找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Web and Wireless Geographical Information Systems; 20th International S Mir Abolfazl Mostafavi,Géraldine Del Mondo Conference proceedings 2

[复制链接]
楼主: 拼图游戏
发表于 2025-3-28 18:07:22 | 显示全部楼层
A Novel GIS-Based Machine Learning Approach for the Classification of Multi-motorized Transportatione based on smart phone sensors information and data from Geospatial Information System (GIS). Specifically, reliable transportation mode detection (TMD) algorithms using the real-time sensors data open new possibilities for travel optimization with minimum greenhouse gas emissions.
发表于 2025-3-28 21:02:47 | 显示全部楼层
Towards Integration of Spatial Context in Building Energy Demand Assessment Supported by CityGML Enes to represent and manage the required spatiotemporal information for BEMs and feed a knowledgebase that can be used in WSN deployment optimization algorithms. Finally, the paper presents and discusses a case study to highlight the advantages and limitations of the proposed approach.
发表于 2025-3-28 22:53:50 | 显示全部楼层
发表于 2025-3-29 04:07:13 | 显示全部楼层
发表于 2025-3-29 09:11:05 | 显示全部楼层
A Novel Feature Matching Method for Matching OpenStreetMap Buildings with Those of Reference Datasetrresponding polygons in the two datasets. The experiment results for five cities in the Province of Quebec indicate that the proposed algorithm can reduce the matching error of previous map matching algorithms from approximately 8% to approximately 3%. Furthermore, the study found that the proposed
发表于 2025-3-29 14:18:40 | 显示全部楼层
发表于 2025-3-29 17:55:11 | 显示全部楼层
发表于 2025-3-29 20:22:20 | 显示全部楼层
Mobility Data Analytics with KNOT: The KNime mObility Toolkittform with a collection of new components specifically designed to support processing steps typical of mobility data, including map-matching, trajectory partitioning, and road network coverage analysis. To show the effectiveness of these components, we report also on how we applied them to perform a
发表于 2025-3-30 00:41:58 | 显示全部楼层
发表于 2025-3-30 07:48:43 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-8 22:05
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表