Genetic Ink Drop Spread
Hesam Sagha, Saeed Bagheri Shouraki, Hamid Beigy, Seyed Hossein Khasteh, Elham Enayati · 2008
This paper describes a genetic-fuzzy system adapted to find efficient partitions on data domains for IDS (ink drop spread). IDS is the engine of Active Learning Method (ALM), a methodology of soft computing. IDS extracts useful information from a system subjected to modeling. Proposed method, called GIDS (Genetic IDS), uses genetic algorithm which optimizes the parameters of membership functions that represent the partitions on data planes. Obtained Results showed that using genetic algorithm to find the partitions has better accuracy than the previous generic IDS methods.