Dabrowski, James MDe Villiers, Johan P2016-10-132016-10-132015-05Dabrowski, J.J. and De Villiers, J.P. 2015. Maritime piracy situation modelling with dynamic Bayesian networks. Information Fusion, 23, pp 116-1301566-2535http://www.sciencedirect.com/science/article/pii/S1566253514000840http://hdl.handle.net/10204/8820Copyright: 2015 Elsevier. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Information Fusion, 23, pp 116-130A generative model for modelling maritime vessel behaviour is proposed. The model is a novel variant of the dynamic Bayesian network (DBN). The proposed DBN is in the form of a switching linear dynamic system (SLDS) that has been extended into a larger DBN. The application of synthetic data fabrication of maritime vessel behaviour is considered. Behaviour of various vessels in a maritime piracy situation is simulated. A means to integrate information from context based external factors that influence behaviour is provided. Simulated observations of the vessels kinematic states are generated. The generated data may be used for the purpose of developing and evaluating counter-piracy methods and algorithms. A novel methodology for evaluating and optimising behavioural models such as the proposed model is presented. The log-likelihood, cross entropy, Bayes factor and the Bhattacharyya distance measures are applied for evaluation. The results demonstrate that the generative model is able to model both spatial and temporal datasetsenBehaviour modellingDynamic Bayesian networkSwitching linear dynamic systemContextual informationMulti-agent simulationArticleDabrowski, J. M., & De Villiers, J. P. (2015). Maritime piracy situation modelling with dynamic Bayesian networks. http://hdl.handle.net/10204/8820Dabrowski, James M, and Johan P De Villiers "Maritime piracy situation modelling with dynamic Bayesian networks." (2015) http://hdl.handle.net/10204/8820Dabrowski JM, De Villiers JP. Maritime piracy situation modelling with dynamic Bayesian networks. 2015; http://hdl.handle.net/10204/8820.TY - Article AU - Dabrowski, James M AU - De Villiers, Johan P AB - A generative model for modelling maritime vessel behaviour is proposed. The model is a novel variant of the dynamic Bayesian network (DBN). The proposed DBN is in the form of a switching linear dynamic system (SLDS) that has been extended into a larger DBN. The application of synthetic data fabrication of maritime vessel behaviour is considered. Behaviour of various vessels in a maritime piracy situation is simulated. A means to integrate information from context based external factors that influence behaviour is provided. Simulated observations of the vessels kinematic states are generated. The generated data may be used for the purpose of developing and evaluating counter-piracy methods and algorithms. A novel methodology for evaluating and optimising behavioural models such as the proposed model is presented. The log-likelihood, cross entropy, Bayes factor and the Bhattacharyya distance measures are applied for evaluation. The results demonstrate that the generative model is able to model both spatial and temporal datasets DA - 2015-05 DB - ResearchSpace DP - CSIR KW - Behaviour modelling KW - Dynamic Bayesian network KW - Switching linear dynamic system KW - Contextual information KW - Multi-agent simulation LK - https://researchspace.csir.co.za PY - 2015 SM - 1566-2535 T1 - Maritime piracy situation modelling with dynamic Bayesian networks TI - Maritime piracy situation modelling with dynamic Bayesian networks UR - http://hdl.handle.net/10204/8820 ER -