Results 21 to 30 of about 728,627 (161)
Shuitu Baochi Xuebao, 2004 以江西严重退化第四纪红粘土为研究对象,选择其中9种模式重建的林龄10年的森林,调查土壤理化性状,结果表明:(1)土壤有机质、全N、速效N、全P、速效P明显增加,而且增加幅度最大的是有机质;土壤全钾、有效钾都较大程度提高。(2)土壤有机质、全氮浓度随土层深度明显下降,有效磷、有效钾、有效氮浓度则随土层深度平缓下降,全磷、全钾浓度随土层变化不明显。(3)各重建森林模式的土壤容重、非毛管孔隙度也呈较大幅度降低;毛管持水量、毛管孔隙度呈不同幅度增加;不同重建模式总孔隙度变化的差异较大。
刘苑秋 杜天真 郭晓敏 杨国平 罗良兴
doaj +2 more sources
基于机器学习的沟谷地貌识别模型对比——以黄土高原典型流域为例
Shuitu Baochi Xuebao, 2023 探索沟谷地貌空间分布与环境控制特征之间的联系并构建沟谷地貌准确提取模型,对大尺度范围沟谷提取具有重要意义。基于人工提取黄土高原典型流域沟谷地貌样本,结合不同时期的Landsat8 OLI影像数据和DEM数据,建立随机森林模型确定黄土高原沟谷地貌提取最佳影像时期和最佳组合特征,基于最优模型参数,对比其与支持向量机和人工神经网络沟谷提取模型效果,验证模型泛化能力。结果表明:(1)黄土高原沟谷提取的最佳影像时期为12月,最佳组合特征集为Red、Blue、H、SWIR1、PNT、Coastal ...
范天程 +5 more
doaj
Organ‐specific ozone and nitrogen legacies strengthen substrate control over litter decomposition
Functional Ecology, Volume 40, Issue 8, Page 2548-2559, August 2026.Read the free Plain Language Summary for this article on the Journal blog. Abstract Elevated tropospheric ozone (O3) and nitrogen (N) deposition are concurrent atmospheric changes that strongly influence terrestrial carbon cycling, yet their combined effects on below‐ground decomposition remain poorly understood.
Xiaofan Hou +8 more
wiley +1 more source
Functional Ecology, Volume 40, Issue 8, Page 2617-2627, August 2026.Read the free Plain Language Summary for this article on the Journal blog. Abstract Root activity creates unique microbial hotspots in the rhizosphere by influencing the metabolic activities of surrounding soil microorganisms, profoundly regulating the dynamics of soil organic carbon (SOC). However, how root economic strategies affect the formation and
Qiyu Tan +8 more
wiley +1 more source
, 2012 针对利用分类器对建筑结构进行损伤识别的问题,引入一种新的组合分类器算法——随机森林,提出基于小波包分解和随机森林的结构损伤识别方法。首先,采用小波包对结构在不同损伤程度和位置上的振动加速度信号进行分解,得到各个频带上的总能量;然后,利用各频带上能量值存在着差异性作为输入到分类器的特征向量;最后,训练随机森林模型并对建筑结构的损伤位置和损伤程度进行识别。应用该方法对一座8层剪切型钢框架结构进行损伤判别,并与BP神经网络和支持向量机方法进行对比 ...
周绮凤 +3 more
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Gongye shui chuli, 2023 造纸法烟草薄片废水的COD高且波动大，采用传统国标检测方法（重铬酸钾比色法）操作复杂、耗时长，难以实现快速检测以指导污水处理工况的及时调整。针对此问题，提出了一种基于机器学习的COD快速预测方法。在对烟草薄片废水水质指标分析基础上，采用数理统计结合人工智能的方法对废水COD与悬浮物、pH、溶解氧和电导率等水质参数之间的关系进行分析，并建立COD预测模型。结果表明，线性回归、多项式拟合、正则化回归、回归树等模型的R2为0.656~0.777，基于机器学习的极端随机森林模型的R2最高，为0.861 ...
戴泽军 +5 more
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Structured machine learning modeling to support conservation of deep‐sea benthic biodiversity
Conservation Biology, Volume 40, Issue 4, August 2026.Abstract Biodiversity monitoring programs need to deliver accurate, timely, and actionable predictions. To establish a predictive monitoring program for deep‐sea benthos of the Santos Basin, Brazil, we developed a two‐stage structured model that allowed comparison of biodiversity predictions obtained from environmental simulations (2M‐Sim).
Gustavo Fonseca +23 more
wiley +1 more source
Functional Ecology, Volume 40, Issue 7, Page 2128-2142, July 2026.Read the free Plain Language Summary for this article on the Journal blog. Abstract Soil organic nitrogen (SON) transformation is critical for global nutrient cycling and ecosystem productivity, yet how its responsiveness to climate change differs across diverse land use types remains poorly resolved.
Xinyi Yang +10 more
wiley +1 more source
, 2018 随机森林算法可对特征进行重要性排序,并能提高运行效率和分类的准确率.采用方差分析、随机森林算法对乳腺癌基因进行筛选,使得用随机森林算法、支持向量机算法和k近邻算法测试集的准确率分别达到95.6%,92.9%和92.7 ...
陈冬东, 张旭, 何林, 杨绍华
core +1 more source