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Analysis of Ship Accidents in the Istanbul Strait Using Neuro-Fuzzy and Genetically Optimised Fuzzy Classifiers

Published online by Cambridge University Press:  14 September 2017

Sercan Erol ,
Mengü Demir ,
Bayram Çetişli  and
Ekrem Eyüboğlu
Sercan Erol*
Affiliation:
(Department of Maritime Transportation and Management, Karadeniz Technical University, TR)
Mengü Demir
Affiliation:
(Information Technology Department Directorate, Karadeniz Technical University, TR)
Bayram Çetişli
Affiliation:
(Electrical Electronics Engineer, Isparta, TR)
Ekrem Eyüboğlu
Affiliation:
(Department of Maritime Transportation and Management, Karadeniz Technical University, TR)
*
(E-mail: [email protected])
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Abstract

Marine accident analysis is important for ships passing through narrow, shallow and busy waterways. This study analyses the accidents which have occurred in the Istanbul Strait and proposes both quantitative and qualitative assessments of marine accidents. Marine accidents occurring in the Istanbul Strait are analysed by using a method based on neuro-fuzzy and genetically optimised fuzzy classifiers. It can be concluded that accident severity increases when poor weather conditions prevail in the Strait regardless of ship size. Therefore, solutions to reduce unwanted events should be prioritised by accounting for weather conditions and the capacity of the vessels. This analysis indicates that the safety level would be significantly improved if all the vessels follow the passage guidelines.

Keywords

Accident AnalysisIstanbul StraitAdaptive Neuro-Fuzzy ClassifierMaritime TransportationGenetically Optimized Fuzzy Classifier
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 2 , March 2018 , pp. 419 - 436
Copyright
Copyright © The Royal Institute of Navigation 2017 

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References

REFERENCES

Akten, N. (2004). Analysis of shipping casualties in the Bosphorus. Journal of Navigation, 57(3), 345–356.CrossRefGoogle Scholar
Arslan, O. and Turan, O. (2009). Analytical investigation of marine casualties at the Strait of Istanbul with SWOT–AHP method. Maritime Policy & Management, 36(2), 131–145.CrossRefGoogle Scholar
Aydogdu, Y.V., Yurtoren, C., Kum, S., Park, J.-S. (2010). Questionnaire survey on the risk perception in the Istanbul Strait. Journal of Navigation and Port Research, 34(7), 517–523, http://dx.doi.org/10.5394/KINPR.2010.34.7.517.CrossRefGoogle Scholar
Barnett, M.L. (2005). Searching for the root causes of maritime casualties - individual competence or organizational culture? WMU Journal of Maritime Affairs, 4(2), 131–145.CrossRefGoogle Scholar
Başar, E. (2010). Investigation into marine traffic and a risky area in the Turkish straits system: Çanakkale Strait, TRANSPORT, 25, 5–10.CrossRefGoogle Scholar
Başar, E. and Yıldırım, U. (2014). Effect of the oil areas on marine traffic and oil spill risks at the Black Sea. Journal of ETA Maritime Science, 2(2), 105–110.Google Scholar
Bishop, C.M. (1995). Neural networks for pattern recognition. Oxford University Press.CrossRefGoogle Scholar
Cetisli, B. (2010a). Development of an adaptive neuro-fuzzy classifier using linguistic hedges: Part 1, Expert Systems with Applications, 37(8), 6093–6101.CrossRefGoogle Scholar
Cetisli, B. (2010b). The effect of linguistic hedges on feature selection: Part 2. Expert Systems with Applications, 37(8), 6102–6108.CrossRefGoogle Scholar
Cetisli, B. and Barkana, A. (2010). Speeding up the scaled conjugate gradient algorithm and its application in neuro-fuzzy classifier training, Springer. Soft Computing, 14(4), 365–378.CrossRefGoogle Scholar
Cetisli, B. and Kalkan, H. (2014). A new deterministic validation method for classifier success: Give&Take, 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 345–348.CrossRefGoogle Scholar
Çelik, M. and Çebi, S. (2009). Analytical HFACS for investigating human errors in shipping accidents. Accident Analysis and Prevention, 41(1), 66–75.CrossRefGoogle ScholarPubMed
Ece, N.J. (2005). Investigation of accidents in Istanbul Strait, for safety of marine and pollution and determination of passage in safety condition. Doctorate Thesis, Gazi University.Google Scholar
Erol, S. and Başar, E. (2015). The analysis of ship accident occurred in Turkish search and rescue area by using decision tree. Maritime Policy & Management, 42(4), 377–388.CrossRefGoogle Scholar
Goerlandt, F. and Montewka, J. (2015). Maritime transportation risk analysis: Review and analysis in light of some foundational issues. Reliability Engineering and System Safety, 138, 115–134.CrossRefGoogle Scholar
Goerlandt, F., Montewka, J., Kuzmin, V. and Kujala, P. (2015). A risk-informed ship collision alert system: framework and application. Safety Science, 77, 182–204.CrossRefGoogle Scholar
Harrald, J., Mazzuchi, T., Merrick, J., van Dorp, R. and Spahn, J. (1998). Using system simulation to model the impact of human error in a maritime system. Safety Science, 30(1–2), 235–247.CrossRefGoogle Scholar
Hashemi, R.R., Le Blanc, L.A., Rucks, C.T. and Shearry, A. (1995). A neural network for transportation safety modelling, Expert Systems with Applications, 9(3), 247–256.CrossRefGoogle Scholar
Herrera, F. (2008). Genetic fuzzy systems: taxonomy, current research trends and prospects. Evolutionary Intelligence, 1, 27–46, DOI 10.1007/s12065-007-0001-5.CrossRefGoogle Scholar
Jang, J.S.R. (1993). ANFIS: Adaptive network based fuzzy inference systems. IEEE Transactions on Systems Man and Cybernetics, 23(3), 665–685.CrossRefGoogle Scholar
Jang, J.S.R., Sun, C.T. and Mizutani, E. (1997). Neuro-fuzzy and soft computing. Upper Saddle River: Prentice Hall.Google Scholar
Kristiansen, S. (2005). Maritime transportation safety management and risk analysis. Burlington, Biddles.Google Scholar
Kum, S., Furusho, M. and Iwasaki, H. (2008). Investigation on the factors of VTS operators’ mental workload: case of Turkish operators. International Maritime Lecturers Association 16th Conference, Izmir.Google Scholar
Küçükosmanoğlu, A. (2012). Maritime accidents forecast model for Bosphorus. Doctorate Thesis, Middle East Technical University.Google Scholar
Le Blanc, L.A., Hashemi, R.R. and Rucks, C.T. (2001). Pattern development for vessel accidents: a comparison of statistical and neural computing techniques. Expert Systems with Applications, 20, 163–171.CrossRefGoogle Scholar
Marine Traffic. (2016). Marine Traffic Istanbul Strait Traffic Density Map. http://www.marinetraffic.com/tr/ais/home/centerx:29/centery:41/zoom:8. Accessed 15 February 2016.Google Scholar
Martins, M.R. and Maturana, M.C. (2010). Human error contribution in collision and grounding of oil tankers. Risk Analysis, 30(4), 674-698, http://dx.doi.org/10.1111/j.1539-6924.2010.01392.x.CrossRefGoogle ScholarPubMed
McKnight, A.J., Becker, W.W., Pettit, A.J. and McKnight, A.S. (2007). Human error in recreational boating. Accident Analysis and Prevention, 39, 398–405.CrossRefGoogle ScholarPubMed
Mentes, A., Akyildiz, H., Yetkin, M. and Turkoglu, N. (2015). A FSA based fuzzy DEMATEL approach for risk assessment of cargo ships at coast and open seas of Turkey. Safety Science, 79, 1–10.CrossRefGoogle Scholar
Montreux Convention. (1936). Traduction - Translation Convention Regarding The Regime Of The Straits. Signed At Montreux, July 20th 1936.Google Scholar
MTRTS. (1998). Republic of Turkey, Ministry of Transport, Maritime Affairs and Communications, Maritime Traffic Regulations for the Turkish Straits.Google Scholar
Portela, R. de la C. (2005). Maritime casualty analysis as a tool to improve research about human factors on maritime environment. Journal of Maritime Research, 2(2), 3–18.Google Scholar
Poyraz, , Ö, . (1998). Coastal crisis management following vessel casualties and application of this in the Turkish Straits. Doctorate Thesis, Natural and Applied Sciences, Istanbul University.Google Scholar
Qu, X., Meng, Q. and Suyi, L. (2011). Ship collision risk assessment for the Singapore Strait. Accident Analysis and Prevention, 43, 2030–2036.CrossRefGoogle ScholarPubMed
Reason, J. T. (1997). Managing the risks of organizational accidents. Hants: Ashgate.Google Scholar
Takagi, T. and Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man, and Cybernetics, 15(1), 116–132.CrossRefGoogle Scholar
Trucco, P., Cagno, E., Ruggeri, F. and Grande, O. (2007). A Bayesian belief network modelling of organizational factor in risk analysis: A case study in maritime transportation. Reliability Engineering and System Safety, 93(6), 823–834.Google Scholar
Ucan, E. and Nas, S. (2016). Analysing Istanbul Strait Maritime Pilot Capacity by Simulation Technique. The Journal of Navigation, 69, 815–827. http://dx.doi:10.1017/S0373463315000909 CrossRefGoogle Scholar
Uğurlu, Ö., Erol, S. and Başar, E. (2015). The analysis of life safety and economic loss in marine accidents occurring in the Turkish Straits. Maritime Policy & Management, 43(3), 356–370. http://dx.doi.org/10.1080/03088839.2014.1000992.CrossRefGoogle Scholar
Uğurlu, Ö., Yıldırım, U. and Yüksekyıldız, E. (2013). Marine Accident Analysis with GIS. Journal of Shipping and Ocean Engineering, 3(12), 21–29.Google Scholar
Ulusçu, Ö.S., Özbaş, B., Altıok, T. and Or, İ. (2008). Risk analysis of transit vessel traffic in the strait of Istanbul. Modelling Technology Policy, Laboratory for Port Security.Google Scholar
Ulusçu, Ö.S., Özbaş, B., Altıok, T. and Or, İ. (2009). Risk analysis of the vessel traffic in the strait of Istanbul. Risk Analysis, 29(10), 1454–1472. http://dx.doi.org/10.1111/j.1539-6924.2009.01287.x CrossRefGoogle ScholarPubMed
Valdez Banda, O.A., Goerlandt, F., Montewka, J. and Kujala, P. (2015). A risk analysis of winter navigation in Finnish sea areas. Accident Analysis and Prevention, 79, 100–116.CrossRefGoogle ScholarPubMed
Wang, J., Pillay, A., Kwon, Y.S., Wall, A.D. and Loughran, C.G. (2005). An analysis of fishing vessel accidents. Accident Analysis and Prevention, 37(6), 1019–1024.CrossRefGoogle ScholarPubMed
Wang, L. Zeng, Y. and Chen, T. (2015). Back propagation neural network with adaptive differential evolution algorithm for time series forecasting, Expert Systems with Applications, 42(2), pp. 855–863.CrossRefGoogle Scholar
Wei, L., Hu, Z., Dong, L. and Zhao, W. (2015). A damage assessment model of oil spill accident combining historical data and satellite remote sensing information: A case study in Penglai 19-3 oil spill accident of China, Marine Pollution Bulletin, 91, pp. 258–271.CrossRefGoogle Scholar
Yazici, M.A. and Otay, E.N. (2009). A Navigation Safety Support Model for the Strait of Istanbul, The Journal of Navigation, 62, pp. 609–630, http://doi:10.1017/S0373463309990130 CrossRefGoogle Scholar
Yıldırım, U., Uğurlu, Ö. and Başar, E. (2015). Human error in grounding accidents: case study for container ships, Journal of ETA Maritime Science, 3(1), pp. 1–10, http://dx.doi.org/10.5505/jems.2015.57966 Google Scholar
Yurtören, C. (2004). Marine traffic management in Istanbul Strait, Doctorate Thesis, Kobe University.Google Scholar