Author: Au, Sze-wan Sandra
Title: Web-based spatial data mining on air pollution meteorology
Degree: M.Sc.
Year: 2000
Subject: Air -- Pollution -- China -- Hong Kong
Data mining -- China -- Hong Kong
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Department of Computing
Pages: 87, [66] p. : ill. (some col.), col. maps ; 31 cm
Language: English
Abstract: This paper applies spatial data mining and agent technologies to investigate the serious air pollution in Hong Kong. This project attempts to assess the air pollutants' concentration and meteorological information through routine collection of data from the Web in order to analyze the effects of different components. With the advance changes in Information Technologies, the impact of air pollution meteorological condition and air pollutants can be investigated by means of spatial data mining technologies. Besides, since most of the air pollution meteorological data is available on the Web, agent technology can be applied in this project. Spatial data mining can be used for discovering spatial relationships and relationships between spatial and non-spatial data and optimising spatial queries. Agent technology can be applied to control the communication between different parts of the system. A prototype will be constructed in this project in order to illustrate the feasibility of the spatial data mining and agent technologies applied in the investigation on air pollution meteorology. Besides, from the result of the prototype, the relationship between the air pollution meteorological data and air pollutants can be found.
Rights: All rights reserved
Access: restricted access

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