![]() |
![]() |
NeuroDimension Home | Products | Applications | Resources | Support | Order |
|
' Products NeuroSolutions TradingSolutions Trader68 Interactive Book Neural Network Course Genetic Server and Library Applications Medical Science Business Investment and Trading Manufacturing Sports Betting Academic Other Problem Types Resources Intro to Neural Networks Intro to Genetic Algorithms Partners and Clients Customer List Company History Employment Resellers Search Support Contact NeuroDimension Licensed User Center Order NeuroSolutions.com TradingSolutions.com |
|
|
Genetic Algorithms: MutationMutation is a genetic operator that alters one ore more gene values in a chromosome from its initial state. This can result in entirely new gene values being added to the gene pool. With these new gene values, the genetic algorithm may be able to arrive at better solution than was previously possible. Mutation is an important part of the genetic search as help helps to prevent the population from stagnating at any local optima. Mutation occurs during evolution according to a user-definable mutation probability. This probability should usually be set fairly low (0.01 is a good first choice). If it is set to high, the search will turn into a primitive random search.Genetic Server and Genetic Library include the following types of mutation: Flip Bit -A mutation operator that simply inverts the value of the chosen gene (0 goes to 1 and 1 goes to 0). This mutation operator can only be used for binary genes. Boundary - A mutation operator that replaces the value of the chosen gene with either the upper or lower bound for that gene (chosen randomly). This mutation operator can only be used for integer and float genes. Non-Uniform - A mutation operator that increases the probability that the amount of the mutation will be close to 0 as the generation number increases. This mutation operator keeps the population from stagnating in the early stages of the evolution then allows the genetic algorithm to fine tune the solution in the later stages of evolution. This mutation operator can only be used for integer and float genes. Uniform - A mutation operator that replaces the value of the chosen gene with a uniform random value selected between the user-specified upper and lower bounds for that gene. This mutation operator can only be used for integer and float genes. Gaussian - A mutation operator that adds a unit Gaussian distributed random value to the chosen gene. The new gene value is clipped if it falls outside of the user-specified lower or upper bounds for that gene. This mutation operator can only be used for integer and float genes.
Product questions? Contact info@nd.com |
|
|
|