9786137348406 - knowledge base reasoning based on artificial neural network: ishik university de mahdi, prof. dr. qaysar; hassan rasul, m.sc. safeen (6 resultados)
- Tapa blanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 89,06
Envío por EUR 11,70Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: Brand New. 104 pages. 8.66x5.91x0.24 inches. In Stock.
- Tapa blanda
Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 44,05
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Taschenbuch. Condición: Neu. Knowledge Base Reasoning based on Artificial Neural Network | Ishik University | Qaysar Mahdi (u. a.) | Taschenbuch | 104 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137348406 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mai…l[at]preigu[dot]de | Anbieter: preigu.
- Tapa blanda
- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,90
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The main aim of this book is to introduce the knowledge base reasoning using artificial intelligence in computer science. This book provides a proposed system that represents two important topics: a propositional logic and non-class…ical logic. Then represents them in artificial neural network so that to provide an easy way for reasoning and making a hybrid system. The first part of this work uses a Connectionist Inductive Learning and Logic Programming, (CILP) algorithm which is a method that translates a propositional logic to a three layers neural network. The second part of the book uses a Connectionist Modal Logic (CML) algorithm. This algorithm acts as an extension language added to a logic program to represent a non-classical logic program. This will add an ability to interconnect a number of possible words, stationeries, clusters, logic programs and so on to make representing of real world more accurate than poor propositional logic. The proposed system has been applied successfully on all tested logic programs. It proves that the neural network can represent logic language and have ability to reason rather than handling a missing data in absence of background knowledge. 104 pp. Englisch.
- Tapa blanda
- Impresión bajo demanda
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 41,71
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mahdi Prof. Dr. QaysarProf. Dr. Qaysar Mahdi supervised many PhD, MSc students in the field of communication, radar and computer engineering since 2000. His MSc and PhD were obtained in 1988 and 2002, r…espectively. He is now working .
- Tapa blanda
- Impresión bajo demanda
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,90
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The main aim of this book is to introduce the knowledge base reasoning using artificial intelligence in computer science. This book provides a proposed system that represents two important topics: a propositional logic and non-classical… logic. Then represents them in artificial neural network so that to provide an easy way for reasoning and making a hybrid system. The first part of this work uses a Connectionist Inductive Learning and Logic Programming, (CILP) algorithm which is a method that translates a propositional logic to a three layers neural network. The second part of the book uses a Connectionist Modal Logic (CML) algorithm. This algorithm acts as an extension language added to a logic program to represent a non-classical logic program. This will add an ability to interconnect a number of possible words, stationeries, clusters, logic programs and so on to make representing of real world more accurate than poor propositional logic. The proposed system has been applied successfully on all tested logic programs. It proves that the neural network can represent logic language and have ability to reason rather than handling a missing data in absence of background knowledge.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.
- Tapa blanda
- Impresión bajo demanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 50,50
Envío por EUR 60,87Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The main aim of this book is to introduce the knowledge base reasoning using artificial intelligence in computer science. This book provides a proposed system that represents two important topics: a propositional logic and non-classical…logic. Then represents them in artificial neural network so that to provide an easy way for reasoning and making a hybrid system. The first part of this work uses a Connectionist Inductive Learning and Logic Programming, (CILP) algorithm which is a method that translates a propositional logic to a three layers neural network. The second part of the book uses a Connectionist Modal Logic (CML) algorithm. This algorithm acts as an extension language added to a logic program to represent a non-classical logic program. This will add an ability to interconnect a number of possible words, stationeries, clusters, logic programs and so on to make representing of real world more accurate than poor propositional logic. The proposed system has been applied successfully on all tested logic programs. It proves that the neural network can represent logic language and have ability to reason rather than handling a missing data in absence of background knowledge.
