Inhaltsangabe
Dengue is one of the common infectious diseases which is caused by the dengue virus and transmitted to humans by mosquitoes with this many are infected in varied regions around the world per year. The reason for this virus is atmospheric conditions, which play a vital role in the outbreak of dengue. Therefore early prediction of dengue is the key to regulate outbreaks and reduces the transmission within the community. To overcome this we are using various machine learning (ML) algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest tree (RF), and Decision Tree (DT) are used to predict the dengue outbreak. Prediction is done based on weather parameters like monthly wise maximum temperature, minimum temperature, average temperature, mean temperature, humidity, and Precipitation which is considered as weather dataset and this weather dataset is pre-processed using label encoding function before applying into the training models. The performances of all the models are calculated based on weather datasets.
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Über die Autorin bzw. den Autor
Dr. Chalumuru Suresh, currently working as an Assistant Professor in the Department of CSE at VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad. Dr. Satish Thatavarthi, Currently Working as a Professor in the Department of CSE, Nadimpalli Satayanaryana Raju Institute of Technology, Sontyam, Vishakapatnam.
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Prediction of Epidemic Diseases Using Machine Learning Algorithms
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LAP LAMBERT Academic Publishing Sep 2020, 2020
ISBN 10: 3330008865
ISBN 13: 9783330008861
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Dengue is one of the common infectious diseases which is caused by the dengue virus and transmitted to humans by mosquitoes with this many are infected in varied regions around the world per year. The reason for this virus is atmospheric conditions, which play a vital role in the outbreak of dengue. Therefore early prediction of dengue is the key to regulate outbreaks and reduces the transmission within the community. To overcome this we are using various machine learning (ML) algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest tree (RF), and Decision Tree (DT) are used to predict the dengue outbreak. Prediction is done based on weather parameters like monthly wise maximum temperature, minimum temperature, average temperature, mean temperature, humidity, and Precipitation which is considered as weather dataset and this weather dataset is pre-processed using label encoding function before applying into the training models. The performances of all the models are calculated based on weather datasets. 68 pp. Englisch. Bestandsnummer des Verkäufers 9783330008861
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Prediction of Epidemic Diseases Using Machine Learning Algorithms
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Suresh ChalumuruDr. Chalumuru Suresh, currently working as an Assistant Professor in the Department of CSE at VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad. Dr. Satish Thatavarthi, Currently Working as a Profe. Bestandsnummer des Verkäufers 412817404
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Prediction of Epidemic Diseases Using Machine Learning Algorithms
Verlag:
LAP LAMBERT Academic Publishing Sep 2020, 2020
ISBN 10: 3330008865
ISBN 13: 9783330008861
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Dengue is one of the common infectious diseases which is caused by the dengue virus and transmitted to humans by mosquitoes with this many are infected in varied regions around the world per year. The reason for this virus is atmospheric conditions, which play a vital role in the outbreak of dengue. Therefore early prediction of dengue is the key to regulate outbreaks and reduces the transmission within the community. To overcome this we are using various machine learning (ML) algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest tree (RF), and Decision Tree (DT) are used to predict the dengue outbreak. Prediction is done based on weather parameters like monthly wise maximum temperature, minimum temperature, average temperature, mean temperature, humidity, and Precipitation which is considered as weather dataset and this weather dataset is pre-processed using label encoding function before applying into the training models. The performances of all the models are calculated based on weather datasets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch. Bestandsnummer des Verkäufers 9783330008861
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Prediction of Epidemic Diseases Using Machine Learning Algorithms : Machine Learning
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Dengue is one of the common infectious diseases which is caused by the dengue virus and transmitted to humans by mosquitoes with this many are infected in varied regions around the world per year. The reason for this virus is atmospheric conditions, which play a vital role in the outbreak of dengue. Therefore early prediction of dengue is the key to regulate outbreaks and reduces the transmission within the community. To overcome this we are using various machine learning (ML) algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest tree (RF), and Decision Tree (DT) are used to predict the dengue outbreak. Prediction is done based on weather parameters like monthly wise maximum temperature, minimum temperature, average temperature, mean temperature, humidity, and Precipitation which is considered as weather dataset and this weather dataset is pre-processed using label encoding function before applying into the training models. The performances of all the models are calculated based on weather datasets. Bestandsnummer des Verkäufers 9783330008861
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Prediction of Epidemic Diseases Using Machine Learning Algorithms : Machine Learning
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Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Dengue is one of the common infectious diseases which is caused by the dengue virus and transmitted to humans by mosquitoes with this many are infected in varied regions around the world per year. The reason for this virus is atmospheric conditions, which play a vital role in the outbreak of dengue. Therefore early prediction of dengue is the key to regulate outbreaks and reduces the transmission within the community. To overcome this we are using various machine learning (ML) algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest tree (RF), and Decision Tree (DT) are used to predict the dengue outbreak. Prediction is done based on weather parameters like monthly wise maximum temperature, minimum temperature, average temperature, mean temperature, humidity, and Precipitation which is considered as weather dataset and this weather dataset is pre-processed using label encoding function before applying into the training models. The performances of all the models are calculated based on weather datasets. Bestandsnummer des Verkäufers 37720918/1
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