soft computing techniques predict von kumar surjeet (4 Ergebnisse)

Taschenbuch. Zustand: 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.

Zustand: 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. .

Taschenbuch. Zustand: 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.

Taschenbuch. Zustand: 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.