An active learning approach for identifying the smallest subset of informative scenarios for robust planning under deep uncertainty

首页> 外文期刊>Environmental Modelling & Software >An active learning approach for identifying the smallest subset of informative scenarios for robust planning under deep uncertainty

【24h】

An active learning approach for identifying the smallest subset of informative scenarios for robust planning under deep uncertainty

机译：一种主动学习方法，用于识别信息情景中最小的子集，以在深度不确定性下进行可靠的计划

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

页面导航

著录项
相似文献
相关主题

著录项

来源
《Environmental Modelling & Software》 |2020年第5期|104681.1-104681.13|共13页
作者

展开▼
作者单位

Politecn Milan Dept Elect Informat & Bioengn Piazza L da Vinci 32 Milan 20133 Italy;

Univ Adelaide Sch Civil Environm & Min Engn Adelaide SA 5005 Australia;

展开▼
收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
入库时间 2022-08-18 05:18:46

相似文献

外文文献
中文文献
专利

1. Multi-scenario multi-objective robust optimization under deep uncertainty: A posteriori approach [J] . Shavazipour Babooshka, Kwakkel Jan H., Miettinen Kaisa Environmental Modelling & Software . 2021,第Octa期

机译：深度不确定性下的多场景多目标鲁棒优化：后验方法
2. A Deep Learning Approach for Identifying User Communities Based on Geographical Preferences and Its Applications to Urban and Environmental Planning [J] . DANIELLE L. FERREIRA, BRUNO A. A. NUNES, CARLOS ALBERTO V. CAMPOS, ACM Transactions on Spatial Algorithms and Systems . 2020,第3期

机译：基于地理偏好及其对城市和环境规划的应用识别用户社区的深度学习方法
3. Robust global sensitivity analysis under deep uncertainty via scenario analysis [J] . Gao Lei, Bryan Brett A., Nolan Martin, Environmental Modelling & Software . 2016,第FEBa期

机译：通过方案分析在深度不确定性下进行强大的全局敏感性分析
4. A robust approach for active distribution network restoration based on scenario techniques considering load and DG uncertainties [C] . Xin Chen, Wenchuan Wu, Boming Zhang, IEEE Power and Energy Society General Meeting . 2016

机译：基于情景技术的，考虑负荷和DG不确定性的主动配电网恢复的可靠方法
5. Directed International Technological Change and Climate Policy: New Methods for Identifying Robust Policies Under Conditions of Deep Uncertainty. [D] . Molina-Perez, Edmundo. 2016

机译：指导国际技术变化和气候政策：在高度不确定性条件下确定稳健政策的新方法。
6. Towards a Robust Visual Place Recognition in Large-Scale vSLAM Scenarios Based on a Deep Distance Learning [O] . Liang Chen, Sheng Jin, Zhoujun Xia 2021

机译：基于深度远程学习的大规模VSLAM情景中的强大视觉识别
7. Scenario-robustness methodology: An approach to flexible planning under uncertainty with an application to AIDS-related resource allocation. [O] . Rizakou Eleni 1995

机译：情景稳健性方法：在不确定性下灵活规划的方法，适用于与艾滋病相关的资源分配。

An active learning approach for identifying the smallest subset of informative scenarios for robust planning under deep uncertainty

著录项

相似文献

相关主题

期刊订阅