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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shihab, K. |
| Copyright Year | 2005 |
| Description | Author affiliation: Dept. of Comput. Sci. & Math., Victoria Univ., Vic., Australia (Shihab, K.) |
| Abstract | Bayesian techniques are attractive and viable tools for modeling complex stochastic processes in general and the groundwater contamination process in particular. This is mainly because these techniques do not only emphasize the stochastic nature of this process but also the precision and the accuracy of the tested methods used by environmental laboratories. In this work, we describe the development and application of a prototype dynamic Bayesian network (DBN) that models groundwater quality in order to assess and predict the impact of pollutants on the water column. |
| Sponsorship | World Federation on Soft Comput. European Soc. for Fuzzy Logic and Technol. European Neural Network Soc. The Warsaw School of Social Psychology (SWPS) Polish Minist. of Sci. Res. and Inf. Technol |
| Starting Page | 73 |
| Ending Page | 78 |
| File Size | 224111 |
| Page Count | 6 |
| File Format | |
| ISBN | 0769522866 |
| DOI | 10.1109/ISDA.2005.65 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-09-08 |
| Publisher Place | Poland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bayesian methods Stochastic processes Predictive models Water pollution Pollution measurement Monitoring Water resources Contamination Chemicals Testing |
| Content Type | Text |
| Resource Type | Article |
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