Optimizing Adaptive Neuro Fuzzy Inference System (ANFIS) parameters using Cuckoo Search (Case study of world crude oil price estimatio)

Anshori, Mohamad Yusak and Rahmalia, Dinita and Herlambang, Teguh and Karya, Denis Fidita (2020) Optimizing Adaptive Neuro Fuzzy Inference System (ANFIS) parameters using Cuckoo Search (Case study of world crude oil price estimatio). Journal of Physics: Conference Series. pp. 1-10. ISSN 1742-6596

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Abstract

There are some methods that have found for estimating data and one of them is Adaptive Neuro Fuzzy Inference System (ANFIS). In estimation using ANFIS, there are some initial parameters such as premise parameters (nonlinear) and consequent parameters (linear) which should be fixed to be trained forward and backward by gradient descent. In this research with case study of world crude oil price estimation, initial ANFIS parameters will be optimized by Cuckoo Search method. Cuckoo Search uses reproduction strategy i.e. laying their eggs in the other bird's nest. When the eggs are hatched, their chicks are fed by other birds. In Cuckoo Search method, initial ANFIS parameters is represented as bird nest position. Based on simulation, Cuckoo Search method can optimize initial ANFIS parameters giving the best estimation both of training data and testing data in world crude oil price estimation.

Item Type:	Article
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions:	Faculty of Economics and Business > Program Study of Management
Depositing User:	Mr. . Aji
Date Deposited:	29 Sep 2021 03:07
Last Modified:	01 Nov 2023 09:37
URI:	http://repository.unusa.ac.id/id/eprint/6682

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