Robotics & Machine Learning Daily News2024,Issue(Nov.26) :47-48.

Research from Shandong Jiaotong University Reveals New Findings on Support Vecto r Machines (Vehicle Lane Changing Game Model Based on Improved SVM Algorithm)

山东交通大学的研究揭示了支持向量机的新发现(基于改进SVM算法的车辆换道博弈模型)

Robotics & Machine Learning Daily News2024,Issue(Nov.26) :47-48.

Research from Shandong Jiaotong University Reveals New Findings on Support Vecto r Machines (Vehicle Lane Changing Game Model Based on Improved SVM Algorithm)

山东交通大学的研究揭示了支持向量机的新发现(基于改进SVM算法的车辆换道博弈模型)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑新闻-调查人员在讨论新发现。据来自济南的新闻报道,中华民国,由NewsRx通讯员所作的研究指出,“为了改进自治制度。”本文旨在解决无人机换道精度不高的问题传统支持向量机(SVM)算法在换道中的决策分类智能驾驶车辆的决策阶段》。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators discuss new findings in . According to news reporting originating from Jinan, People’sRepublic of China, by NewsRx correspondents, research stated, “In order to improve the autonomouslane-chang ing performance of unmanned vehicles, this paper aims to solve the problem of in accuratedecision classification in traditional support vector machine (SVM) alg orithms applied to the lane-changingdecision-making stage of intelligent drivin g vehicles.”

Key words

Shandong Jiaotong University/Jinan/Peo ple’s Republic of China/Asia/Algorithms/Emerging Technologies/Machine Learni ng/Support Vector Machines/Vector Machines

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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