Applied Research of Route Similarity Analysis Based on Association Rules

• Autorzy: Xiang Z. , Liu R. , Hu Q. , Shi C.
• Języki publikacji: EN

Abstrakty

EN

In recent years, with the development of information technology, businesses have accumulated a lot of useful historical data, as the shipping industry does. These data can be found deposited a large number of "knowledge", for example, Shipping records for historical information, Ship-Port relations information, Ship-ship relations information, Port & shipping route relations, Shipping route information. It can provide intellectual support to shipping informatization development. Association rules in data mining technology is one of important technologies. The technology, based on sta-tistical methods, can mine the associated and implied "knowledge" from data warehouse ,which has a large number of accumulated data. Apart from this, the technology can also play an important role in the prediction. In this paper, based on FP-growth algorithm, we improve it forming Relevent ships routes. From the prevalent perspective of data mining, deal with the corresponding vessels' dynamic information, ac-quired from the AIS, such as data collection, data statistics. On this basis, get the ship-port relation and ship-ship relation after a certain level of data analysis, processing, handing. Furthermore, this paper use the numer-ous historical ship-port relation and ship-ship relation to build a mathematical model on the ship-port and ship-ship relation. And use the improved association algorithm, FP-growth algorithm, to acquire the strong association rules between ship-port and ship-ship, and eventually mine the similarity of the ship route. Main points of this paper as follows: Collect ,count and check the data, which is from ship dynamic information; Establish the mathematical model between ship-port and ship-ship relation; Improve the algorithm; Analyse the similarity of ship route more accurately using the improved algorithm.

Słowa kluczowe

EN

collision avoidance; Route Analysis; Automatic Identification System (AIS); mathematical model

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2012
• Tom: Vol. 6, no. 2
• Strony: 181--185
• Opis fizyczny: Bibliogr. 6 poz., tab.

Twórcy

autor

Xiang Z.

• Merchant Marine College, Shanghai Maritime University, China

autor

Liu R.

• Merchant Marine College, Shanghai Maritime University, China

autor

Hu Q.

• Merchant Marine College, Shanghai Maritime University, China

autor

Shi C.

• Merchant Marine College, Shanghai Maritime University, China

Bibliografia

• [1] MA Xu-hui, Zhang A-hong. Association Rules Generated By the FP Tree Depth-First Algorithm. Computer Knowledge and Technology, 2010, 13: 058
• [2] HUI Liang, QIAN Xue-zhong. Non-check mining algo-rithm of maximum frequent patterns in association rules based on FP-tree. Journal of Computer Applications, 2010, 07: 064
• [3] YAN Wei, BAI Wen-yang, ZHANG Yan. Hiding Associa-tion Rules with FP-Tree Based Transaction Dataset Recon-strucion. Department of Computer Science and Technolo-gy, 2008
• [4] JI Xian-biao, SHAO Zhe-ping, PAN Jia-cai, et al. Devel-opment of distributed data collection system of AIS infor-mation and key techniques[J].Journal of Shanghai Maritime University, 2007, 28(3): 28-31
• [5] Lee C Y. An algorithm for path connections and its applica-tions. IRE Trans Electronic Computers, 1961, EC-10: 346-365
• [6] ZHANG Wen, TANG Xi-jin, YOSHIDA Taketoshi. AIS: An approach to Web information processing based on Web text mining. Systems Engineering-Theory & Practice, 2010, 01:015