Published by LAP Lambert Academic Publishing, 2019
ISBN 10: 6139947170 ISBN 13: 9786139947171
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketPaperback. Condition: Brand New. 8.70x5.91x0.28 inches. In Stock.
Published by LAP LAMBERT Academic Publishing Jan 2019, 2019
ISBN 10: 6139947170 ISBN 13: 9786139947171
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
£ 24.20
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Add to basketTaschenbuch. Condition: Neu. Neuware -This book aims at researching the possibility of predicting the poverty risk threshold in France, considering the sustainable development indicators defined and registered by the European Union, and using a technique from the artificial intelligence field, i.e. artificial neural networks (ANNs). The main objective is to determine a more efficient economic method, which can be easily applied, in order to simulate the influence of sustainable development indicators on the poverty risk threshold, and to explore the possibility of predicting the latter. Thus, we could assess the poverty risk and establish policies and strategies in order to lower this risk, through actions that eliminate the causes of those sustainable development indicators which negatively influence the poverty risk threshold. The authors¿ research and contributions demonstrated the possibility of using the ANNs for modeling and simulation, in order to predict the poverty risk threshold in France, with results that can be used and applied in risk management.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch.
Published by LAP LAMBERT Academic Publishing Jan 2019, 2019
ISBN 10: 6139947170 ISBN 13: 9786139947171
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims at researching the possibility of predicting the poverty risk threshold in France, considering the sustainable development indicators defined and registered by the European Union, and using a technique from the artificial intelligence field, i.e. artificial neural networks (ANNs). The main objective is to determine a more efficient economic method, which can be easily applied, in order to simulate the influence of sustainable development indicators on the poverty risk threshold, and to explore the possibility of predicting the latter. Thus, we could assess the poverty risk and establish policies and strategies in order to lower this risk, through actions that eliminate the causes of those sustainable development indicators which negatively influence the poverty risk threshold. The authors' research and contributions demonstrated the possibility of using the ANNs for modeling and simulation, in order to predict the poverty risk threshold in France, with results that can be used and applied in risk management. 52 pp. Englisch.
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139947170 ISBN 13: 9786139947171
Language: English
Seller: moluna, Greven, Germany
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ilie ConstantinDr. Eng. Constantin Ilie obtained his Ph.D degree in Industrial Engineering in 2010. Since then he is working as Lecturer at OVIDIUS University from Constanta. He has a wide experience in international and local projec.
Published by LAP LAMBERT Academic Publishing, 2019
ISBN 10: 6139947170 ISBN 13: 9786139947171
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
£ 25.99
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims at researching the possibility of predicting the poverty risk threshold in France, considering the sustainable development indicators defined and registered by the European Union, and using a technique from the artificial intelligence field, i.e. artificial neural networks (ANNs). The main objective is to determine a more efficient economic method, which can be easily applied, in order to simulate the influence of sustainable development indicators on the poverty risk threshold, and to explore the possibility of predicting the latter. Thus, we could assess the poverty risk and establish policies and strategies in order to lower this risk, through actions that eliminate the causes of those sustainable development indicators which negatively influence the poverty risk threshold. The authors' research and contributions demonstrated the possibility of using the ANNs for modeling and simulation, in order to predict the poverty risk threshold in France, with results that can be used and applied in risk management.