From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS).
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Cherry Bhargava is working as Assistant Professor and Head VLSI domain, Lovely Professional University, India. She is an alumnus of Thapar University, Patiala and she has submitted PhD at IKG PTU, India. Pardeep Sharma is working as Assistant Professor at Lovely Professional University. Jaya is working with CSS Corp as a Network Engineer
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS). 84 pp. Englisch. Bestandsnummer des Verkäufers 9786139842995
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Bhargava CherryCherry Bhargava is working as Assistant Professor and Head VLSI domain, Lovely Professional University, India. She is an alumnus of Thapar University, Patiala and she has submitted PhD at IKG PTU, India. Pardeep Sharma. Bestandsnummer des Verkäufers 385873886
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS).VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 84 pp. Englisch. Bestandsnummer des Verkäufers 9786139842995
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - From daily life applications to military applications and from toys to satellites, the use of electronic components is in extensive. Due to rapid evolution of electronics device technology towards low cost and high performance, the electronics products become more complex, higher in density and speed, and lighter for easy portability. Reliability prediction of the electronic components used in industrial safety systems requires high accuracy and compatibility with the working environment. The user can replace faulty component with the accurate one, and system will be saved from complete shutdown. Using low-cost materials, carbon, and potash alum, a new solid composite electrolyte system was fabricated and characterized using various techniques. An Arrhenius behavior was reported when the temperature dependence of conductivity was analyzed. The synthesized solid composite electrolyte exhibited excellent humidity sensing behavior. An expert system was modeled using artificial intelligence techniques and failure of the sensor was predicted using artificial neural networks (ANN), fuzzy logic (FIS) an adaptive neuro-fuzzy inference system (ANFIS). Bestandsnummer des Verkäufers 9786139842995
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Taschenbuch. Zustand: Neu. Residual Life Estimation of a Fabricated Humidity Sensor Using AI | Alum-Carbon based humidity sensor: Its Fabrication and Residual Life Prediction using Artificial Intelligence Techniques | Cherry Bhargava (u. a.) | Taschenbuch | 84 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139842995 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 113883115
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