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1.
Numerous efforts have been made to understand stemflow dynamics under different types of vegetation at the inter-event scale, but few studies have explored the stemflow characteristics and corresponding influencing factors at the intra-event scale. An in-depth investigation of the inter- and intra-event dynamics of stemflow is important for understanding the ecohydrological processes in forest ecosystems. In this study, stemflow volume (FV), stemflow funnelling ratio (FR), and stemflow ratio (F%) from Quercus acutissima and Broussonetia papyrifera trees were measured at both inter- and intra-event scales in a subtropical deciduous forest, and the driving factors, including tree species and meteorological factors were further explored. Specifically, the FV, FR and F% of Q. acutissima (52.3 L, 47.2, 9.6%) were lower than those of B. papyrifera (85.1 L, 91.2, 12.4%). The effect of tree species on FV and F% was more obvious under low intensity rainfall types. At the inter-event scale, FV had a strong positive linear correlation with rainfall amount (GP) and event duration (DE) for both tree species, whereas FR and F% had a positive logarithmic correlation with GP and DE only under high-intensity, short-duration rainfall type. FR and F% were mainly affected by wind speed and the maximum 30-min rainfall intensity under low-intensity, long-duration rainfall type. At the intra-event scale, for both tree species, the mean lag time between the start of rainfall and stemflow was the shortest under high-intensity, short-duration rainfall type, while the mean duration and amount of stemflow after rain cessation were the greatest under high-amount, long-duration rainfall type. The relationship between stemflow intensity and rainfall intensity at the 5-min interval scale also depended greatly on rainfall type. These findings can help clarify stemflow dynamics and driving factors at both inter- and intra-event scales, and also provide abundant data and parameters for ecohydrological simulations in subtropical forests.  相似文献   
2.
随着互联网产业的飞速发展,电子商务开始进入农业领域。以电子商务起步较早的"洛川苹果"作为研究对象进行调研。基于随机森林模型的决策树集成算法,对农业网络销售体系整体进行数据分析,模型构建,从问题表象出发挖掘其在不同部分的影响因子,最终基于影响因素解决问题,提出合理化建议:加强农村基础设施建设、健全农村公共服务体系以及完善农村电子商务培训制度等,因地制宜,推进农业电子商务的健康发展。  相似文献   
3.
依靠岩浆构造环境的地球化学成分认识岩浆形成过程是岩石地球化学中的重要应用。当前利用岩石地球化学成分判别构造环境的工作还不够深入。用4种基于决策树的机器学习方法对来自全球新生代洋岛玄武岩(OIB)、岛弧玄武岩(IAB)及大洋中脊玄武岩(MORB)等镁铁-超镁铁岩中单斜辉石的13种主量元素构成数据集进行了岩浆构造环境判别和主要特征排序。通过对比4种基于决策树的机器学习方法,验证了树类算法对于地球化学成分识别问题的有效性,并总结出4种方法在处理岩浆构造环境判别问题时的优劣:决策树算法判别过程更易于理解,但是其准确率欠佳;boosting算法中的AdaBoost和GBDT对于岩浆构造环境的鉴别准确度较高,但构造过程复杂;bagging集成算法随机森林在权衡性能和模型可理解性时不失为一个良好的选择。此外,还通过4种算法的特征重要性排序得出Cr_2O_3,TFeO,TiO_2,FeO和Al_2O_3是进行岩浆构造环境判别的重要成分。  相似文献   
4.
高分六号卫星具有覆盖广、多种分辨率、波段多的优势,能为遥感解译提供更丰富的信息。为探究高分六号卫星新增波段在森林树种识别上的应用,本文以覆盖根河市阿龙山林业局的一期高分六号宽幅影像为数据源,基于特征优化空间算法(Feature Space Optimization,FSO)和最大似然分类法,分别利用高分六号的前4个波段和所有波段(8波段)的光谱、纹理等特征进行了森林树种分类,并逐一添加新增波段特征确定了各波段的贡献率排名。结果表明:在加入了优选出的均匀性纹理、均值纹理和角二阶矩纹理3种纹理特征后,前4波段和8波段的分类精度比只基于光谱特征时的精度分别高出13.23%和24.63%;利用8波段信息比只利用前4波段在基于光谱特征上的精度高11.88%,在基于光谱+纹理特征上则高23.24%;基于8波段光谱+纹理特征的树种分类精度最高,达到68.74%,新增4波段的贡献率排名为B6>B5>B8>B7,说明新增红边波段对于本次树种分类试验的贡献率最高,能为北方树种识别提供有效帮助。  相似文献   
5.
为揭示树木的不同空间配植方案对行人呼吸高度气流的影响,本文将树木视为均匀多孔介质,通过附加源项法从空气动力学角度用CFD模拟了H/W=2的典型深街谷几何内4种树木配植情景,实验表明,不同空间配置下树木对街谷内行人呼吸高度处局地气流的影响强弱在空间分布模式上差异悬殊:① 均匀种植的树木对街谷内行人呼吸高度的气流起到阻碍作用,不均匀种植则有效提升街谷的整体流速。4种空间配植方案下树木对气流的影响程度不同,阻碍作用从大到小的顺序为均匀间距8 m(Spa8m)>均匀间距6 m(Spa6m)>均匀间距20 m(Spa20m)>不均匀配植(Non-uniform);对应的平均气流增强指标顺序为$\bar{D}_{spa8}$(-19.31%)<$\bar{D}_{spa6}$(-16.14%)<$\bar{D}_{spa20}$(-10.73%)<$\bar{D}_{non-uniform}$(1.25%)。② 对比不均匀和均匀的种植方案,不均匀植树的街谷内部行人呼吸高度的气流流速比其对照案例(均匀植树Spa8m方案)整体增强了106.49%。街谷中部不种树,在街谷两端配置树木并预留足够的自由空间的不均匀植树方案,能够让角涡渗入街谷中部,促使街谷内部的垂直漩涡和两端的水平角涡运动,增强湍流和垂直交换,有效减少了街道两端“风口效应”和街道中部“风影效应”的区域,改善了整个街谷行人呼吸平面的风环境。④ 合理空间配置的树木能够改善街谷内部的行人风环境。街谷内行人呼吸高度处的气流对局地条件很敏感,树木的局部配置(空间簇集、密度)将引起强烈的空间变化。在既有城市建筑布局条件下,如何通过谨慎的景观设计,利用树木等城市绿化措施有效地改善城市的行人风环境,缓解污染扩散、疾病传播等问题,本文的方法可提供一定的参考。  相似文献   
6.
A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV.  相似文献   
7.
海域动态监管业务是实施海域管理精细化、科学化的重要手段。文章从海域监管工作模式、海域使用动态监测、海域资源调查、分析评价与决策支持成果等方面对江苏海域动态监视监测业务进行梳理,以期为全国海域动态监管业务化拓展提供参考。  相似文献   
8.
Abstract

Liquefaction of loose saturated soil deposits is a hazardous type of ground failure occurring under earthquake excitations. Therefore, an accurate estimation of liquefaction potential is extremely important in geotechnical engineering. In the current study, a new model is proposed which estimates the level of strain energy needed for liquefaction initiation. A compiled database containing cyclic tests gathered from previously published works was used to develop new models to predict liquefaction potential. M5′ algorithm was used to find the best correlation between parameters. It was shown that not only the derived formulas are acceptably accurate but also they feature a very simple structure in comparison with available formulas in the literature. The proposed equations are accurate, physically sound and uncomplicated. Furthermore, safety factors were given for different levels of risk, which can be useful for engineering practice. In addition, the influence of different predictors on the liquefaction potential was evaluated and also the significance of input variables was assessed via sensitivity analysis. Finally, a new model was introduced for preliminary estimation of liquefaction potential.  相似文献   
9.
Accurate estimation of pan evaporation (Epan) is very important in water resources management, irrigation scheduling and water budget of lakes. This study investigates the accuracy of two heuristic regression approaches, multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in estimating pan evaporation using only temperature data as input. Monthly minimum temperature, maximum temperature and Epan data from three Turkish stations were used, with month number (periodicity information) added as input to see its effect on estimation accuracy. The models were compared with the calibrated Hargreaves-Samani (CHS), Stephens-Stewart (SS) and multiple linear regression methods. Three different train-test splitting strategies (50%–50%, 60%–40% and 75%–25%) were employed for better evaluation of the applied methods. The results show that the MARS method generally estimated monthly Epan with higher accuracy compared to the M5Tree, CHS and SS methods. When extraterrestrial radiation, calculated from Julian date and latitude information, was used as input to the SS instead of solar radiation, satisfactory estimates were obtained. A positive effect on model accuracy was observed when involving periodicity information in inputs and increasing training data length.  相似文献   
10.
The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET0). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET0. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET0. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET0, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four-input PCE models for Isparta and Antalya, respectively.  相似文献   
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