GeoWeb Conference

GeoWeb2007与2008年大会分别于Vancouver举办,主题分别为“From Mashups to Infrastructure”及“Infrastructure: Local to Global”。大会强调了地理信息系统从消费者应用向关键基础设施的转变,并探讨了全球聚合器、安全防御、实时应急响应等议题。

 

首届大会GeoWeb 2007于July 23-27在Vancouver, British Columbia举办,

主题为 From Mashups to Infrastructure—GeoWeb 2007。

大会blog地址:http://www.geowebblog.org/

大会KeyNote Speech的视频可以访问:http://www.geowebblog.org/index.php?cat=5 下载mp3、Podcast或Quicktime

或者直接到Youtube在线浏览。

参与人员会后给予极高评价:

            100% of GeoWeb 2007 Attendees Surveyed Said They Would Recommend this Conference to a Colleague!

 

GeoWeb 2007’s principal theme, “From Mashups to Infrastructure,” reflects the breadth, the evolution, and the growing maturity of the GeoWeb. This theme acknowledges the highly visible consumer applications that helped spawn the GeoWeb while emphasizing that the GeoWeb is increasingly playing a meaningful role in mainstream, mission-critical applications. As such, the GeoWeb is now a key component in critical decision-making across a broad spectrum of market segments and application domains.

 

GeoWeb 2008又粉墨登场,于July21-25在Vancouver再次主办,今年的主题为:Infrastructure:  Local to Global 。

The theme for the 2008 conference is “Infrastructure:  Local to Global”, which implies the GeoWeb has a local community dimension as well as a global dimension.  The integration of global aggregators will drive the creation of local infrastructures and will give rise to a global infrastructure.  Additional points of discussion will include:

  • Global Aggregators and Data Communities
  • GeoWeb in Security and Defense
  • Real Time Emergency Response and Environmental Security
  • Neo-Geo, User Generated Data and the GI Professional
  • CAD-BIM-GIS-Games Integration – 3D Cityscapes (Worlds Real and Virtual)
  • Infrastructure for Information – Building Alongside Physical Infrastructure
  • Municipal SDI in the GeoWeb
  • Imaging, Coverages and Information Infrastructures

 

【电动汽车充电站有序充电调度的分散式优化】基于蒙特卡诺和拉格朗日的电动汽车优化调度(分时电价调度)(Matlab代码实现)内容概要:本文介绍了基于蒙特卡洛和拉格朗日方法的电动汽车充电站有序充电调度优化方案,重点在于采用分散式优化策略应对分时电价机制下的充电需求管理。通过构建数学模型,结合不确定性因素如用户充电行为和电网负荷波动,利用蒙特卡洛模拟生成大量场景,并运用拉格朗日松弛法对复杂问题进行分解求解,从而实现全局最优或近似最优的充电调度计划。该方法有效降低了电网峰值负荷压力,提升了充电站运营效率与经济效益,同时兼顾用户充电便利性。 适合人群:具备一定电力系统、优化算法和Matlab编程基础的高校研究生、科研人员及从事智能电网、电动汽车相关领域的工程技术人员。 使用场景及目标:①应用于电动汽车充电站的日常运营管理,优化充电负荷分布;②服务于城市智能交通系统规划,提升电网与交通系统的协同水平;③作为学术研究案例,用于验证分散式优化算法在复杂能源系统中的有效性。 阅读建议:建议读者结合Matlab代码实现部分,深入理解蒙特卡洛模拟与拉格朗日松弛法的具体实施步骤,重点关注场景生成、约束处理与迭代收敛过程,以便在实际项目中灵活应用与改进。
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