Structural Health Monitoring Using by Pawar Prashant (21 results)

Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Condition: New. In.

Paperback. Condition: New.

Condition: New.

Condition: New.

Condition: New. In.

Condition: New. The high profile of structural health monitoring (SHM) will add urgency to this detailed treatment of intelligent SHM development and implementation via the evolutionary system, which uses a genetic algorithm to automate the development of the fuzzy system. Num Pages: 132 pages, 25 black & white tables, biography. BIC Classification: TBJ; TNC; TNKX. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 18. Weight in Grams: 380. . 2011. Hardback. . . . .

Hardcover. Condition: Brand New. 138 pages. 9.25x6.25x0.75 inches. In Stock.

Hardcover. Condition: new. Hardcover. Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: SHM of beams; SHM of composite tubes; and SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condition: new. Paperback. Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: SHM of beams; SHM of composite tubes; and SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New.

Hardcover. Condition: Like New. Like New. book.

Paperback. Condition: Like New. Like New. book.

Condition: New. The high profile of structural health monitoring (SHM) will add urgency to this detailed treatment of intelligent SHM development and implementation via the evolutionary system, which uses a genetic algorithm to automate the development of the fuzzy system. Num Pages: 132 pages, 25 black & white tables, biography. BIC Classification: TBJ; TNC; TNKX. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 18. Weight in Grams: 380. . 2011. Hardback. . . . . Books ship from the US and Ireland.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: new. Paperback. Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: SHM of beams; SHM of composite tubes; and SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condition: new. Hardcover. Structural health monitoring (SHM) has emerged as a prominent research area in recent years owing to increasing concerns about structural safety, and the need to monitor and extend the lives of existing structures. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. The use of a genetic algorithm automates the development of the fuzzy system, and makes the method easy to use for problems involving a large number of measurements, damage locations and sizes; such problems being typical of SHM. The ideas behind fuzzy logic, genetic algorithms and genetic fuzzy systems are also explained. The functionality of the genetic fuzzy system architecture is elucidated within a case-study framework, covering: SHM of beams; SHM of composite tubes; and SHM of helicopter rotor blades. Structural Health Monitoring Using Genetic Fuzzy Systems will be useful for aerospace, civil and mechanical engineers working with structures and structured components. It will also be useful for computer scientists and applied mathematicians interested in the application of genetic fuzzy systems to engineering problems. Structural Health Monitoring Using Genetic Fuzzy Systems elaborates the process of intelligent SHM development and implementation using the evolutionary system. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Demonstrates the application of genetic fuzzy systems to engineering problems, which will be of interest to computer scientists and applied mathematicians Provides the reader with information on the use of genetic fuzzy systems as a computational .

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Demonstrates the application of genetic fuzzy systems to engineering problems, which will be of interest to computer scientists and applied mathematicians Provides the reader with information on the use of genetic fuzzy systems as a computational .