A novel genetic programming approach to control bloat using crossover and mutation with intelligence technique
Autor: | Pankaj Dashore, Harshit Bhardwaj |
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Rok vydání: | 2015 |
Předmět: |
business.industry
Computer science Crossover MathematicsofComputing_NUMERICALANALYSIS Genetic programming ComputingMethodologies_ARTIFICIALINTELLIGENCE Tree (data structure) Mutation (genetic algorithm) Benchmark (computing) Fitness measure Artificial intelligence business Control (linguistics) Algorithm |
Zdroj: | 2015 International Conference on Computer, Communication and Control (IC4). |
DOI: | 10.1109/ic4.2015.7375619 |
Popis: | Bloat is a problem that occurs when there is no advancement in fitness measure, but the size of the tree grows exponentially. Bloat eventually increases the time required to reach the optimal solution. To overcome this defect, Crossover and Mutation with Intelligence technique is proposed. We also used double tournament, in which we apply two tournaments on the basis of size and fitness respectively to select the individuals to perform Crossover with Intelligence. Our approach of overcoming bloat is tested experimentally on some benchmark datasets picked up from UCI repository and by some observations. The results verified that our Crossover and Mutation with Intelligence degrades the bloat phenomena. |
Databáze: | OpenAIRE |
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