorithm Hybrid EPSO/DE is presented in this paper. This method intends to reduce the number of perturbed elements in the array to form the null toward the interference direction by getting the optimum solution of the problem using the Hybrid EPSO/DE as optimization...
In many applications it is desirable to have the maximum radiation of an array directed normal to the axis of the array. In this paper, the broadside radiation patterns of three-ring Concentric Circular Antenna Arrays (CCAA) with central element feeding are reported. For each optimal synthesis, optimal current excitation weights and optimal radii of the rings are determined having the objective of...
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