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Coping with such disadvantages of particle swarm optimization algorithm and GA as being easy to run into local optima, the method of cooperative optimization is proposed to solve the job shop scheduling problem by combing the quantum-behaved particle swarm optimization and GA. The algorithm applied the parallel hybrid architecture of collaborative quantum particle swarm and GA, in which a kind migration...
Neural networks (NNs) have been widely used to financial risk management because of their excellent performances of treating non-linear data with self-learning capability. However, the shortcoming of neural networks is also significant due to a "black box" syndrome and the difficulty in dealing with qualitative information, which limited its applications in practice. To overcome these drawbacks...
Particle swarm optimization (PSO) algorithm and fuzzy neural network (FNN) system has been widely used to solve complex decision making problems in practice. However, both of them more or less suffer from the slow convergence,"black-box" and occasionally involve in a local optimal solution. To overcome these drawbacks of PSO and FNN, in this study an improved particle swarm optimization...
The objective of feeder reconfiguration on distribution system during normal operation is to find the best switch operation plan for reducing power losses and enhancing service reliability. By changing on/off status of sectionalizing-switches and tie-switches on a distribution system, feeder reconfiguration can be achieved. Also, the configured system must satisfy operation conditions as well as restrictions...
Particle swarm optimization (PSO) algorithm and fuzzy neural network (FNN) system has been widely used to solve complex decision making problems in practice. However, both of them more or less suffer from the slow convergence and occasionally involve in a local optimal solution. To overcome these drawbacks of PSO and FNN, in this study a modified particle swarm optimization algorithm (MPSO) is developed...
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