Tarun soni (22 resultados)

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Paperback. Condición: Brand New. 184 pages. Hindu language. 5.00x0.42x8.00 inches. In Stock.

Taschenbuch. Condición: Neu. Effectiveness of Neural Networks in Forecasting B.S.E Sensex Index | Tarun Soni | Taschenbuch | 60 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846555606 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. Neuware - A gay man tries to live his life on his own terms, struggling with his sexuality, passion and at the same time, balancing it with family, friends, society and culture, his life changes completely when he goes public with his sexuality.He did find peace in the end, but have to sacrifice all that he had.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Since stock markets are volatile, dynamic and complicated, forecasting stock market return is considered as a challenging task. Nevertheless, researchers have developed various linear and nonlinear methods for effective forecasting. Among these neural networks are most suitable for forecasting non linear and chaotic relationships among variables. The current study attempts to forecast the future returns of B.S.E, highly volatile index, with the help of conventional method i.e. ARIMA (Auto Regression Integrated Moving Average) and Artificial Neural Network M.L.P (Multilayer Perceptron).To examine the efficiency of the models, MAD (Mean Absolute Deviation) and MSE (Mean Square Error) of the two models are compared. The study results revealed that neural network is better for forecasting in comparison to ARIMA. 60 pp. Englisch.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Since stock markets are volatile, dynamic and complicated, forecasting stock market return is considered as a challenging task. Nevertheless, researchers have developed various linear and nonlinear methods for effective forecasting. Among these neural networks are most suitable for forecasting non linear and chaotic relationships among variables. The current study attempts to forecast the future returns of B.S.E, highly volatile index, with the help of conventional method i.e. ARIMA (Auto Regression Integrated Moving Average) and Artificial Neural Network M.L.P (Multilayer Perceptron).To examine the efficiency of the models, MAD (Mean Absolute Deviation) and MSE (Mean Square Error) of the two models are compared. The study results revealed that neural network is better for forecasting in comparison to ARIMA.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Soni TarunTarun Soni is a Doctoral Student, NIFM, An Autonomous body of Ministry of Finance, Faridabad. His areas of interest include artificial intelligence, market efficiency and commodity market volatility.Since stock markets .…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Soni ShaileshShailesh soni is a PG student at B.S.Patel pharmacy college,linch,Mehsana.Tarun patel is also PG student at B.S.Patel pharmacy,college,linch,Mehsana.Transdermal delivery offers several biomedical advantages over conv.…

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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Since stock markets are volatile, dynamic and complicated, forecasting stock market return is considered as a challenging task. Nevertheless, researchers have developed various linear and nonlinear methods for effective forecasting. Among these neural networks are most suitable for forecasting non linear and chaotic relationships among variables. The current study attempts to forecast the future returns of B.S.E, highly volatile index, with the help of conventional method i.e. ARIMA (Auto Regression Integrated Moving Average) and Artificial Neural Network M.L.P (Multilayer Perceptron).To examine the efficiency of the models, MAD (Mean Absolute Deviation) and MSE (Mean Square Error) of the two models are compared. The study results revealed that neural network is better for forecasting in comparison to ARIMA.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.…