TY - JOUR ID - 1698 TI - Shuffled Frog-Leaping Programming for Solving Regression Problems JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Abdollahi, M. AU - Aliyari Shoorehdeli, M. AD - Department of Computer Engineering, K.N. Toosi University of Technology, Tehran, Iran. AD - Department of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran. Y1 - 2020 PY - 2020 VL - 8 IS - 3 SP - 331 EP - 341 KW - Genetic Programming KW - Shuffled Frog Leaping Algorithm KW - Shuffled Frog Leaping Programming KW - Regression Problems DO - 10.22044/jadm.2020.7847.1924 N2 - There are various automatic programming models inspired by evolutionary computation techniques. Due to the importance of devising an automatic mechanism to explore the complicated search space of mathematical problems where numerical methods fails, evolutionary computations are widely studied and applied to solve real world problems. One of the famous algorithm in optimization problem is shuffled frog leaping algorithm (SFLA) which is inspired by behaviour of frogs to find the highest quantity of available food by searching their environment both locally and globally. The results of SFLA prove that it is competitively effective to solve problems. In this paper, Shuffled Frog Leaping Programming (SFLP) inspired by SFLA is proposed as a novel type of automatic programming model to solve symbolic regression problems based on tree representation. Also, in SFLP, a new mechanism for improving constant numbers in the tree structure is proposed. In this way, different domains of mathematical problems can be addressed with the use of proposed method. To find out about the performance of generated solutions by SFLP, various experiments were conducted using a number of benchmark functions. The results were also compared with other evolutionary programming algorithms like BBP, GSP, GP and many variants of GP. UR - https://jad.shahroodut.ac.ir/article_1698.html L1 - https://jad.shahroodut.ac.ir/article_1698_4cc451902ceefd66954d47fad2547b9d.pdf ER -