efficient algorithm large scale rfid von hasnan khalid (8 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware -Radio Frequency Identification (RFID) technology as a new inventory tracking technology has achieved significant development in many practical industrial scenarios, where much great application potential has been realized and many are being explored. In many real-world RIFD applications, such as production, logistics, and supply chain management, more and more readers are deployed to provide complete coverage of all the tags in the given area. Large-scale radio frequency identification (RFID) network planning (RNP) problem has been proven to be an NP-hard issue, which can be formulated as a high dimensional nonlinear optimization problem with a mixture of discrete and continuous variables and uncertain parameters. In the RFID system, the optimization technique was very helpful in solving problems of large search spaces, high complexity, searching ill-structured spaces. For this reason, nature-inspired algorithms applied in this area. In the past two decades, evolutionary computation (EC) and swarm intelligence (SI) techniques for solving RNP problems have gained increasing attention, such as particle swarm optimization algorithms (PSO), Firefly algorithm (FA), and Cuckoo Search.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Radio Frequency Identification (RFID) technology as a new inventory tracking technology has achieved significant development in many practical industrial scenarios, where much great application potential has been realized and many are being explored. In many real-world RIFD applications, such as production, logistics, and supply chain management, more and more readers are deployed to provide complete coverage of all the tags in the given area. Large-scale radio frequency identification (RFID) network planning (RNP) problem has been proven to be an NP-hard issue, which can be formulated as a high dimensional nonlinear optimization problem with a mixture of discrete and continuous variables and uncertain parameters. In the RFID system, the optimization technique was very helpful in solving problems of large search spaces, high complexity, searching ill-structured spaces. For this reason, nature-inspired algorithms applied in this area. In the past two decades, evolutionary computation (EC) and swarm intelligence (SI) techniques for solving RNP problems have gained increasing attention, such as particle swarm optimization algorithms (PSO), Firefly algorithm (FA), and Cuckoo Search. 56 pp. Englisch.

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Radio Frequency Identification (RFID) technology as a new inventory tracking technology has achieved significant development in many practical industrial scenarios, where much great application potential has been realized and many are being explored. In many real-world RIFD applications, such as production, logistics, and supply chain management, more and more readers are deployed to provide complete coverage of all the tags in the given area. Large-scale radio frequency identification (RFID) network planning (RNP) problem has been proven to be an NP-hard issue, which can be formulated as a high dimensional nonlinear optimization problem with a mixture of discrete and continuous variables and uncertain parameters. In the RFID system, the optimization technique was very helpful in solving problems of large search spaces, high complexity, searching ill-structured spaces. For this reason, nature-inspired algorithms applied in this area. In the past two decades, evolutionary computation (EC) and swarm intelligence (SI) techniques for solving RNP problems have gained increasing attention, such as particle swarm optimization algorithms (PSO), Firefly algorithm (FA), and Cuckoo Search.

Taschenbuch. Zustand: Neu. An efficient algorithm for large-scale RFID Network Planning | Khalid Bin Hasnan (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202682503 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.