K-Prototype Clustering for the Person of Temporary Probation and Parole and Criminal Release Based on Rough Set

Li, Kangshun; Wang, Ziming; Fang, Hongming; Lei, Yishu

doi:10.1109/cis.2019.00083

Cited by 1 publication

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“…This study proposes the use of the K-prototype algorithm for clustering crashes on mountainous freeways. The K-prototype algorithm, first published by [24] , is a widely used ensemble clustering algorithm in various fields such as education [25] , sociology [26] , biology science [27] , and public safety [28] .…”

Section: Introductionmentioning

confidence: 99%

Crash data mining in mountainous freeway: a case study with K-prototype algorithm

Wang

2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

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To enhance the risk management strategies for crashes in mountainous freeways, this study conducted a data mining using the mountainous freeway in Fuzhou as an example. The K-prototype algorithm was used to cluster crash types into three categories with a SSE of 6450.049. The three categories reflects different crash characteristics, which can be used to implement different strategies. C1 represents crashes with high death rates, primarily occurring in confluence zones and tunnels during holidays with high traffic flow. C2 represents crashes with high injury rates, occurring on bridges, long downhill slopes, and diversion zones during evening peak hours. C3 represents crashes with low severity but long rescue response times. Different risk management strategies such as visual guidance devices and recommended speed reminders, were proposed for the three types of crashes mentioned above. The result also showed that more attention should be paid to the peak hours and holiday time in critical areas to minimize the influence of mountainous freeway crashes.

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Section: Introductionmentioning

confidence: 99%

Crash data mining in mountainous freeway: a case study with K-prototype algorithm

Wang

2024

Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024)

View full text Add to dashboard Cite

show abstract

K-Prototype Clustering for the Person of Temporary Probation and Parole and Criminal Release Based on Rough Set

Cited by 1 publication

References 4 publications

Crash data mining in mountainous freeway: a case study with K-prototype algorithm

Crash data mining in mountainous freeway: a case study with K-prototype algorithm

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