کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
566310 875963 2010 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Application of advanced Grammatical Evolution to function prediction problem
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزار
پیش نمایش صفحه اول مقاله
Application of advanced Grammatical Evolution to function prediction problem
چکیده انگلیسی

Grammatical Evolution (GE) is one of the evolutionary algorithms to find functions and programs, which can deal according to a syntax with tree structure by one-dimensional chromosome of Genetic Algorithm. An original GE starts from the definition of the syntax by means of Backus Naur Form (BNF). Chromosome in binary number is translated to that in decimal number. The BNF syntax selects according to the remainder of the decimal number with respect to the total number of candidate rules. In this study, we will introduce three schemes for improving the convergence property of the original GE. In numerical examples, the original GE is compared in function identification problem with the Genetic Programming (GP), which is one of the most popular evolutionary algorithm to find unknown functions or programs. Three algorithms are compared in Santa Fe trail problem and prediction problem of Nikkei stock average, which finds programs to control artificial ants collecting foods. The results show that the efficiency of schemes depends on the problem to be solved and that the schemes 1 and 2 are effective for Santa Fe trail problem and prediction problem of Nikkei stock average, respectively.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 41, Issue 12, December 2010, Pages 1287–1294
نویسندگان
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