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

大雨

Characteristics and Analysis of Urban Traffic Flow in Smart Traffic Systemsto solve traffic congestion. The problem studied in this chapter is to establish a vehicle trajectory prediction model based on vehicle historical trajectory data. The research idea is to use machine learning algorithms and neural network algorithms to predict future trajectories after pre-processin

Eosinophils

小木槌

Prediction Models of Traffic Flow Driven Based on Multi-Dimensional Data in Smart Traffic Systemsjacent road sections will affect the future traffic flow of the target road section. Therefore, this chapter uses the traffic changes of adjacent road sections and the traffic changes of the target road sections to build multi-dimensional datasets. Based on different model frameworks, four traffic f

骯臟

outset

Prediction Models of Urban Hydrological Status in Smart Environmenthe intelligent embodiment of the intelligent city. In addition to paying attention to its fluctuation state, the river water level is also very important for the accurate prediction of water level height in the future. For this reason, this chapter first constructs the prediction model of water leve

檔案

Foolproof

GIDDY

Prediction Models of Energy Consumption in Smart Urban Buildingsaset in the simulation results of DeST software, and an intelligent prediction method for energy consumption of a building in Changsha is proposed. Similarly, the big data computing framework is constructed according to the proposed prediction model to provide support for the design and operation of intelligent buildings in smart cities.

兇猛

內(nèi)閣

Book 2020t 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 u