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| Title: | A CONCURRENT NEURAL NETWORK - GENETIC PROGRAMMING MODEL FOR DECISION SUPPORT SYSTEMS | |
| DOI No: | 10.1142/9789812701527_0020 | |
| Source: | KNOWLEDGE MANAGEMENT: NURTURING CULTURE, INNOVATION AND TECHNOLOGY (pp 231-245) | |
| Author(s): | AJITH ABRAHAM
School of Computer Science and Engineering, Chung-Ang University, Korea CRINA GROSAN Department of Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania CONG TRAN School of Electrical and Information Engineering, University of South Australia, Australia LAKHMI JAIN School of Electrical and Information Engineering, University of South Australia, Australia |
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| Abstract: | This paper suggests a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and three well known genetic programming techniques to classify the different decision regions accurately. The genetic programming techniques used are: Linear Genetic programming (LGP), Multi Expression Programming (MEP) and Gene Expression Programming (GEP). The clustered data is used as the inputs to the genetic programming algorithms. Some simulation results demonstrating the difference of these techniques and are also performed. Experiment results reveal that the proposed method is efficient. | |
| Full Text: | View full text in PDF format (765KB) | |
| TOC: | Back to Table of Contents | |
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