matlab中的粒子群优化算法

2 回答

• 0

  我做了以前的代码非常感谢你 .

  我找到了一个关于PSO的新代码，我想用鼠标点击来定义一个窗口大小为[min1，max1]和[min2，max2]的空间点 .

  然后，初始化由n = 10个粒子组成的聚类，并搜索用户最初的点集 .

  代码是这样的：

  %% Initialization
  clear
  clc
  n = 50;          % Size of the swarm " no of birds "
  bird_setp  = 50; % Maximum number of "birds steps"
  dim = 2;          % Dimension of the problem
  
  c2 =1.1;          % PSO parameter C1 
  c1 = 0.12;        % PSO parameter C2 
  w =0.9;           % pso momentum or inertia  
  fitness=0*ones(n,bird_setp);
                                         %-----------------------------%
                                         %    initialize the parameter %
                                         %-----------------------------%
  
  R1 = rand(dim, n);
  R2 = rand(dim, n);
  current_fitness =0*ones(n,1);
  
                                   %------------------------------------------------%
                                   % Initializing swarm and velocities and position %
                                   %------------------------------------------------%
  
  current_position = 10*(rand(dim, n)-.5);
  velocity = .3*randn(dim, n) ;
  local_best_position  = current_position ;
  
  
                                   %-------------------------------------------%
                                   %     Evaluate initial population           %           
                                   %-------------------------------------------%
  
  for i = 1:n
      current_fitness(i) = Live_fn(current_position(:,i));    
  
  end
  
  
  local_best_fitness  = current_fitness ;
  [global_best_fitness,g] = min(local_best_fitness) ;
  
  for i=1:n
      globl_best_position(:,i) = local_best_position(:,g) ;
  
  end
                                                 %-------------------%
                                                 %  VELOCITY UPDATE  %
                                                 %-------------------%
  
  velocity = w *velocity + c1*(R1.*(local_best_position-current_position)) + c2*(R2.*(globl_best_position-current_position));
  
                                                 %------------------%
                                                 %   SWARMUPDATE    %
                                                 %------------------%
  
  
  current_position = current_position + velocity ;
  
                                                 %------------------------%
                                                 %  evaluate anew swarm   %
                                                 %------------------------%
  
  
  %% Main Loop
  iter = 0 ;        % Iterations’counter
  while  ( iter < bird_setp )
  iter = iter + 1;
  
  for i = 1:n,
  current_fitness(i) = Live_fn(current_position(:,i)) ;    
  
  end
  
  
  for i = 1 : n
          if current_fitness(i) < local_best_fitness(i)
             local_best_fitness(i)  = current_fitness(i);  
             local_best_position(:,i) = current_position(:,i)   ;
          end   
   end
  
  
   [current_global_best_fitness,g] = min(local_best_fitness);
  
  
  if current_global_best_fitness < global_best_fitness
     global_best_fitness = current_global_best_fitness;
  
      for i=1:n
          globl_best_position(:,i) = local_best_position(:,g);
      end
  
  end
  
  
   velocity = w *velocity + c1*(R1.*(local_best_position-current_position)) + c2*(R2.*(globl_best_position-current_position));
   current_position = current_position + velocity; 
  
  
  
  
  x=current_position(1,:);
  y=current_position(2,:);
  
  clf    
      plot(x, y , 'h')   
      axis([-5 5 -5 5]);
  
  pause(.2)
  
  
  end % end of while loop its mean the end of all step that the birds move it 
  
  
                [Jbest_min,I] = min(current_fitness) % minimum fitness
                 current_position(:,I) % best solution
  
  
  
  
  
  
  %
  

  回复于 2024-05-05T05:58:27+08:00
• 0

  您可以使用 ginput 获取鼠标单击的坐标：

  [x,y] = ginput;
  

  然后相应地定义您的窗口 .

  回复于 2024-05-05T05:58:27+08:00