S
Sandeep Kumar
Researcher at Christ University
Publications - 93
Citations - 1605
Sandeep Kumar is an academic researcher from Christ University. The author has contributed to research in topics: Artificial bee colony algorithm & Swarm intelligence. The author has an hindex of 16, co-authored 92 publications receiving 953 citations. Previous affiliations of Sandeep Kumar include Jagannath University & Guru Gobind Singh Indraprastha University.
Papers
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Prediction of COVID-19 corona virus pandemic based on time series data using support vector machine
Vijander Singh,Ramesh C. Poonia,Ramesh C. Poonia,Sandeep Kumar,Pranav Dass,Pankaj Agarwal,Vaibhav Bhatnagar,Linesh Raja +7 more
TL;DR: The Corona Virus Disease 2019 (COVID-19) prediction of confirmed, deceased and recovered cases will help to plan resources, determine government policy, and provide survivors with immunity passports, and use the same plasma for care.
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Descriptive analysis of COVID-19 patients in the context of India
Vaibhav Bhatnagar,Ramesh C. Poonia,Pankaj Nagar,Sandeep Kumar,Vijander Singh,Linesh Raja,Pranav Dass +6 more
TL;DR: In this article, a descriptive analysis of COVID-19 is performed and it is declared as pandemic by world health organization and this virus spread out from China to entire world.
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Analysis and predictions of spread, recovery, and death caused by COVID-19 in India
Rajani Kumari,Sandeep Kumar,Ramesh C. Poonia,Vijander Singh,Linesh Raja,Vaibhav Bhatnagar,Pankaj Agarwal +6 more
TL;DR: In this article, the authors presented a detailed study of recently developed forecasting models and predicted the number of confirmed, recovered, and death cases in India caused by COVID-19.
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Plant leaf disease identification using exponential spider monkey optimization
TL;DR: This paper introduces a novel exponential spider monkey optimization which is employed to fix the significant features from high dimensional set of features generated by SPAM and demonstrates that the selected features by Exponential SMO effectively increase the classification reliability of the classifier in comparison to the considered feature selection approaches.
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Automated soil prediction using bag-of-features and chaotic spider monkey optimization algorithm
TL;DR: An automated system for categorization of the soil datasets into respective categories using images of the soils using Bag-of-words and chaotic spider monkey optimization based method which can further be used for the decision of crops.