Elsevier

Applied Soft Computing

Volume 111, November 2021, 107735
Applied Soft Computing

Grey forecasting models based on internal optimization for Novel Corona virus (COVID-19)

https://doi.org/10.1016/j.asoc.2021.107735Get rights and content

Highlights

  • Internal optimization and diverse overlap data pattern based grey models (IOGMs) are proposed.

  • Conventional Grey models and proposed one are evaluated on benchmark time series.

  • Models are employed to predict the COVID cases in different locations of India.

  • Evaluation is based on errors in simulation & forecasting along with average ranks.

Abstract

Pandemic forecasting has become an uphill task for the researchers on account of the paucity of sufficient data in the present times. The world is fighting with the Novel Coronavirus to save human life. In a bid to extend help to the concerned authorities, forecasting engines are invaluable assets. Considering this fact, the presented work is a proposal of two Internally Optimized Grey Prediction Models (IOGMs). These models are based on the modification of the conventional Grey Forecasting model (GM(1,1)). The IOGMs are formed by stacking infected case data with diverse overlap periods for forecasting pandemic spread at different locations in India. First, IOGM is tested using time series data. Its two models are then employed for forecasting the pandemic spread in three large Indian states namely, Rajasthan, Gujarat, Maharashtra and union territory Delhi.

Several test runs are carried out to evaluate the performance of proposed grey models and conventional grey models GM(1,1) and NGM(1,1,k). It is observed that the prediction accuracies of the proposed models are satisfactory and the forecasted results align with the mean infected cases. Investigations based on the evaluation of error indices indicate that the model with a higher overlap period provides better results.

Keywords

Corona
Grey forecasting models
Optimization
Mean Absolute Percentage Error (MAPE)

Cited by (0)

Dr. Akash Saxena received his Ph.D. and Master of Technology Degree (with Honours) in Electrical Engineering from Malviya National Institute of Technology, Jaipur in 2015 and 2008 respectively and a Bachelor of Engineering Degree (with Honours) in Electrical Engineering from Engineering College Kota in 2001. Dr. Akash is the proud recipient of Chartered Management Institute (Level 3) Diploma in Management which represents a global benchmark for excellence. Also, he is a senior member of IEEE. Dr. Akash Saxena has been working as a Professor in Electrical Engineering Department of SKIT, Jaipur, India since 2014 with almost two decades of teaching.As an academician, he has been associated with numerous institutions as Member, Doctoral Research Committee and Member, Board of Studies. He has presented his research work at various platforms to showcase his findings to the fellow researchers and providing a pathway to the future researchers. His intellectual work has been published in leading journals in the form of short communication/letters /articles/research papers. A number of prestigious professional organizations have taken him on board as an editor, reviewer and adviser. Dr. Akash Saxena has to his credit a number of accomplished sponsored projects from the prestigious government organizations. Dr. Akash Saxena who has been a passionate researcher is currently immersed into extensive research in the areas of Computational Intelligence, Application of Artificial Intelligence in the Power System, and Smart Grid. He has published more than 70 quality research papers in international refereed journals and conferences and supervised 22 Master theses hitherto.

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