Titlebook: Smart Cities: Big Data Prediction Methods and Applications; Hui Liu Book 2020 Springer Nature Singapore Pte Ltd. 2020 Smart Cities.Big Dat

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978-981-15-2839-2Springer Nature Singapore Pte Ltd. 2020

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Hui LiuBroadens readers‘ understanding of the smart cities.Describes in detail the latest theories and specific applications of smart time series prediction methods in smart cities, as well as a big data fra

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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..978-981-15-2839-2978-981-15-2837-8

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, and presents a wide range of applications to allow readers to understand the role of facility location in such areas and learn how to handle real-world location problems..The book is intend978-3-030-32179-6978-3-030-32177-2

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stic location problems..The book is intended for researchers working on theory and applications involving location problems and models. It is also suitable as a textbook for graduate courses on facility locatio978-3-319-34290-0978-3-319-13111-5

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Prediction Model of Traffic Flow Driven Based on Single Data in Smart Traffic Systemse WD-BP predictive model is higher than the BP predictive model in the deterministic forecast of traffic flow. In the interval prediction of traffic flow, BP neural network is used to establish a deterministic prediction model, and the GARCH model is used to calculate the uncertainty of forecasting

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Prediction Models of Urban Air Quality in Smart Environment compared and analyzed. The results show that the prediction of pollutant concentrations after effectively extracting the main characteristics of air pollution is feasible. On this basis, this chapter also puts forward the big data calculation framework of two air pollution prediction models as a re

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