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| Future Demand, Supply and Prices for Voluntary Carbon Credits – Keeping the Balance 科技报告 , 2021 作者: [unavailable]
Adobe PDF(1512Kb)  |   收藏  |  浏览/下载:8/0  |  提交时间:2021/11/24 |
| Prediction of landslide displacement using multi-kernel extreme learning machine and maximum information coefficient based on variational mode decomposition: a case study in Shaanxi, China 期刊论文 Natural Hazards, 2021, 卷号: 108, 期号: 1 作者: Ling Q.; Zhang Q.; Zhang J.; Kong L.; Zhang W.; Zhu L.
![](/themes/default/image/downing1.png) 收藏  |  浏览/下载:27/0  |  提交时间:2021/09/01 Displacement prediction Kernel extreme learning machine Kernel functions Maximum information coefficient Variational mode decomposition |
| State of the Climate in 2019 科技报告 , 2020 作者: [unavailable]
Adobe PDF(46553Kb)  |   收藏  |  浏览/下载:16/1  |  提交时间:2021/11/24 |
| Identifying groundwater contaminant sources based on a KELM surrogate model together with four heuristic optimization algorithms 期刊论文 , 2020, 卷号: 138 作者: Zhao Y.; Qu R.; Xing Z.; Lu W.
![](/themes/default/image/downing1.png) 收藏  |  浏览/下载:12/0  |  提交时间:2020/07/28 Contamination Efficiency Genetic algorithms Groundwater Groundwater pollution Heuristic algorithms Knowledge acquisition Learning algorithms Machine learning Modular robots Particle swarm optimization (PSO) Quantum computers Contaminant concentrations Contaminant sources Extreme learning machine Groundwater contaminants Heuristic optimization algorithms Heuristic search algorithms Source characteristics Traditional genetic algorithms Computational efficiency accuracy assessment genetic algorithm groundwater pollution identification method machine learning optimization reliability analysis surrogate method |
| Review of multi-hazards research and risk assessments 科技报告 , 2018
Adobe PDF(3538Kb)  |   收藏  |  浏览/下载:59/6  |  提交时间:2019/11/06 |
| Compilation and assessment of resource values and hazards to inform transportation planning and associated land-use planning 科技报告 报告编号: 70196396, , 2018 作者: Manier, Daniel J. manierd@usgs.gov; O'Donnell, Michael odonnellm@usgs.gov
Adobe PDF(17569Kb)  |   收藏  |  浏览/下载:6/3  |  提交时间:2019/11/06 |