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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.
收藏  |  浏览/下载：27/0  |  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  
A keystone species, European aspen (Populus tremula L.), in boreal forests: Ecological role, knowledge needs and mapping using remote sensing 期刊论文
, 2020, 卷号: 462
作者:  Kivinen S.;  Koivisto E.;  Keski-Saari S.;  Poikolainen L.;  Tanhuanpää T.;  Kuzmin A.;  Viinikka A.;  Heikkinen R.K.;  Pykälä J.;  Virkkala R.;  Vihervaara P.;  Kumpula T.
收藏  |  浏览/下载：39/0  |  提交时间：2020/07/28
Arches  Biodiversity  Data acquisition  Ecology  Mapping  Reforestation  Airborne Laser scanning  Biochemical properties  Boreal forests  European aspen  Populus tremula L  Remote sensing techniques  Spatiotemporal information  Three-dimensional data  Remote sensing  airborne survey  biodiversity  boreal forest  coniferous forest  ecological approach  forest management  keystone species  knowledge  mapping method  photogrammetry  population viability analysis  remote sensing  species diversity  Biochemical Properties  Biodiversity  Data Processing  Ecology  Mapping  Reforestation  Coniferales  Populus  Populus tremula  Populus tremuloides