In this book, the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for protection of distribution systems is introduced. The ANFIS can be viewed as a fuzzy system, a neural network or fuzzy neural network. The objective of this research is firstly, to detect the High Impendence Fault occurrence, secondly to classify the fault type and deduce if it is single line to ground, double lines to ground, triple lines to ground or line to line. Finally, locating the fault will be carried out to estimate the fault distance and hence to eliminate the fault and decrease the outage time. The Fault Detectors, Classifiers and Locators are firstly trained using ANFIS technique and then they are tested in diversity of system conditions with respect to the fault types, distance, supply voltage, inception instant, resistance, and pre-fault conditions.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
In this book, the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for protection of distribution systems is introduced. The ANFIS can be viewed as a fuzzy system, a neural network or fuzzy neural network. The objective of this research is firstly, to detect the High Impendence Fault occurrence, secondly to classify the fault type and deduce if it is single line to ground, double lines to ground, triple lines to ground or line to line. Finally, locating the fault will be carried out to estimate the fault distance and hence to eliminate the fault and decrease the outage time. The Fault Detectors, Classifiers and Locators are firstly trained using ANFIS technique and then they are tested in diversity of system conditions with respect to the fault types, distance, supply voltage, inception instant, resistance, and pre-fault conditions.
M. S. Abdel Aziz received the BSc, MSc and PhD degrees in Electrical Engineering from FECU and BU, Egypt, in 2008, 2011 and 2017 respectively. Now, he works as an electrical engineer in Dar Al-Handasah (Shair and Partners). M. A. Moustafa Hassan received the BSc, MSc and PhD from FECU, Egypt. Now, he works as Full Professor at FECU.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for protection of distribution systems is introduced. The ANFIS can be viewed as a fuzzy system, a neural network or fuzzy neural network. The objective of this research is firstly, to detect the High Impendence Fault occurrence, secondly to classify the fault type and deduce if it is single line to ground, double lines to ground, triple lines to ground or line to line. Finally, locating the fault will be carried out to estimate the fault distance and hence to eliminate the fault and decrease the outage time. The Fault Detectors, Classifiers and Locators are firstly trained using ANFIS technique and then they are tested in diversity of system conditions with respect to the fault types, distance, supply voltage, inception instant, resistance, and pre-fault conditions. 100 pp. Englisch. N° de réf. du vendeur 9786202065429
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abdel Aziz M. S.M. S. Abdel Aziz received the BSc, MSc and PhD degrees in Electrical Engineering from FECU and BU, Egypt, in 2008, 2011 and 2017 respectively. Now, he works as an electrical engineer in Dar Al-Handasah (Shair and Part. N° de réf. du vendeur 385924202
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for protection of distribution systems is introduced. The ANFIS can be viewed as a fuzzy system, a neural network or fuzzy neural network. The objective of this research is firstly, to detect the High Impendence Fault occurrence, secondly to classify the fault type and deduce if it is single line to ground, double lines to ground, triple lines to ground or line to line. Finally, locating the fault will be carried out to estimate the fault distance and hence to eliminate the fault and decrease the outage time. The Fault Detectors, Classifiers and Locators are firstly trained using ANFIS technique and then they are tested in diversity of system conditions with respect to the fault types, distance, supply voltage, inception instant, resistance, and pre-fault conditions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 100 pp. Englisch. N° de réf. du vendeur 9786202065429
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) for protection of distribution systems is introduced. The ANFIS can be viewed as a fuzzy system, a neural network or fuzzy neural network. The objective of this research is firstly, to detect the High Impendence Fault occurrence, secondly to classify the fault type and deduce if it is single line to ground, double lines to ground, triple lines to ground or line to line. Finally, locating the fault will be carried out to estimate the fault distance and hence to eliminate the fault and decrease the outage time. The Fault Detectors, Classifiers and Locators are firstly trained using ANFIS technique and then they are tested in diversity of system conditions with respect to the fault types, distance, supply voltage, inception instant, resistance, and pre-fault conditions. N° de réf. du vendeur 9786202065429
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Taschenbuch. Etat : Neu. An ANFIS Based Study for High Impedance Faults in Distribution Systems | M. S. Abdel Aziz (u. a.) | Taschenbuch | 100 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202065429 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 110489354
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