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A Study on Evolutionary Technique to Predict the Sales During COVID-19

Manu PriyaDarshani, Mohan Prasad Sinha, Keshav Sinha

Source Title: Handbook of Research on Library Response to the COVID-19 Pandemic

ISBN13: 9781799864493|ISBN10: 1799864499|ISBN13 Softcover: 9781799864509|EISBN13: 9781799864516

DOI: 10.4018/978-1-7998-6449-3.ch020

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MLA

PriyaDarshani, Manu, et al. "A Study on Evolutionary Technique to Predict the Sales During COVID-19." Handbook of Research on Library Response to the COVID-19 Pandemic, edited by Barbara Holland, IGI Global, 2021, pp. 376-402. https://doi.org/10.4018/978-1-7998-6449-3.ch020

APA

PriyaDarshani, M., Sinha, M. P., & Sinha, K. (2021). A Study on Evolutionary Technique to Predict the Sales During COVID-19. In B. Holland (Ed.), Handbook of Research on Library Response to the COVID-19 Pandemic (pp. 376-402). IGI Global. https://doi.org/10.4018/978-1-7998-6449-3.ch020

Chicago

PriyaDarshani, Manu, Mohan Prasad Sinha, and Keshav Sinha. "A Study on Evolutionary Technique to Predict the Sales During COVID-19." In Handbook of Research on Library Response to the COVID-19 Pandemic, edited by Barbara Holland, 376-402. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-6449-3.ch020

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Abstract

COVID-19 has affected the growth of every industry; in the meantime, an enormous amount of demand is present in the field of telecom and automobiles. In this chapter, the authors present case studies based on sales prediction for the Indian market. The analysis of the study is based on the various traditional methods like growth rate (GR), percentage growth rate (PGR), and the evolutionary techniques like genetic algorithms (GA). The data are collected for the report of telecommunication and heavy industry ministry (Republic of India). The results are used to analyze the sale of automobiles and telecommunication devices and to predict the growth at the time of the COVID-19 pandemic. The prediction is used to identify the upcoming sale and counterparts with demand.

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A Study on Evolutionary Technique to Predict the Sales During COVID-19

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