Comparing the accuracy of regression and artificial intelligence methods in estimating daily wind speed in the Sistan region

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PIRI SAHRAGARD H.; PAHLAVANRAVI A.; PIRI J.; abtin a.

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Journal: Desert Management Year:2017 | Volume:4 | Issue:8 Page(s): 84-95

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Title

Comparing the accuracy of regression and artificial intelligence methods in estimating daily wind speed in the Sistan region

Author(s)

PIRI SAHRAGARD H. | PAHLAVANRAVI A. | PIRI J. | abtin a. | Issue Writer Certificate

Keywords

Sensitivity analysisQ1

Mean square errorQ1

Neuro-fuzzy methodQ1

Coefficient of determinationQ1

Abstract

This paper aims at comparing the accuracy of regression, artificial intelligence, and adaptive neuro-fuzzy (ANFIS) interpretation methods in estimating wind speed in the Sistan region. To this end, we used the daily weather information obtained from Zabol synoptic stations during a five-year period (2010-2015). MATLAB software was used for modeling based on artificial neural network. On the other hand, DATA FIT software was used for modeling based on regression methods. The methods’ accuracies were estimated using Mean square error statistics, comparison indexes, and mean error. Based on Sensitivity analysis results; variables such as daily temperature mean, mean relative humidity, sunshine hours, and evaporation from pan were regarded as input variables of regression and artificial intelligence methods. Wind speed was considered as output variable. Based on the results, mean daily temperature and mean relative humidity had the most and the least effect on wind speed in Sistan (0. 42 and 0. 25 respectively). Neuro-fuzzy method with Gaussian function was the most accurate method in estimating wind speed (error squares mean of 2. 56). The same statistic for regression method is 4. 44. The correlation of regression method (0. 45 and 0. 51) is less than those of multilayer perceptron method and Neuro-fuzzy method (0. 51 and 0. 52). So, it is suggested that Neuro-fuzzy method can be used for more accurate estimating wind speed in Sistan region. With accurate estimation of this variable, we can hinder the devastative effects of wind and use it as an effective source of energy.

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APA: Copy

PIRI SAHRAGARD, H., PAHLAVANRAVI, A., PIRI, J., & abtin, a.. (2017). Comparing the accuracy of regression and artificial intelligence methods in estimating daily wind speed in the Sistan region. DESERT MANAGEMENT, 4(8 ), 84-95. SID. https://sid.ir/paper/252855/en

Vancouver: Copy

PIRI SAHRAGARD H., PAHLAVANRAVI A., PIRI J., abtin a.. Comparing the accuracy of regression and artificial intelligence methods in estimating daily wind speed in the Sistan region. DESERT MANAGEMENT[Internet]. 2017;4(8 ):84-95. Available from: https://sid.ir/paper/252855/en

IEEE: Copy

H. PIRI SAHRAGARD, A. PAHLAVANRAVI, J. PIRI, and a. abtin, “Comparing the accuracy of regression and artificial intelligence methods in estimating daily wind speed in the Sistan region,” DESERT MANAGEMENT, vol. 4, no. 8 , pp. 84–95, 2017, [Online]. Available: https://sid.ir/paper/252855/en

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