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超建模：通过替代模型的同步达成共识Supermodeling: Consensus by Synchronization of Alternative Models |
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| 课程网址: | http://videolectures.net/solomon_duane_supermodeling/ |
| 主讲教师: | Gregory Duane |
| 开课单位: | 马其顿科学艺术学院 |
| 开课时间: | 2011-09-08 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Computational models of an ongoing objective process, as in weather forecasting, must continually assimilate new observational data as they run. Both "truth" and "model" are chaotic systems that thus synchronize through a limited exchange of information in one direction - a phenomenon that can be characterized as machine perception. A recent suggestion has been to envision the fusion of different models analogously, as 3-way synchronization of the different models with reality. This phenomenon may be useful for improving climate projection by combining a few different models that differ in regard to the magnitude of global warming and regional predictions. Several machine learning approaches have been proposed to train the connections linking corresponding variables in the different models. Stochastic approaches can avoid non-global local optima, but it seems likely that an intelligent "expert system" approach would improve the supermodel. |
| 关 键 词: | 混沌系统; 机器感知; 超模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-09-21：cwx |
| 阅读次数: | 67 |