P. Rolland-Balzon November 04th, 2002
About Genetic Algorithm / Artificial Neural Network / C++
int popsize = 400; //default = 30; int ngen = 5000; //default = 100; float pmut = 0.01; //default = 0.001; float pcross = 0.6; //default = 0.9; GAParameterList params; GASimpleGA::registerDefaultParameters(params); params.set(gaNscoreFilename, "bog.dat"); params.set(gaNflushFrequency, 5); params.set(gaNpMutation, 0.001); params.set(gaNpCrossover, 0.8); params.parse(argc, argv, gaFalse); GA2DBinaryStringGenome genome(width, height, objective, (void *)target); GASimpleGA ga(genome); GASigmaTruncationScaling scaling; //Enable negative value in fitness function ga.parameters(params); ga.populationSize(popsize); ga.nGenerations(ngen); ga.pMutation(pmut); ga.pCrossover(pcross); ga.scaling(scaling); //Enable negative value in fitness function ga.evolve(); //Run Genetic algorithm with specified parameter