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006 m o d |
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008 200709s2020 si ob 000 0 eng d
020 _z9789811528361
020 _a9789811528378 (e-book)
035 _a(MiAaPQ)EBC6145527
035 _a(Au-PeEL)EBL6145527
035 _a(OCoLC)1150194958
040 _aMiAaPQ
_beng
_erda
_epn
_cMiAaPQ
_dMiAaPQ
050 4 _aTD159.4
_b.L58 2020
082 0 _a307.760285
_223
100 1 _aLiu, Hui,
_eauthor.
245 1 0 _aSmart cities :
_bbig data prediction methods and applications /
_cHui Liu.
264 1 _aSingapore :
_bSpringer ;
_aScience Press :
_bBeijing, China,
_c[2020]
264 4 _c�2020
300 _a1 online resource (338 pages)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references.
505 0 _aPart 1 Exordium -- 1. Key Issues of Smart Cities -- Part 2 Smart Grid and Buildings -- 2. Electrical Characteristics and Correlation Analysis in Smart Grid -- 3. Prediction Model of City Electricity Consumption -- 4. Prediction Models of Energy Consumption in Smart Urban Buildings -- Part 3 Smart Traffic Systems -- 5. Characteristics and Analysis of Urban Traffic Flow in Smart Traffic Systems -- 6. Prediction Model of Traffic Flow Driven Based on Single Data in Smart Traffic Systems -- 7. Prediction Models of Traffic Flow Driven Based on Multi-dimensional Data in Smart Traffic Systems -- Part 4 Smart Environment 8 Prediction Models of Urban Air Quality in Smart Environment -- 9. Prediction Models of Urban Hydrological Status in Smart Environment -- 10. Prediction Model of Urban Environmental Noise in Smart Environment.
520 _aSmart Cities: Big Data Prediction Methods and Applications is the first reference to provide a comprehensive overview of smart cities with the latest big data predicting techniques. This timely book discusses big data forecasting for smart cities. It introduces big data forecasting techniques for the key aspects (e.g., traffic, environment, building energy, green grid, etc.) of smart cities, and explores three key areas that can be improved using big data prediction: grid energy, road traffic networks and environmental health in smart cities. The big data prediction methods proposed in this book are highly significant in terms of the planning, construction, management, control and development of green and smart cities. Including numerous case studies to explain each method and model, this easy-to-understand book appeals to scientists, engineers, college students, postgraduates, teachers and managers from various fields of artificial intelligence, smart cities, smart grid, intelligent traffic systems, intelligent environments and big data computing.
588 _aDescription based on print version record.
590 _aElectronic reproduction. Ann Arbor, MI : ProQuest, 2018. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
650 0 _aSmart cities
_xForecasting.
650 0 _aArtificial intelligence.
650 0 _aBig data.
650 0 _aComputational intelligence.
650 0 _aMathematical Models of Cognitive Processes and Neural Networks.
655 4 _aElectronic books.
776 0 8 _iPrint version:
_aLiu, Hui.
_tSmart cities : big data prediction methods and applications.
_dSingapore : Springer ; Science Press : Beijing, China, c2020
_h338 pages
_z9789811528361
797 2 _aProQuest (Firm)
856 4 0 _uhttps://ebookcentral.proquest.com/lib/vajira-ebooks/detail.action?docID=6145527
_zClick to View
999 _c35191
_d35191
942 _cEBK
850 _aKCNL