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Sinopsis
India, which has the most agricultural tillage area in the world, is one of the massive cultivators of crops. Besides, rice and wheat is the main staple food of many Indians. The main purpose of this study is to develop a predictive model on Indian agriculture production. Here, we have used different types of soft computing models like Fuzzy Logic, Statistical Equations, Artificial Neural Network (ANN) and Genetic Algorithm (GA) and tried to develop a hybrid model to get the optimum result. The vital aspect of this proposed prediction model is to achieve improved accuracy. The Prediction performance has been assessed by using error finding equations like Mean Squared Error (MSE), Root Mean Square Error (RMSE) and Average Error.
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- EditorialLAP Lambert Academic Publishing
- Año de publicación2019
- ISBN 10 6200463344
- ISBN 13 9786200463340
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas60
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Soft Computing Techniques to Predict the Future of Indian Agriculture
Publicado por
LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200463344
ISBN 13: 9786200463340
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -India, which has the most agricultural tillage area in the world, is one of the massive cultivators of crops. Besides, rice and wheat is the main staple food of many Indians. The main purpose of this study is to develop a predictive model on Indian agriculture production. Here, we have used different types of soft computing models like Fuzzy Logic, Statistical Equations, Artificial Neural Network (ANN) and Genetic Algorithm (GA) and tried to develop a hybrid model to get the optimum result. The vital aspect of this proposed prediction model is to achieve improved accuracy. The Prediction performance has been assessed by using error finding equations like Mean Squared Error (MSE), Root Mean Square Error (RMSE) and Average Error. 60 pp. Englisch. Nº de ref. del artículo: 9786200463340
Cantidad disponible: 2 disponibles
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Soft Computing Techniques to Predict the Future of Indian Agriculture : MATLAB Coding
Publicado por
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200463344
ISBN 13: 9786200463340
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - India, which has the most agricultural tillage area in the world, is one of the massive cultivators of crops. Besides, rice and wheat is the main staple food of many Indians. The main purpose of this study is to develop a predictive model on Indian agriculture production. Here, we have used different types of soft computing models like Fuzzy Logic, Statistical Equations, Artificial Neural Network (ANN) and Genetic Algorithm (GA) and tried to develop a hybrid model to get the optimum result. The vital aspect of this proposed prediction model is to achieve improved accuracy. The Prediction performance has been assessed by using error finding equations like Mean Squared Error (MSE), Root Mean Square Error (RMSE) and Average Error. Nº de ref. del artículo: 9786200463340
Cantidad disponible: 1 disponibles
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Soft Computing Techniques to Predict the Future of Indian Agriculture
Publicado por
LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6200463344
ISBN 13: 9786200463340
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar SurjeetB.Tech (Computer Science), M.Tech(Computer Science), Pursuing Ph.D,University of KalyaniWest Bengal, IndiaIndia, which has the most agricultural tillage area in the world, is one of the massive cultivators of crops. . Nº de ref. del artículo: 497402146
Cantidad disponible: Más de 20 disponibles
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Soft Computing Techniques to Predict the Future of Indian Agriculture
Publicado por
LAP LAMBERT Academic Publishing Okt 2019, 2019
ISBN 10: 6200463344
ISBN 13: 9786200463340
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. Neuware -India, which has the most agricultural tillage area in the world, is one of the massive cultivators of crops. Besides, rice and wheat is the main staple food of many Indians. The main purpose of this study is to develop a predictive model on Indian agriculture production. Here, we have used different types of soft computing models like Fuzzy Logic, Statistical Equations, Artificial Neural Network (ANN) and Genetic Algorithm (GA) and tried to develop a hybrid model to get the optimum result. The vital aspect of this proposed prediction model is to achieve improved accuracy. The Prediction performance has been assessed by using error finding equations like Mean Squared Error (MSE), Root Mean Square Error (RMSE) and Average Error.Books on Demand GmbH, Überseering 33, 22297 Hamburg 60 pp. Englisch. Nº de ref. del artículo: 9786200463340
Cantidad disponible: 2 disponibles