机译:使用随机多准则可接受性分析(SMAA)评估生态区域对比中林地生产力预测的建模技术
Department of Earth and Environmental Sciences, Division Forest, Nature and Landscape, Katholieke Universiteit Leuven, Celestijnenlaan 200E Box 2411, BE-3001 Leuven, Belgium;
Department of Earth and Environmental Sciences, Division Forest, Nature and Landscape, Katholieke Universiteit Leuven, Celestijnenlaan 200E Box 2411, BE-3001 Leuven, Belgium;
Department of Earth and Environmental Sciences, Division Forest, Nature and Landscape, Katholieke Universiteit Leuven, Celestijnenlaan 200E Box 2411, BE-3001 Leuven, Belgium;
Department of Earth and Environmental Sciences, Division Forest, Nature and Landscape, Katholieke Universiteit Leuven, Celestijnenlaan 200E Box 2411, BE-3001 Leuven, Belgium;
mediterranean mountain forest; temperate lowland forest; predictive modelling; boosted regression trees; artificial neural networks; generalized additive models; site index;
机译:利用Dirichlet分布统一多标准决策分析(MCDA)和随机多轨道可接受性分析(SMAA)的简单方法
机译:SMAA-PO:基于随机多准则可接受性分析的项目组合优化问题
机译:前景理论和随机多准则可接受性分析(SMAA)
机译:基于态度积分的随机多准则可接受性分析
机译:评估基于Web的公众参与GIS以进行多准则站点选择分析:以Canmore Alberta为例。
机译:基于多准则评估技术的最佳森林公路网制图-以希腊萨索斯岛地中海岛为例
机译:使用随机多标准可接受性分析(SMAA)评估生态区域对比中林地生产力预测的建模技术