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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Prediction Models of Traffic Flow Driven Based on Multi-Dimensional Data in Smart Traffic Systems the traffic flow prediction performance of the WPD-Elman model using multi-dimensional data is the best. When building a traffic flow prediction model, the wavelet packet algorithm can effectively improve the accuracy of the model.

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Prediction Model of Urban Environmental Noise in Smart Environment, traffic noise, and neighborhood noise. Through comprehensive comparative analysis of the experimental results, it can be concluded that the noise prediction performance of the BFGS model is the best in this experiment. Neighborhood noise is the most predictable among the three types of noise data.

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Key Issues of Smart Cities be the future direction of the development of cities. This chapter is the general chapter of the book. In the chapter, the big data forecasting technology is used as the basic point to elaborate and analyze from the aspects of smart grid and buildings, smart traffic, and smart environment. In each

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Electrical Characteristics and Correlation Analysis in Smart Grid kinds of data is also very complex. How to extract effective data sources from massive data, simplify the identification process, and effectively improve the accuracy of data processing is a necessary way to realize power grid intelligence. In this chapter, taking the air-conditioning circuit syste

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