Application of Genetic Algorithm to Optimize the Performance of Adaptive Neural-Fuzzy Inference System in order to predict maximum of air temperature (Case study: Isfahan city)

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manoochehri nia mehran; Azad armin; FARZIN SAEED; KARAMI HOJAT

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Journal: IRANIAN JOURNAL OF ECOHYDROLOGY Year:2018 | Volume:5 | Issue:3 Page(s): 763-775

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Title

Application of Genetic Algorithm to Optimize the Performance of Adaptive Neural-Fuzzy Inference System in order to predict maximum of air temperature (Case study: Isfahan city)

Author(s)

manoochehri nia mehran | Azad armin | FARZIN SAEED | KARAMI HOJAT | Issue Writer Certificate

Keywords

Adaptive Neural-Fuzzy Inference SystemQ2

Hybrid Evolutionary AlgorithmsQ2

Genetic AlgorithmQ2

Local Optimum SolutionQ3

Air TemperatureQ2

Abstract

In this study, the use of genetic optimization algorithm (GA), Particle Swarm(PSO), the ant colony for continuum (ACOR)and differential evolution (DE), to develop and improve the performance of ANFIS were investigated. the monthly maximum temperatures in Isfahan during the period of 64 years (1951-2014), was simulated and analyzed. At first in a sensitivity analysis, the best entries for each prediction period (1 month, 1, 2 and 3 years) were selected. Then, the maximum temperature hybrid models by ANFIS-GA, ANFIS-PSO, ANFIS-DE, ANFIS-ACOR and ANFIS were examined. The performance of each model with regard to R2, RMSE and MAE were evaluated. The results showed that the ANFIS-GA, as the most appropriate model, increased ANFIS performance in R2 to by 0. 06, 0. 07, 0. 08 and 0. 12 and RMSE by 0. 09, 0. 09, 0. 16 and 0. 1, respectively, in 1 month and 1, 2 and 3 year. After, ANFIS-DE and ANFIS-PSO, respectively, had the best forecasting accuracy. On the other hand, ANFIS showed highest error and lowest R2, as the weakest model. The results showed that the proposed models, which use global search techniques and avoid being trapped in local optimum, could improve the performance of ANFIS favorably. Therefore, these models can be used in other areas related to hydrology and water resources.

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APA: Copy

manoochehri nia, mehran, Azad, armin, FARZIN, SAEED, & KARAMI, HOJAT. (2018). Application of Genetic Algorithm to Optimize the Performance of Adaptive Neural-Fuzzy Inference System in order to predict maximum of air temperature (Case study: Isfahan city). IRANIAN JOURNAL OF ECOHYDROLOGY, 5(3 ), 763-775. SID. https://sid.ir/paper/254017/en

Vancouver: Copy

manoochehri nia mehran, Azad armin, FARZIN SAEED, KARAMI HOJAT. Application of Genetic Algorithm to Optimize the Performance of Adaptive Neural-Fuzzy Inference System in order to predict maximum of air temperature (Case study: Isfahan city). IRANIAN JOURNAL OF ECOHYDROLOGY[Internet]. 2018;5(3 ):763-775. Available from: https://sid.ir/paper/254017/en

IEEE: Copy

mehran manoochehri nia, armin Azad, SAEED FARZIN, and HOJAT KARAMI, “ Application of Genetic Algorithm to Optimize the Performance of Adaptive Neural-Fuzzy Inference System in order to predict maximum of air temperature (Case study: Isfahan city),” IRANIAN JOURNAL OF ECOHYDROLOGY, vol. 5, no. 3 , pp. 763–775, 2018, [Online]. Available: https://sid.ir/paper/254017/en

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