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chapter13
- 粒子群算法优化的详细讲解和实例应用，欢迎下载-Particle swarm optimization algorithm and explain in detail the application example, welcome to download
Files-and-Codes
- Improving the efficiency of three-phase squirrel cage induction motors, which are the most energy consuming electric machines in the world, saves much energy. The efficiency can be raised by optimizing the induction motor design. The objective
dcmotor
- DC MOTOR WITH MATLAB Improving the efficiency of three-phase squirrel cage induction motors, which are the most energy consuming electric machines in the world, saves much energy. The efficiency can be raised by optimizing the induction motor d
Files-and-Codes
- SYSTEM DEGREE TWO WITH MATLAB . Improving the efficiency of three-phase squirrel cage induction motors, which are the most energy consuming electric machines in the world, saves much energy. The efficiency can be raised by optimizing the induct
sim33a
- electrical system with matlab. Improving the efficiency of three-phase squirrel cage induction motors, which are the most energy consuming electric machines in the world, saves much energy. The efficiency can be raised by optimizing the inducti
cir4trasformer
- paralell trans 3 phase with matlab. Improving the efficiency of three-phase squirrel cage induction motors, which are the most energy consuming electric machines in the world, saves much energy. The efficiency can be raised by optimizing the in
myMatlab-code
- In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. This algorithm is a member of the
ypea104-acor
- continuous ACO. In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. This algorithm
PSO
- In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of c