Cascade reservoir optimal operation method based on adaptive particle swarm optimization algorithm
A particle swarm optimization, cascade reservoir technology, applied in the direction of calculation, calculation model, data processing application, etc., can solve the problem of loss of population diversity, affecting the stability of the algorithm, affecting the speed and efficiency of convergence, etc.
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[0042] Such as figure 1 As shown, the specific steps of the application of dynamic grouping adaptive particle swarm optimization algorithm in cascade reservoir optimization scheduling are as follows:
[0043] (1) Fixed initialization of particles in the search area
[0044] Specify the size of the population, set the upper and lower limits of position and speed, and set the learning factor c 1 、c 2 、c 3 、c 4 , the maximum number of iterations and convergence accuracy of the algorithm.
[0045] (2) Evaluate the initialized particles
[0046] Calculate the fitness value of the particle according to the fitness function (set according to the specific situation), and then arrange the calculated fitness value in ascending order. The fitness value of is denoted as f min , and the largest one is denoted as f max , while calculating f avg , f' avg and f″ avg , divide the entire population into dynamic subgroups, greater than f min less than f" avg is inferior group, great...
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