2009
DOI: 10.1016/j.eswa.2008.02.030
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Clone selection programming and its application to symbolic regression

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Cited by 33 publications
(15 citation statements)
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“…field. Compared with other approaches based on artificial immune system, clone selection programming (Gan et al, 2008) based method can significantly improve the program performance. In this paper, we extend clone selection programming to the design of classifier for machine fault detection.…”
Section: Introductionmentioning
confidence: 98%
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“…field. Compared with other approaches based on artificial immune system, clone selection programming (Gan et al, 2008) based method can significantly improve the program performance. In this paper, we extend clone selection programming to the design of classifier for machine fault detection.…”
Section: Introductionmentioning
confidence: 98%
“…We have proposed a new programming method, called clone selection programming (CSP) (Gan et al, 2008) based on the theories of the immune system to enhance the effectiveness of programs encoding and search engine. The newly proposed CSP can become a powerful tool applied widely into artificial intelligence and machine learning etc.…”
Section: Introductionmentioning
confidence: 99%
“…It is an extension of artificial immune system (AIS), which is a systematic, domain independent, and intelligent based method to solve regression problems. A specific operation is implemented by an antibody's affinity and a set of probabilistic parameters [13].…”
Section: Introductionmentioning
confidence: 99%
“…Having been motivated by evolutionary algorithms, researchers successfully have applied automatic programming algorithms to automatically generate programs or equations among the inputs and outputs. Depending on the type of evolutionary computation techniques used to produce variation in the population, different types of automatic programming models have been subsequently proposed [5][6][7][8][9][10][11][12][13][14][15].…”
Section: Introductionmentioning
confidence: 99%
“…The problem of SR is an optimization problem the purpose of which is finding the best combination of variables, symbols, and coefficients to develop an optimum model satisfying a set of fitness cases [16]. Depending on the type of optimization strategy applied for SR, different branches of SR have been introduced, such as Genetic programming (GP) [17], Immune programming (IP) [18], Dynamic ant programming (DAP) [19], Clone selection programming (CSP) [20] and artificial bee colony programming (ABCP) [16]. Various types of GP have been applied successfully in different areas of civil engineering.…”
Section: Introductionmentioning
confidence: 99%