Sonja Petrovic-Lazarevic

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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)
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 academic literature suggests that the extent of exporting by multinational corporation subsidiaries (MCS) depends on their product manufactured, resources, tax protection, customers and markets, involvement strategy, financial independence and suppliers' relationship with a multinational corporation (MNC). The aim of this paper is to model the complex(More)
In this paper a neuro-fuzzy modelling is proposed to support knowledge management in social regulation. The neuro-fuzzy learning process is based on tacit knowledge in order to highlight what specific steps local government should undertake to reach the outcome with an increase in compliance. An example is given to demonstrate the validity of the approach.(More)