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001488190 020__ $$a9781000965582
001488190 020__ $$a1000965589
001488190 040__ $$aNhCcYBP$$cNhCcYBP
001488190 050_4 $$aTA1$$b.D383 2024
001488190 08204 $$a624.1710285
001488190 1001_ $$aNoori, Mohammad.
001488190 24510 $$aData driven methods for civil structural health monitoring and resilience :$$bLatest developments and applications.
001488190 260__ $$aMilton :$$bTaylor & Francis Group,$$c2023.
001488190 300__ $$a1 online resource (358 pages.)
001488190 336__ $$atext$$btxt$$2rdacontent
001488190 337__ $$acomputer$$bc$$2rdamedia
001488190 338__ $$aonline resource$$bcr$$2rdacarrier
001488190 4901_ $$aResilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems Series
001488190 5050_ $$aCover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Contents -- Foreword -- A Brief Overview of the Book by the Editors -- About the Editors -- List of Contributors -- Chapter 1: Structural Resilience through Structural Health Monitoring: A Critical Review -- Chapter 2: The Differential Evolution Algorithm: An Analysis of More than Two Decades of Application in Structural Damage Detection (2001-2022) -- Chapter 3: Fatigue Assessment and Structural Health Monitoring of Steel Truss Bridges -- Chapter 4: Sensor-Based Structural Assessment of Aging Bridges
001488190 5058_ $$aChapter 5: Pile Integrity Assessment through a Staged Data Interpretation Framework -- Chapter 6: Data-Centric Monitoring of Wind Farms: Combining Sources of Information -- Chapter 7: From Structural Health Monitoring to Finite Element Modeling of Heritage Structures: The Medieval Towers of Lucca -- Chapter 8: Development of an Adaptive Linear Quadratic Gaussian (LQG) Controller for Structural Control Using Particle Swarm Optimization -- Chapter 9: Application of AI Tools in Creating Datasets from a Real Data Component for Structural Health Monitoring
001488190 5058_ $$aChapter 10: Ambient Vibration Prediction of a Cable-Stayed Bridge by an Artificial Neural Network -- Chapter 11: Modeling Uncertainties by Data-Driven Bayesian Updating for Structural and Damage Detection -- Chapter 12: Image Processing for Structural Health Monitoring: The Resilience of Computer Vision-Based Monitoring Systems and Their Measurement -- Chapter 13: Automatic Structural Health Monitoring of Road Surfaces Using Artificial Intelligence and Deep Learning
001488190 5058_ $$aChapter 14: Computer Vision-Based Intelligent Disaster Mitigation from Two Aspects of Structural System Identification and Local Damage Detection -- Index
001488190 506__ $$aAccess limited to authorized users
001488190 533__ $$aElectronic reproduction.$$bAnn Arbor, MI$$nAvailable via World Wide Web.
001488190 588__ $$aDescription based on print version record.
001488190 650_0 $$aCivil engineering$$vPeriodicals.$$vHandbooks, manuals, etc.$$0(DLC)sh2008100894
001488190 650_0 $$aEngineering$$vPeriodicals.
001488190 655_0 $$aElectronic books
001488190 7001_ $$aRainieri, Carlo.
001488190 7001_ $$aDomaneschi, Marco.
001488190 7001_ $$aSarhosis, Vasilis.
001488190 7102_ $$aProQuest (Firm)
001488190 77608 $$iPrint version:$$aNoori, Mohammad$$tData Driven Methods for Civil Structural Health Monitoring and Resilience$$dMilton : Taylor & Francis Group,c2023$$z9781032308388
001488190 830_0 $$aResilience and Sustainability in Civil, Mechanical, Aerospace and Manufacturing Engineering Systems Series.
001488190 852__ $$bebk
001488190 85640 $$3GOBI DDA$$uhttps://univsouthin.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/usiricelib-ebooks/detail.action?docID=30738832$$zOnline Access
001488190 909CO $$ooai:library.usi.edu:1488190$$pGLOBAL_SET
001488190 980__ $$aBIB
001488190 980__ $$aEBOOK
001488190 982__ $$aEbook
001488190 983__ $$aOnline