As the demand for materials continues to grow and the supply of natural resources continues to dwindle, a high degree of recycling of materials has become increasingly important. Recycling industries need to overcome the high cost of recycling and improve profitability by effective management of resources and management practices, using decision support models that are both quantitative and qualitative. However, models in present use emphasize mathematical procedures which are only good for analyzing quantitative decision variables and fail to take into consideration several relevant qualitative decision variables which can not be simply quantified. This book provides means of handling qualitative decision variables problems in profitability control using fuzzy logic and neural network tools to solve the lapses in other models. To reinforce the work, it is applied to a case study performed on a Paper recycling industry in Nigeria. Comparative analyses indicate that fuzzy-neural network offers a better correlation than the fuzzy logic components and should be useful in handling qualitative decision variable problems and should provide a better solution to the profitability control.
"Sinopsis" puede pertenecer a otra edición de este libro.
As the demand for materials continues to grow and the supply of natural resources continues to dwindle, a high degree of recycling of materials has become increasingly important. Recycling industries need to overcome the high cost of recycling and improve profitability by effective management of resources and management practices, using decision support models that are both quantitative and qualitative. However, models in present use emphasize mathematical procedures which are only good for analyzing quantitative decision variables and fail to take into consideration several relevant qualitative decision variables which can not be simply quantified. This book provides means of handling qualitative decision variables problems in profitability control using fuzzy logic and neural network tools to solve the lapses in other models. To reinforce the work, it is applied to a case study performed on a Paper recycling industry in Nigeria. Comparative analyses indicate that fuzzy-neural network offers a better correlation than the fuzzy logic components and should be useful in handling qualitative decision variable problems and should provide a better solution to the profitability control.
Umoh U. A. had received a Ph.D. degree in Soft Computing, MSc. degree in DBMS and BSc. degree. She is currently working as a Senior Lecturer, in the University of Uyo, Dept. of Computer Sc. She has published several quality articles and written some quality books in computer discipline. She is a member of CPN, NCS, NIWIT, OWSD, UACEE, SCRG, etc.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As the demand for materials continues to grow and the supply of natural resources continues to dwindle, a high degree of recycling of materials has become increasingly important. Recycling industries need to overcome the high cost of recycling and improve profitability by effective management of resources and management practices, using decision support models that are both quantitative and qualitative. However, models in present use emphasize mathematical procedures which are only good for analyzing quantitative decision variables and fail to take into consideration several relevant qualitative decision variables which can not be simply quantified. This book provides means of handling qualitative decision variables problems in profitability control using fuzzy logic and neural network tools to solve the lapses in other models. To reinforce the work, it is applied to a case study performed on a Paper recycling industry in Nigeria. Comparative analyses indicate that fuzzy-neural network offers a better correlation than the fuzzy logic components and should be useful in handling qualitative decision variable problems and should provide a better solution to the profitability control. 328 pp. Englisch. Nº de ref. del artículo: 9786202008662
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Umoh UduakUmoh U. A. had received a Ph.D. degree in Soft Computing, MSc. degree in DBMS and BSc. degree. She is currently working as a Senior Lecturer, in the University of Uyo, Dept. of Computer Sc. She has published several quality. Nº de ref. del artículo: 159930552
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Librería: Revaluation Books, Exeter, Reino Unido
Paperback. Condición: Brand New. 328 pages. 8.66x5.91x0.74 inches. In Stock. Nº de ref. del artículo: zk6202008660
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. Neuware -As the demand for materials continues to grow and the supply of natural resources continues to dwindle, a high degree of recycling of materials has become increasingly important. Recycling industries need to overcome the high cost of recycling and improve profitability by effective management of resources and management practices, using decision support models that are both quantitative and qualitative. However, models in present use emphasize mathematical procedures which are only good for analyzing quantitative decision variables and fail to take into consideration several relevant qualitative decision variables which can not be simply quantified. This book provides means of handling qualitative decision variables problems in profitability control using fuzzy logic and neural network tools to solve the lapses in other models. To reinforce the work, it is applied to a case study performed on a Paper recycling industry in Nigeria. Comparative analyses indicate that fuzzy-neural network offers a better correlation than the fuzzy logic components and should be useful in handling qualitative decision variable problems and should provide a better solution to the profitability control.Books on Demand GmbH, Überseering 33, 22297 Hamburg 328 pp. Englisch. Nº de ref. del artículo: 9786202008662
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. Fuzzy-Neural Network Models for Effective Control of Profitability | Uduak Umoh | Taschenbuch | 328 S. | Englisch | 2017 | LAP Lambert Academic Publishing | EAN 9786202008662 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 109605329
Cantidad disponible: 5 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As the demand for materials continues to grow and the supply of natural resources continues to dwindle, a high degree of recycling of materials has become increasingly important. Recycling industries need to overcome the high cost of recycling and improve profitability by effective management of resources and management practices, using decision support models that are both quantitative and qualitative. However, models in present use emphasize mathematical procedures which are only good for analyzing quantitative decision variables and fail to take into consideration several relevant qualitative decision variables which can not be simply quantified. This book provides means of handling qualitative decision variables problems in profitability control using fuzzy logic and neural network tools to solve the lapses in other models. To reinforce the work, it is applied to a case study performed on a Paper recycling industry in Nigeria. Comparative analyses indicate that fuzzy-neural network offers a better correlation than the fuzzy logic components and should be useful in handling qualitative decision variable problems and should provide a better solution to the profitability control. Nº de ref. del artículo: 9786202008662
Cantidad disponible: 1 disponibles