Comparative Analysis of ANFIS, ARIMA and Polynomial Curve Fitting for Weather Forecasting

P  Srikanth; D  Rajeswara Rao  and P  Vidyullatha

doi:10.17485/ijst/2016/v9i15/89814

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Comparative Analysis of ANFIS, ARIMA and Polynomial Curve Fitting for Weather Forecasting

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2016/v9i15/89814

Year: 2016, Volume: 9, Issue: 15, Pages: 1-6

Original Article

Comparative Analysis of ANFIS, ARIMA and Polynomial Curve Fitting for Weather Forecasting

P. Srikanth^1*, D. Rajeswara Rao² and P. Vidyullatha¹

¹KL University, Guntur – 522502, Andhra Pradesh, India; [email protected], [email protected] ²Department of Computer Science and Engineering, KL University, Guntur – 522502, Andhra Pradesh, India; [email protected]

*Author of Corresponding: P. Srikanth KL University, Guntur – 522502, Andhra Pradesh, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Background/Objectives: Weather forecasting is to facilitate the appliance of knowledge and tools to predict the state of the atmosphere for a future time at a given location. Methods/Statistical Analysis: This paper focused to forecast the weather conditions on Indian weather conditions using three approaches such as ANFIS, ARIMA and polynomial curve fitting. It’s disbursed by collection quantitative information regarding state of the atmosphere and past and/or present experiences. Findings: In this analysis, this work reveals the superior performance of polynomial curve fitting through the SSE, RMSE, MAE and R2 .

Keywords: ANFIS, ARIMA, Curve Fitting, MAE, RMSE, R2, SSE, Weather Forecasting