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Maritime Policy & Management
The flagship journal of international shipping and port research
Volume 46, 2019 - Issue 4
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Articles

ANFIS model for assessing near-miss risk during tanker shipping voyages

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References

  • Ahn, J. H., K. P. Rhee, and Y. J. You. 2012. “A Study on the Collision Avoidance of A Ship Using Neural Networks and Fuzzy Logic.” Applied Ocean Research 37: 162–173. doi:10.1016/j.apor.2012.05.008.
  • (ABS) American Bureau of Shipping. 2005. “Guidance Notes on the Investigation of Marine Incidents.”
  • Ansari, T., M. Kumar, A. Shukla, J. Dhar, and R. Tiwari. 2010. “Sequential Combination of Statistics, Econometrics and Adaptive Neural-Fuzzy Interface for Stock Market Prediction.” Expert Systems with Applications 37 (7): 5116–5125. doi:10.1016/j.eswa.2009.12.083.
  • Boyacioglu, M. A., and D. Avci. 2010. “An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the Prediction of Stock Market Return: The Case of the Istanbul Stock Exchange.” Expert Systems with Applications 37 (12): 7908–7912. doi:10.1016/j.eswa.2010.04.045.
  • Brown, M., and C. J. Harris. 1994. Neuro Fuzzy Adaptive Modelling and Control. New Jersey: Prentice Hall.
  • Buragohain, M., and C. Mahanta. 2008. “A Novel Approach for ANFIS Modelling Based on Full Factorial Design.” Applied Soft Computing 8 (1): 609–625. doi:10.1016/j.asoc.2007.03.010.
  • Chang, F. J., and Y. T. Chang. 2006. “Adaptive Neuro-Fuzzy Inference System for Prediction of Water Level in Reservoir.” Advances in Water Resources 29 (1): 1–10. doi:10.1016/j.advwatres.2005.04.015.
  • Ciarapica, F. E., and G. Giacchetta. 2009. “Classification and Prediction of Occupational Injury Risk Using Soft Computing Techniques: An Italian Study.” Safety Science 47 (1): 36–49. doi:10.1016/j.ssci.2008.01.006.
  • Firat, M., and M. Güngör. 2007. “River Flow Estimation Using Adaptive Neuro Fuzzy Inference System.” Mathematics and Computers in Simulation 75 (3): 87–96. doi:10.1016/j.matcom.2006.09.003.
  • Fragiadakis, N. G., V. D. Tsoukalas, and V. J. Papazoglou. 2014. “An Adaptive Neuro-Fuzzy Inference System (ANFIS) Model for Assessing Occupational Risk in the Shipbuilding Industry.” Safety Science 63: 226–235. doi:10.1016/j.ssci.2013.11.013.
  • Hänninen, M., and P. Kujala. 2014. “Bayesian Network Modelling of Port State Control Inspection Findings and Ship Accident Involvement.” Expert Systems with Applications 41 (4): 1632–1646. doi:10.1016/j.eswa.2013.08.060.
  • Heij, C., and S. Knapp. 2018. “Predictive Power of Inspection Outcomes for Future Shipping Accidents–An Empirical Appraisal with Special Attention for Human Factor Aspects.” Maritime Policy & Management 45 (5): 604–621. doi:10.1080/03088839.2018.1440441.
  • Ho, W. H., J. T. Tsai, B. T. Lin, and J. H. Chou. 2009. “Adaptive Network-Based Fuzzy Inference System for Prediction of Surface Roughness in End Milling Process Using Hybrid Taguchi-Genetic Learning Algorithm.” Expert Systems with Applications 36 (2): 3216–3222. doi:10.1016/j.eswa.2008.01.051.
  • IMO. 2008. Guidance on Near-Miss Reporting. International Maritime Organization, London, UK.
  • Jang, J. S. R. 1996. “Input Selection for ANFIS Learning.” In Proceedings of the Fifth IEEE International Conference on Fuzzy Systems, 1493–1499. New Orleans, September. doi: 10.1109/FUZZY.1996.552396
  • Jang, J. S. R., and C. T. Sun. 1993. “Functional Equivalence between Radial Basis Function Networks and Fuzzy Inference Systems.” IEEE Transactions on Neural Networks 4 (1): 156–159. doi:10.1109/72.182710.
  • Karahalios, H. 2017. “Evaluating the Knowledge of Experts in the Maritime Regulatory Field.” Maritime Policy & Management 44 (4): 426–441. doi:10.1080/03088839.2017.1298865.
  • Kasabov, N. K., and Q. Song. 2002. “DENFIS: Dynamic Evolving Neural-Fuzzy Inference System and Its Application for Time-Series Prediction.” IEEE Transactions on Fuzzy Systems 10 (2): 144–154. doi:10.1109/91.995117.
  • Köhler, F. 2010. “Barriers to near-miss reporting in the maritime domain.” Master diss., Linköping University.
  • Kujala, P., M. Hänninen, T. Arola, and J. Ylitalo. 2009. “Analysis of the Marine Traffic Safety in the Gulf of Finland.” Reliability Engineering & System Safety 94 (8): 1349–1357. doi:10.1016/j.ress.2009.02.028.
  • Li, S., Q. Meng, and X. Qu. 2012. “An Overview of Maritime Waterway Quantitative Risk Assessment Models.” Risk Analysis 32 (3): 496–512. doi:10.1111/j.1539-6924.2011.01697.x.
  • Lo, S. P. 2003. “An Adaptive-Network Based Fuzzy Inference System for Prediction of Workpiece Surface Roughness in End Milling.” Journal of Materials Processing Technology 142 (3): 665–675. doi:10.1016/S0924-0136(03)00687-3.
  • Luo, M., S.-H. Shin, and Y.-T. Chang. 2017. “Duration Analysis for Recurrent Ship Accidents.” Maritime Policy & Management 44 (5): 603–622. doi:10.1080/03088839.2017.1319983.
  • Mazaheri, A., J. Montewka, and P. Kujala. 2014. “Modeling the Risk of Ship Grounding—A Literature Review from a Risk Management Perspective.” WMU Journal of Maritime Affairs 13 (2): 269–297. doi:10.1007/s13437-013-0056-3.
  • Mekanik, F., M. A. Imteaz, and A. Talei. 2015. “Seasonal Rainfall Forecasting by Adaptive Network-Based Fuzzy Inference System (ANFIS) Using Large Scale Climate Signals.” Climate Dynamics 1–15. doi:10.1007/s00382-015-2755-2.
  • Mullai, A., and U. Paulsson. 2011. “A Grounded Theory Model for Analysis of Marine Accidents.” Accident Analysis & Prevention 43 (4): 1590–1603. doi:10.1016/j.aap.2011.03.022.
  • Oltedal, H. A., and D. P. McArthur. 2011. “Reporting Practices in Merchant Shipping, and the Identification of Influencing Factors.” Safety Science 49 (2): 331–338. doi:10.1016/j.ssci.2010.09.011.
  • Ozbas, B. 2013. “Safety Risk Analysis of Maritime Transportation: Review of the Literature.” Transportation Research Record: Journal of the Transportation Research Board 2326 (1): 32–38. doi:10.3141/2326-05.
  • Razani, M., A. Yazdani-Chamzini, and S. H. Yakhchali. 2013. “A Novel Fuzzy Inference System for Predicting Roof Fall Rate in Underground Coal Mines.” Safety Science 55: 26–33. doi:10.1016/j.ssci.2012.11.008.
  • Storgård, J., I. Erdogan, J. Lappalainen, and U. Tapaninen. 2012. “Developing Incident and near Miss Reporting in the Maritime Industry–A Case Study on the Baltic Sea.” Procedia-Social and Behavioral Sciences 48: 1010–1021. doi:10.1016/j.sbspro.2012.06.1078.
  • Sugeno, M., and G. T. Kang. 1988. “Structure Identification of Fuzzy Model.” Fuzzy Sets and Systems 28 (1): 15–33. doi:10.1016/0165-0114(88)90113-3.
  • Sun, C. T. 1994. “Rule-Base Structure Identification in an Adaptive-Network-Based Fuzzy Inference System.” IEEE Transactions on Fuzzy Systems 2 (1): 64–73. doi:10.1109/91.273127.
  • Svalina, I., V. Galzina, R. Lujić, and G. Šimunović. 2013. “An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the Forecasting: The Case of Close Price Indices.” Expert Systems with Applications 40 (15): 6055–6063. doi:10.1016/j.eswa.2013.05.029.
  • Takagi, T., and M. Sugeno. 1983. “Derivation of Fuzzy Control Rules from Human Operator’s Control Actions.” IFAC Proceedings Volumes 16 (13): 55–60. doi:10.1016/S1474-6670(17)62005-6.
  • Takagi, T., and M. Sugeno. 1985. “Fuzzy Identification of Systems and Its Applications to Modelling and Control.” IEEE Transactions on Systems, Man, and Cybernetics SMC-15 (1): 116–132. doi:10.1109/TSMC.1985.6313399
  • Tan, Z., C. Quek, and P. Y. Cheng. 2011. “Stock Trading with Cycles: A Financial Application of ANFIS and Reinforcement Learning.” Expert Systems with Applications 38 (5): 4741–4755. doi:10.1016/j.eswa.2010.09.001.
  • Tsoukalas, V. D., and N. G. Fragiadakis. 2016. “Prediction of Occupational Risk in the Shipbuilding Industry Using Multivariable Linear Regression and Genetic Algorithm Analysis.” Safety Science 83: 12–22. doi:10.1016/j.ssci.2015.11.010.
  • Uğurlu, Ö., S. Kum, and Y. V. Aydoğdu. 2017. “Analysis of Occupational Accidents Encountered by Deck Cadets in Maritime Transportation.” Maritime Policy & Management 44 (3): 304–322. doi:10.1080/03088839.2016.1245449.
  • Ying, L.-C., and M.-C. Pan. 2008. “Using Adaptive Network Based Fuzzy Inference System to Forecast Regional Electricity Loads.” Energy Conversion and Management 49 (2): 205–211. doi:10.1016/j.enconman.2007.06.015.
  • Zhang, D., X. P. Yan, Z. L. Yang, A. Wall, and J. Wang. 2013. “Incorporation of Formal Safety Assessment and Bayesian Network in Navigational Risk Estimation of the Yangtze River.” Reliability Engineering & System Safety 118: 93–105. doi:10.1016/j.ress.2013.04.006.
  • Zhou, Q., and V. V. Thai. 2015. “Application of Data-Mining Techniques for Personal Injury Evaluation in Tanker Shipping Industry.” International Journal of Computing, Communication & Instrumentation 2 (2): 185–190.

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