A Novel Cellular Automata Classifier for COVID-19 Prediction
China has witnessed a new virus Corona, which is named COVID-19. It has become the world's most concern as this virus has spread over the world at a higher speed, the world has witnessed more than one lakh cases and one thousand deaths in a span of a few days. We have developed a preliminary cl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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University of Sarajevo
2020-03-01
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| Series: | Journal of Health Sciences |
| Subjects: | |
| Online Access: | https://www.jhsci.ba/ojs/index.php/jhsci/article/view/907 |
| _version_ | 1818081936732585984 |
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| author | Kiran Sree Pokkuluri SSSN Usha Devi N |
| author_facet | Kiran Sree Pokkuluri SSSN Usha Devi N |
| author_sort | Kiran Sree Pokkuluri |
| collection | DOAJ |
| description | China has witnessed a new virus Corona, which is named COVID-19. It has become the world's most concern as this virus has spread over the world at a higher speed, the world has witnessed more than one lakh cases and one thousand deaths in a span of a few days. We have developed a preliminary classifier with non-linear hybrid cellular automata, which is trained and tested to predict the effect of COVID-19 in terms of deaths, the number of people affected, the number of people being could be recovered, etc. This indirectly predicts the trend of this epidemic in India. We have collected the data sets from Kaggle and other standard websites. The proposed classifier, HNLCA (Hybrid Non-Linear Cellular Automata) was trained with 23078 datasets and tested with 6785 data sets. HNLCA is compared with conventional methods LSTM, Adaboost, SVM, Regression, and SVR has reported an accuracy of 78.8%, which is better compared with the cited literature. This classifier can also predict the rate at which this virus spreads, transmission within the boundary, and of the boundary, etc. |
| first_indexed | 2024-12-10T19:14:08Z |
| format | Article |
| id | doaj.art-1dfe13e8e8f44f61b79164eca76cca29 |
| institution | Directory Open Access Journal |
| issn | 2232-7576 1986-8049 |
| language | English |
| last_indexed | 2024-12-10T19:14:08Z |
| publishDate | 2020-03-01 |
| publisher | University of Sarajevo |
| record_format | Article |
| series | Journal of Health Sciences |
| spelling | doaj.art-1dfe13e8e8f44f61b79164eca76cca292022-12-22T01:36:39ZengUniversity of SarajevoJournal of Health Sciences2232-75761986-80492020-03-0110.17532/jhsci.2020.907A Novel Cellular Automata Classifier for COVID-19 PredictionKiran Sree Pokkuluri0SSSN Usha Devi N 1Department of CSE, Shri Vishnu Engineering College for Women, West Godavari District, Andhra Pradesh, IndiaDepartment of CSE, University College of Engineering, JNTU Kakinada, Andhra Pradesh, IndiaChina has witnessed a new virus Corona, which is named COVID-19. It has become the world's most concern as this virus has spread over the world at a higher speed, the world has witnessed more than one lakh cases and one thousand deaths in a span of a few days. We have developed a preliminary classifier with non-linear hybrid cellular automata, which is trained and tested to predict the effect of COVID-19 in terms of deaths, the number of people affected, the number of people being could be recovered, etc. This indirectly predicts the trend of this epidemic in India. We have collected the data sets from Kaggle and other standard websites. The proposed classifier, HNLCA (Hybrid Non-Linear Cellular Automata) was trained with 23078 datasets and tested with 6785 data sets. HNLCA is compared with conventional methods LSTM, Adaboost, SVM, Regression, and SVR has reported an accuracy of 78.8%, which is better compared with the cited literature. This classifier can also predict the rate at which this virus spreads, transmission within the boundary, and of the boundary, etc.https://www.jhsci.ba/ojs/index.php/jhsci/article/view/907COVID-19Cellular AutomataNon-Linear CA |
| spellingShingle | Kiran Sree Pokkuluri SSSN Usha Devi N A Novel Cellular Automata Classifier for COVID-19 Prediction Journal of Health Sciences COVID-19 Cellular Automata Non-Linear CA |
| title | A Novel Cellular Automata Classifier for COVID-19 Prediction |
| title_full | A Novel Cellular Automata Classifier for COVID-19 Prediction |
| title_fullStr | A Novel Cellular Automata Classifier for COVID-19 Prediction |
| title_full_unstemmed | A Novel Cellular Automata Classifier for COVID-19 Prediction |
| title_short | A Novel Cellular Automata Classifier for COVID-19 Prediction |
| title_sort | novel cellular automata classifier for covid 19 prediction |
| topic | COVID-19 Cellular Automata Non-Linear CA |
| url | https://www.jhsci.ba/ojs/index.php/jhsci/article/view/907 |
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