Abstract
Predictive analytics is the current focus not only on business applications but also it emerges in all types of applications which involves in the prediction of future outcomes. This results in the development of various prediction algorithms under the domain of machine learning, data mining, and forecasting. This paper focuses on analysis of the data pattern and its behavior using univariate forecasting model. Temperature is taken as the univariate observation from weather dataset, and the forecast value is predicted using forecasting algorithms. The predicted forecast value is compared with real-time data from which it is observed that level component plays a major role than trend and seasonal component in real-time data, and the predicted forecast value does not depend on size of the dataset.
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Poornima, S., Pushpalatha, M., Sujit Shankar, J. (2019). Analysis of Weather Data Using Forecasting Algorithms. In: Verma, N., Ghosh, A. (eds) Computational Intelligence: Theories, Applications and Future Directions - Volume I. Advances in Intelligent Systems and Computing, vol 798. Springer, Singapore. https://doi.org/10.1007/978-981-13-1132-1_1
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DOI: https://doi.org/10.1007/978-981-13-1132-1_1
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