Modelling Climatic Parameters Affecting the Annual Yield of Rheum Ribes Rangeland Species using Data Mining Algorithms

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BASHIRI MEHDI; MAROOSI ALI

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Journal Paper

Paper Information

Journal: Journal of Rangeland Year:2020 | Volume:14 | Issue:3 Page(s): 435-451

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Title

Modelling Climatic Parameters Affecting the Annual Yield of Rheum Ribes Rangeland Species using Data Mining Algorithms

Author(s)

BASHIRI MEHDI | MAROOSI ALI | Issue Writer Certificate

Keywords

Annual yieldQ2

ClimateQ1

Data miningQ2

ModellingQ1

Stepwise regressionQ1

Abstract

Identification of climatic characteristics affecting the Annual yield of Rheum Ribes can be useful in management and development of this species in the rangelands. In this research, the Annual yield of this species in Khorasan-Razavi province based on 74 climatic parameters during a ten-year period evaluated and affecting climatic parameters extracted using Data mining methods. First, the role of climatic parameters associated with temperature, humidity, rainfall and sunny hours analyzed using correlation and regression methods. Then, 11 classification algorithms in MATLAB software programmed and compared. The results showed that the Rheum Ribes yield has a positive relationship with the average of maximum temperatures in the summer, the range of high temperature in May to September, the maximum of summer temperatures and the relative humidity and rainfall of the spring. Evaluation of the algorithms using the indices of coefficient of determination and mean square error showed that in estimation of the Annual yield based on climatic factors, the pattern recognition method at the testing stage with a coefficient of determination equal to 0. 46 and regression methods, classification discrimination and K nearest neighbor (KNN) at the training stage (coefficient of determination equal to 1) had the best performance. With regard to the effective factors in stepwise method, the linear regression method at the testing stage (coefficient of determination equal to 0. 74) and K nearest neighbor method at the training stage with coefficient of determination equal to 1, estimate the Rheum Ribes yield more accurately. Also, the proposed K nearest to mean (KNM) method for k values equal to 6 and 7 with regard to all factors and the effective factors resulted from stepwise method, respectively, had higher accuracy in yield estimation. So, application of Data mining methods and the proposed model, in recognition of Climate parameters affecting different rangeland species could be a practical approach.

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APA: Copy

BASHIRI, MEHDI, & MAROOSI, ALI. (2020). Modelling Climatic Parameters Affecting the Annual Yield of Rheum Ribes Rangeland Species using Data Mining Algorithms. RANGELAND, 14(3 ), 435-451. SID. https://sid.ir/paper/387697/en

Vancouver: Copy

BASHIRI MEHDI, MAROOSI ALI. Modelling Climatic Parameters Affecting the Annual Yield of Rheum Ribes Rangeland Species using Data Mining Algorithms. RANGELAND[Internet]. 2020;14(3 ):435-451. Available from: https://sid.ir/paper/387697/en

IEEE: Copy

MEHDI BASHIRI, and ALI MAROOSI, “Modelling Climatic Parameters Affecting the Annual Yield of Rheum Ribes Rangeland Species using Data Mining Algorithms,” RANGELAND, vol. 14, no. 3 , pp. 435–451, 2020, [Online]. Available: https://sid.ir/paper/387697/en

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