An efficient safest route prediction-based route discovery mechanism for drivers using improved golden tortoise beetle optimizer

IF 1.7 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-04-25 DOI:10.1080/0952813x.2024.2343736

A. Vijaya Lakshmi, A. Parthiban, K. Suresh Joseph

引用次数: 0

Abstract

Several commercialised route recommendation systems only consider the metrics like cost, time, and distance. The essential metric ‘safety’ is neglected by the existent systems. It suggests only the...

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使用改进的金龟甲虫优化器，为驾驶员提供基于最安全路线预测的高效路线发现机制

一些商业化的路线推荐系统只考虑成本、时间和距离等指标。现有系统忽略了 "安全 "这一重要指标。它只建议...

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来源期刊

Journal of Experimental & Theoretical Artificial Intelligence 工程技术-计算机：人工智能

CiteScore

6.10

自引率

4.50%

发文量

审稿时长

>12 weeks

期刊介绍： Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving