Fusion of expert knowledge with data using belief functions: a case study in waste-water treatment
Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) - Tập 2 - Trang 1613-1618 vol.2
Tóm tắt
This paper presents a methodology for combining expert knowledge with information from statistical data, in classification and prediction problems. The method is based on (1) a case-based approach allowing to predict a quantity of interest from past cases in the form of a belief function, (2) Bayesian networks for modelling expert knowledge and (3) a tuning mechanism allowing to optimally discount information sources by optimizing a performance criterion. This methodology is applied to the prediction of chemical oxygen demand solubility in waste-water The approach is expected to be useful in situations where both small databases and partial expert knowledge are available.
Từ khóa
#Computer aided software engineering #Wastewater treatment #Bayesian methods #Chemicals #Information resources #Predictive models #Optimization methods #Databases #UncertaintyTài liệu tham khảo
10.1109/5326.669565
vandegaag, 0, Probabilities for A Probabilistic Network A Case-study in Oesophageal Carcinoma
10.1016/0004-3702(90)90026-V
shafer, 1976, A Mathematical Theory Ofevidence, 10.1515/9780691214696
10.1016/0004-3702(94)90026-4
pearl, 1988, Probabilistic Reasoning in Intelligent Systems Networks of Plausible Inference
10.1016/S0888-613X(99)00027-4
jensen, 1996, An Introduction to Bayesian Networks
onisko, 2000, Learning bayesian networks parameters from small data sets: Application of noisy-or gates, Bayesian and Causal Networks From Inference to Data Mining' 12th European Conference on Artificial Intelligence
10.1016/S0165-0114(00)00086-5
10.1109/21.376493
charniak, 1991, Bayesian Networks Without Tears, 12, 50
henrion, 1987, Some practical issues in constructing belief networks, Uncertainty in Artificial Intelligence 3, 161
druzdzel, 0, Genie: A development environment for graphical decision-analytic models, Proceedings of the 1999Annual Symposium of the American Medical Informatics Association (AMIA-1999)
10.1109/TKDE.2000.868901
druzdzel, 1999, Knowledge engineering for very large decision-analytic medical models, Proceedings of the 1999 Annual Meeting of the American Medical Informatics Association, 10
druzdzel, 1996, Qualitative verbal explanations in bayesian belief networks, Al and Simulation of Behaviour Quarterly (Special Issue on Bayesian Belief Networks), 94, 43
elouedi, 2001, The evaluation of sensor's reliability and their tuning for multisensor data fusion within the transferable behef model, ECSQARU 2001, 305
druzdzel, 2000, Criteria for combining knowledge from different sources in probabilistic models, Working Notes of the UAI2000 Workshop on Domain Knowledge with Data for Decision Support