This research addresses these issues through the use of data mining. Specifically, this dissertation addresses two problems: upscaling models of solute transport in porous media and detecting anomalies in streaming environmental data.; Upscaling refers to the creation of models that do not need to ...
Despite the great potential of applying data mining methods to such complicated air pollution data, the appropriate methods remain premature and insufficient. The major aim of this chapter is to present some data mining methods, along with the real data, as a tool for analyzing the complex ...
The mineral resources in the Northwestern China are very abundant, and mining industry has become the important economic mainstay of the district The ecologic environmental background in the area is very poor, the predatory mine exploration in the recent 50 years makes it more serious The main en...
Chapter Twelve Data Mining for Environmental Systems Over recent years a huge library of data mining algorithms has been developed to tackle a variety of problems in fields such as medical imaging and network... K Gibert,J Spate,M Sànchez-Marrè,... - Elsevier Science & Technology 被引量: ...
The Data Mining for Environmental Sciences workshop series started inside iEMSs in 2006 and provides a valuable opportunity for close contact between KDD and Environmental community. After several editions of the workshop, possibilities of KDD for solving very complex environmental problems seems to be...
partners provides an exchange of the state of the art and future developments in the two key areas of this process: Computer Networking and Data Mining... S Boonkrong,H Unger,P Meesad 被引量: 19发表: 2014年 Development of a Data Mining Application for Huge Scale Earth Environmental Data...
In order to solve the incompatibility problem of assessment data indexes and to raise the precision of assessment model for urban environmental quality, a genetic projection pursuit interpolation data mining model (GPPIDMM) is presented for comprehensive assessment of urban environmental quality. In this...
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. Several available surveys capture STDM advances and report a wealth of important progress in this field. However, STDM challenges and problems are not thoroughly discussed and presented in art...
Traditional theories and methods for comprehensive environmental performance evaluation are challenged by the appearance of big data because of its large q
The economic and environmental performances of the swine farming industry have always resulted in heated discussions in developing countries. Exploring the relationship between these features and the producers' overall performance is the focus of this paper. For constructing multi-objective features that in...