Cover Image, Volume 39, Issue 18

IF 8.5 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer-Aided Civil and Infrastructure Engineering Pub Date : 2024-09-01 DOI:10.1111/mice.13335

引用次数: 0

Abstract

The cover image is based on the Article A traffic state prediction method based on spatial–temporal data mining of floating car data by using autoformer architecture by Shuangzhi Yu et al., https://doi.org/10.1111/mice.13179.

Abstract Image

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封面图片，第 39 卷第 18 期

封面图像基于余双志等人撰写的文章《一种基于时空数据挖掘的浮动车数据交通状态预测方法》（A Traffic State prediction method based on spatial-temporal data mining of floating car data by using autoformer architecture），https://doi.org/10.1111/mice.13179。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer-Aided Civil and Infrastructure Engineering 工程技术-工程：土木

CiteScore

17.60

自引率

19.80%

发文量

146

审稿时长

1 months

期刊介绍： Computer-Aided Civil and Infrastructure Engineering stands as a scholarly, peer-reviewed archival journal, serving as a vital link between advancements in computer technology and civil and infrastructure engineering. The journal serves as a distinctive platform for the publication of original articles, spotlighting novel computational techniques and inventive applications of computers. Specifically, it concentrates on recent progress in computer and information technologies, fostering the development and application of emerging computing paradigms. Encompassing a broad scope, the journal addresses bridge, construction, environmental, highway, geotechnical, structural, transportation, and water resources engineering. It extends its reach to the management of infrastructure systems, covering domains such as highways, bridges, pavements, airports, and utilities. The journal delves into areas like artificial intelligence, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, internet-based technologies, knowledge discovery and engineering, machine learning, mobile computing, multimedia technologies, networking, neural network computing, optimization and search, parallel processing, robotics, smart structures, software engineering, virtual reality, and visualization techniques.