Sonja Petrovic-Lazarevic

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This paper explores the application of fuzzy causal networks (FCNs) to evaluating effect of health warnings in influencing Australian smokers' psychosocial and quitting behaviour. The sample data used in this study are selected from the International Tobacco Control Policy Evaluation Survey project. Our research findings have demonstrated that new health(More)
The aim of the paper is to demonstrate the neuro-fuzzy support of knowledge management in social regulation. Knowledge, defined as human capability of making data and information useful for decision making processes, could be understood for social regulation purposes as explicit and tacit. Explicit knowledge relates to the community culture indicating how(More)
This paper investigates the underlying patterns in data derived from the International Tobacco Control Four Country Survey. The intent of the paper is to determine which attributes have the greatest impact on smokers' plans to quit and their attempts to quit. Rule sets are derived using decision tree models and tested on temporal data sets to assess their(More)
Purpose – This paper aims to propose a novel computational framework called EvoPOL (EVOlving POLicies) to support governmental policy analysis in restricting recruitment of smokers. EvoPOL is a fuzzy inference-based decision support system that uses an evolutionary algorithm (EA) to optimize the if-then rules and its parameters. The performance of the(More)