Abstract
This paper focuses on a new approach of applying a pattern classification technique to ship routing plan. A safe path between a start point and a destination provides information about the space region partition. In the case of 2D routing plan, the route classifies the space into two districts. This means a dual problem of first classifying the entire space into two districts and then picking out the border as a route. We propose a novel approach to solve this dual problem based on support vector machine (SVM). SVM produces a non-linear separating surface on the basis of the margin maximization principle. This feature is applied to the objective of common routing plan problems, that is, generating a non-collision and smooth route. The effectiveness of the proposed approach is demonstrated by using several routing plan results in 2D spaces.
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Acknowledgements
This work was supported by the National Nature Science Foundation of China (Nos. 51579024, 61374114) and the Fundamental Research Funds for the Central Universities (DMU nos. 3132016311, 3132016005).
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Zhang, C., Guo, C. (2017). An Approach of Ship Routing Plan Based on Support Vector Machine. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2016. Communications in Computer and Information Science, vol 710. Springer, Singapore. https://doi.org/10.1007/978-981-10-5230-9_20
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DOI: https://doi.org/10.1007/978-981-10-5230-9_20
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