University of Tabriz Tabriz Journal of Electrical Engineering 2008-7799 49 2 2019 07 23 A Nature-inspired Algorithm based on Classical-conditioning Theory A Nature-inspired Algorithm based on Classical-conditioning Theory 485 501 8878 FA R. Omidvar Department of Computer Engineering, Yasooj Branch, Islamic Azad University, Yasooj, Iran S. Nejatian Department of Electrical Engineering, Yasooj Branch, Islamic Azad University Young Researchers and Elite Clubs, Yasooj Branch, Islamic Azad University H. Parvin Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani Young Researchers and Elite Club, Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran V. Rezaei Young Researchers and Elite Clubs, Yasooj Branch, Islamic Azad University, Yasooj, Iran Department of Mathematic, Yasooj Branch, Islamic Azad University, Yasooj, Iran M. Yasrebi Department of Computer Engineering, Noorabad Mamasani Branch, Islamic Azad University, Noorabad Mamasani, Fars, Iran Journal Article 2017 10 15 Nature-inspired algorithms are the imitation of nature opened a new era in calculations for solving optimization problems. In this thesis, we will provide an optimization algorithm inspired by nature using the instinctive behavior of birds. In this thesis, particles learn to have a conditional normal behavior towards an unconditioned stimulus using the classical conditioning learning behavior of birds. Particles will be divided into multiple categories in the problem space. If any particle had a low-level category, it will try to move towards its best personal experience. If any particle had a high-level category, it will learn to move towards the global optimum in its category. Using the idea of birds’ sensitivity towards the environment, in which birds are flying, we tried to move particles in incompetent spaces more quickly so that the particle goes far away from that space, and vice versa, we will bring down the particles’ speed in valuable spaces to search for more. We selected a population based on the particles’ merit in the initial population selection using the instinctive behavior of birds. The proposed method was implemented in MATLAB software, and the results have been compared in several different ways. The results showed that the proposed method is a reliable algorithm to solve the static problems. Nature-inspired algorithms are the imitation of nature opened a new era in calculations for solving optimization problems. In this thesis, we will provide an optimization algorithm inspired by nature using the instinctive behavior of birds. In this thesis, particles learn to have a conditional normal behavior towards an unconditioned stimulus using the classical conditioning learning behavior of birds. Particles will be divided into multiple categories in the problem space. If any particle had a low-level category, it will try to move towards its best personal experience. If any particle had a high-level category, it will learn to move towards the global optimum in its category. Using the idea of birds’ sensitivity towards the environment, in which birds are flying, we tried to move particles in incompetent spaces more quickly so that the particle goes far away from that space, and vice versa, we will bring down the particles’ speed in valuable spaces to search for more. We selected a population based on the particles’ merit in the initial population selection using the instinctive behavior of birds. The proposed method was implemented in MATLAB software, and the results have been compared in several different ways. The results showed that the proposed method is a reliable algorithm to solve the static problems. https://tjee.tabrizu.ac.ir/article_8878_d7da4fc6f54c3fb53bf505fef2f3498e.pdf