Improving the Accuracy and Efficiency of PM2.5 Forecast Service Using Cluster-Based Hybrid Neural Network Model

Improving the Accuracy and Efficiency of PM2.5 Forecast Service Using Cluster-Based Hybrid Neural Network Model

Information and communication technologies have been widely used to achieve the objective of smart city development. A smart air quality sensing and forecasting system is an important part of a smart city. One of the major challenges in designing such a forecast system is ensuring high accuracy and...

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Bibliographic Details
Main Authors: Sachit Mahajan, Hao-Min Liu, Tzu-Chieh Tsai, Ling-Jyh Chen
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Internet of Things
forecasting
smart cities
neural networks
Online Access:https://ieeexplore.ieee.org/document/8327574/

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