tailieunhanh - Stochastic Controledited Part 5

Tham khảo tài liệu 'stochastic controledited part 5', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 152 Stochastic Control research. The search of PSO spreads all over the solution space so the global optimal solution can be easily got what is more the PSO requires neither continuity nor differentiability for the target function even doesn t require the format of explicit function the only requirement is that the problem should be computable. In order to realize the PSO algorithm a swarm of random particles should be initialized at first and then get the optimal solution through iteration calculation. For each iteration calculation the particles found out their individual optimal value of pbest through tracking themselves and the global optimal value of gbest through tracking the whole swarm. The following formula is used to update the velocity and position. vd wV ci-rand- fíd Vc d-p - 1 1 k k 1 Xid xid vid 2 In the formula 1 and 2 i 1 2 . m m refers to the total number of the particles in the k swarm d 1 2 . n d refers to the dimension of the particle Vd is the No. d dimension k component of the flight velocity vector of iteration particle i of the No. k times. x d is the No. d dimension component of the position vector of iteration particle i of the No. k times Pd is the No. d dimension component of the optimization position pbest of particle i Pgd is the No. d dimension component of the optimization position gbest of the swarm w is the inertia weight c1 c2 refer to the acceleration constants rand refers to the random function which generates random number between 0 1 . Moreover in order to prevent excessive particle velocity set the speed limit for Vmax when accelerating the particle velocity into the level Vid Vmax set Vid Vmax In contrast on the condition of Vid -Vmax set Vid -Vmax. The specific steps of the PSO algorithm are as follows 1 Setting the number of particles m the acceleration constant c1 c2 inertia weight coefficient w and the maximum evolution generation Tmax in the n-dimensional space generating the initial position X t and velocity V t of

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