Case Matching Algorithm of Emergency Disposal Based on LS-SVM

被引：0

作者：

Gong, Xunan ^{[1
]}

Qi, Haoran ^{[2
]}

机构：

[1] Acad Mil Sci, Beijing, Peoples R China

[2] PLA, 31009 Troop, Beijing, Peoples R China

来源：

2022 INTERNATIONAL CONFERENCE ON VIRTUAL REALITY, HUMAN-COMPUTER INTERACTION AND ARTIFICIAL INTELLIGENCE, VRHCIAI | 2022年

关键词：

LS-SVM; Platt scaling; case matching; emergency disposal;

D O I：

10.1109/VRHCIAI57205.2022.00008

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the development of military intelligence technology, the personnel on duty usually need to complete the planning of emergency disposal in a very short time in the face of emergencies, so the demand for intelligent emergency disposal is extremely urgent. In this paper, the LS-SVM model is improved based on the Platt Scaling probability calibration model to solve the problem of unbalanced data distribution and probability calibration expansion of multi-generic output. A Calibration Probabilistic Least Squares Support Vector Machine (CPLS-SVM) classification algorithm was proposed. A case matching method of emergency disposal based on the CPLS-SVM algorithm is designed to improve the matching accuracy in a complex case sample environment. By constructing the LS-SVM based on calibration probability and applying it to the simulation data of the emergency disposal instance. The effectiveness and performance of the algorithm are verified by simulation.

引用

页码：7 / 11

页数：5

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