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A sampling of topics: supply chain performance measurement using logical aggregation, a Bayesian belief network modeling of customer behavior on apparel coordination for fashion retailing business, consensus measures for symbolic data, cigarette sensory evaluation classifier predictive control algorithm, uncertainty aversion under distorted probability, and an agent-based approach to modeling small satellite constellations.
Their topics include evolutionary algorithms in the supervision of error-free control, soft computing techniques in spatial databases, fuzzy decision rule construction using fuzzy decision trees and its application to electronic-learning databases, opportunities for database technologies in a Bayesian belief network methodology for modeling social systems in virtual communities, checking integrity constraints in a distributed database, soft computing techniques in content-based multimedia information retrieval, feature selection and variable precision rough set analysis and its application to financial data, a human-machine interface design to control an intelligent rehabilitation robot system, and congestion control using soft computing.
A more recent study described a prototype Bayesian belief network for the diagnosis of acidification in Welsh rivers.
Bayesian networks are also called as Bayesian Belief Networks (BBN), Belief Nets, Causal Probabilistic Nets (CPN) (Charniak, 1991).
Multiple, competing models: Incorporates a wider variety of models, including: proprietary algorithms, CART, non-linear programming, Bayesian Belief Networks, etc.
Specific subjects examined include mining software repositories for traceability links, a hybrid program model for object-oriented reverse engineering, and using Bayesian belief networks to predict change propagation in software systems.
It is also found that Bayesian belief networks are more effective when compared to the other three considered methods for risk prediction.
A strategy based on Bayesian Belief Networks (BBNs) has proved most useful.