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Zhidong Li

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuodelta 2025, suosituimpien joukossa Data Analytics for Smart Infrastructure. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

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Data Analytics for Smart Infrastructure

Data Analytics for Smart Infrastructure

Yang Wang; Zhidong Li; Bin Liang; Hongda Tian; Ting Guo; Fang Chen

TAYLOR FRANCIS LTD
2025
sidottu
This book presents, for the first time, data analytics for smart infrastructures. The authors draw on over a decade’s experience working with industry and demonstrating the capabilities of data analytics for infrastructure and asset management. The volume gives data-driven solutions to cover critical capabilities for infrastructure and asset management across three domains: 1) situation awareness 2) predictive analytics and 3) decision support. The reader will gain from various data analytic techniques including anomaly detection, performance evaluation, failure prediction, trend analysis, asset prioritization, smart sensing and real-time/online systems. These data analytic techniques are vital to solving problems in infrastructure and asset management. The reader will benefit from case studies drawn from critical infrastructures such as water management, structural health monitoring and rail networks. This groundbreaking work will be essential reading for those studying and practicing analytics in the context of smart infrastructure.
Data Analytics for Smart Infrastructure

Data Analytics for Smart Infrastructure

Yang Wang; Zhidong Li; Bin Liang; Hongda Tian; Ting Guo; Fang Chen

TAYLOR FRANCIS LTD
2025
nidottu
This book presents, for the first time, data analytics for smart infrastructures. The authors draw on over a decade’s experience working with industry and demonstrating the capabilities of data analytics for infrastructure and asset management. The volume gives data-driven solutions to cover critical capabilities for infrastructure and asset management across three domains: 1) situation awareness 2) predictive analytics and 3) decision support. The reader will gain from various data analytic techniques including anomaly detection, performance evaluation, failure prediction, trend analysis, asset prioritization, smart sensing and real-time/online systems. These data analytic techniques are vital to solving problems in infrastructure and asset management. The reader will benefit from case studies drawn from critical infrastructures such as water management, structural health monitoring and rail networks. This groundbreaking work will be essential reading for those studying and practicing analytics in the context of smart infrastructure.