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Fuzzy Monte Carlo clustering for analysing the distribution of fishing vessels in the coastal waters of South Korea
- 언어ENG
- URLhttps://db.koreascholar.com/Article/Detail/435413
pp.26-33
The issue of marine accidents can be based on the traffic/distribution of vessels in the waterways. These accidents are often associated with human and financial losses and require special attention. Usually, these accidents include collision of two fishing vessels with each other, collision of a fishing vessel with other types of vessels in the course and collision of a fishing vessel with an obstacle in the course (Yancai, et al, 2020). In this article, we first want to deal with analysing the recorded statistical samples in 7 fishing areas in coastal waters of South Korea in 2023, while fuzzy clustering them. Then, according to analysing the sample data and finding the probabilistic structure and the membership of data sets the determined clusters, through Monte Carlo simulation, we will generate similar data in each of the 7 studied regions and model them in unsupervised mode. The generated data by Monte Carlo simulation based on the statistical distribution will able us to study the reality of distribution and possible accident in our target areas and find the model for future demands. We show that how the simulated data reduce the cost of data analysis and deliver us the facts of clusters for fishing vessels collisions. Finally, we reach to the most notified area for preventing the fishing vessels accidents and to make more preparations for reducing the human and costly damages in future activities.
2. Monte Carlo Simulation
2.1 Random Variables Simulation
4. Fuzzy Monte Carlo Algorithms
5. Fuzzy Clustering
5.1 FCM Algorithm for Data Clustering
5.2 Advantages of Fuzzy Clustering
6. Numerical Results for Fishing Vessels Distribution
7. Converging Fuzzy Monte Carlo Clusters
8. Conclusions
9. Acknowledgements
References
