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Ajouter au panierTaschenbuch. Etat : Neu. Wire-EDM process parameters and optimization | Umesh Kumar Vates | Taschenbuch | 292 S. | Englisch | 2018 | Scholars' Press | EAN 9786202305785 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Ajouter au panierPaperback. Etat : Brand New. 292 pages. 8.66x5.91x0.66 inches. In Stock.
Langue: anglais
Edité par Scholars' Press Jan 2018, 2018
ISBN 10 : 6202305789 ISBN 13 : 9786202305785
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present work is devoted to the development of ANN models for the analysis of the WEDM process applied to an actual industrial surface quality of components of mould and dies. Four layered structure (including two hidden layers, input and output layer) with back propagation for ANN model is selected and two fold cross-over data approach has been used to develop two different sets of models (S1 & S2) for each experimental set of material rods. Extensive computational results (predicted output values) have been obtained by using training, validation and testing programmed in 'MATLAB R2010a'. Prediction error statistics and correlations coefficient testing carried out between experimental and predicted outputs Ra as well as MRR to evaluate the best modeling result. The best among the proposed ANN models has been used to optimize the process parameter (Ra) with MRR by the effort of best input parametric combination. 292 pp. Englisch.
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vates Umesh KumarDr. Umesh Kumar VatesPhD, IIT Dhanbad, India.The present work is devoted to the development of ANN models for the analysis of the WEDM process applied to an actual industrial surface quality of components of moul.
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Ajouter au panierEtat : New. Print on Demand pp. 292.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. 292.
Langue: anglais
Edité par Scholars' Press Jan 2018, 2018
ISBN 10 : 6202305789 ISBN 13 : 9786202305785
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The present work is devoted to the development of ANN models for the analysis of the WEDM process applied to an actual industrial surface quality of components of mould and dies. Four layered structure (including two hidden layers, input and output layer) with back propagation for ANN model is selected and two fold cross-over data approach has been used to develop two different sets of models (S1 & S2) for each experimental set of material rods. Extensive computational results (predicted output values) have been obtained by using training, validation and testing programmed in 'MATLAB R2010a'. Prediction error statistics and correlations coefficient testing carried out between experimental and predicted outputs Ra as well as MRR to evaluate the best modeling result. The best among the proposed ANN models has been used to optimize the process parameter (Ra) with MRR by the effort of best input parametric combination.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 292 pp. Englisch.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The present work is devoted to the development of ANN models for the analysis of the WEDM process applied to an actual industrial surface quality of components of mould and dies. Four layered structure (including two hidden layers, input and output layer) with back propagation for ANN model is selected and two fold cross-over data approach has been used to develop two different sets of models (S1 & S2) for each experimental set of material rods. Extensive computational results (predicted output values) have been obtained by using training, validation and testing programmed in 'MATLAB R2010a'. Prediction error statistics and correlations coefficient testing carried out between experimental and predicted outputs Ra as well as MRR to evaluate the best modeling result. The best among the proposed ANN models has been used to optimize the process parameter (Ra) with MRR by the effort of best input parametric combination.