基于贡献度随机森林模型的公司债信用风险实证分析

运用贡献度随机森林方法（CRF）方法探讨公司债财务指标比率与其违约率的关系.运用连续属性离散化方法（OB）进行财务指标最优降维；运用WOE变换进行模型变量约简.研究表明，CRF模型的分类性能显著优于其他模型，测试集评估总体正确率达90.47%，AUC统计量、AR比率及K-S值分别提升了2.6%、7.6%、4.38%，变量贡献度量化了各财务指标对违约率影响，为诠释随机森林预测机制提供了依据.     

网络嵌入性、商业模式创新与企业竞争优势关系研究

基于商业模式创新中介效应，依据全国314家企业问卷调查的样本数据，运用多元线性回归方法，考量网络嵌入性、商业模式创新和企业竞争优势之间关系，结果发现：关系嵌入性、结构嵌入性与竞争优势均有显著的正向关系；商业模式创新在关系嵌入性、结构嵌入性与企业竞争优势的关系中起着中介作用。鉴此，企业应注重构建不同形式的网络嵌入，推动商业模式的调整与变革，以提高企业竞争优势。     

Improving cereal yield forecasts in Europe – The impact of weather extremes

The impact of extreme events (such as prolonged droughts, heat waves, cold shocks and frost) is poorly represented by most of the existing yield forecasting systems. Two new model-based approaches that account for the impact of extreme weather events on crop production are presented as a way to improve yield forecasts, both based on the Crop Growth Monitoring System (CGMS) of the European Commission. A first approach includes simple relations – consistent with the degree of complexity of the most generic crop simulators – to explicitly model the impact of these events on leaf development and yield formation. A second approach is a hybrid system which adds selected agro-climatic indicators (accounting for drought and cold/heat stress) to the previous one. The new proposed methods, together with the CGMS-standard approach and a system exclusively based on selected agro-climatic indicators, were evaluated in a comparative fashion for their forecasting reliability. The four systems were assessed for the main micro- and macro-thermal cereal crops grown in highly productive European countries. The workflow included the statistical post-processing of model outputs aggregated at national level with historical series (1995–2013) of official yields, followed by a cross-validation for forecasting events triggered at flowering, maturity and at an intermediate stage. With the system based on agro-climatic indicators, satisfactory performances were limited to microthermal crops grown in Mediterranean environments (i.e. crop production systems mainly driven by rainfall distribution). Compared to CGMS-standard system, the newly proposed approaches increased the forecasting reliability in 94% of the combinations crop × country × forecasting moment. In particular, the explicit simulation of the impact of extreme events explained a large part of the inter-annual variability (up to +44% for spring barley in Poland), while the addition of agro-climatic indicators to the workflow mostly added accuracy to an already satisfactory forecasting system.     

花生黄曲霉生长预测模型的研究

通过对分离自花生的黄曲霉LYYSS03-3在不同温度(15-35℃)、不同相对湿度(水活度分别为0.5,0.7,0.9)下的菌落生长特性进行检测,采用Boltzmann和Logistic 模型对黄曲霉的生长曲线进行拟合,结果表明,在适宜温湿度阶段,花生黄曲霉的生长曲线更适合用Boltzmann模型拟合.     

木工平刨床安全事故浅析

以木工平刨伤手为顶上事件,利用事故树法进行评价,提出有针对性的预防措施,对安全生产可起到积极的作用。     

基于高光谱特征参数的冬小麦氮营养指数估算

为了实现快速高精度获取冬小麦氮营养指数的高光谱监测技术，利用美国SVC HR-1024I型野外光谱辐射仪对2017-2019年关中地区的冬小麦进行遥感监测，获取“三边”参数、任意两波段光谱指数和植被指数，通过相关性分析和逐步回归分析方法筛选冬小麦氮营养指数的敏感光谱参数，结合偏最小二乘回归(PLSR)、随机森林算法(RFR)、支持向量机回归(SVR)和梯度增强回归(GBDT)建立冬小麦氮营养指数模型，并对模型估算精度进行验证。结果表明，从拔节期到灌浆期，各时期的氮营养指数与任意两波段光谱指数均呈极显著相关，其中拔节期氮营养指数与任意两波段光谱指数相关性均高于其他时期，且基于一阶导数光谱的归一化光谱指数和比值光谱指数与氮营养指数的相关系数最大，为0.66。拔节期基于梯度增强回归的冬小麦氮营养指数预测模型的决定系数(r²)和均方根误差(RMSE)分别为0.96和0.05,模型验证的r²、RMSE和相对预测偏差(RPD)分别为0.95、0.12和2.12,模型预测精度最高。因此，拔节期基于梯度增强回归的冬小麦氮营养指数估算模型可用于冬小麦氮营养监测...     

丘陵岗地人工防护林退化成因分析

以桃江县人工防护林为研究对象,分析了导致林地退化的主要原因,包括管护措施不到位、造林技术缺陷、自然灾害侵害、生理老化、环境污染等。针对退化原因,提出了相应的改造措施。     

基于SWAT模型的大安市降水入渗量变化的模拟研究

针对近年的研究热点,通过SWAT模型对半干旱、盐碱化严重的吉林省大安市进行降水入渗模拟。以2000、2004和2008年遥感影像解译得到的土地利用数据为基础,结合SWAT模型的模拟结果,讨论LUCC与降水入渗量的相关关系。2008年与2000年相比,难利用地的面积有所降低,旱地、草地等发生了大面积的增加,研究区内土地状况有所好转。通过SWAT模型运行得到的结果显示:2008年的平均降水入渗量为56.27 mm,比2000年的值高。利用降水入渗系数法进行计算,也得到了2008年的降水入渗量高于2000年的结果,这与SWAT模型模拟得到的结果有着相同的趋势,且平均降水入渗量的标准偏差为5.27,说明SWAT模型对于研究区有良好的适应性。同时,根据土地利用数据和SWAT模型模拟数据可以得知,LUCC对研究区的降水入渗量存在着一定的相关性。     

A conceptual model of farmers' decision-making process for nitrogen fertilization and irrigation of durum wheat

With a 2 millions of tons production, France is the second country in the European Union to produce durum wheat. Durum wheat production requires high grain nitrogen concentration. Irrigation and nitrogen fertilization must be managed simultaneously to maximize grain yield and also avoid low protein concentration and environmental impacts. To help advisors and farmers to better manage together these two agricultural operations and to develop innovative managements, developing a biodecisional model is an interesting possibility. However, knowledge is still missing on how farmers already managed these operations and how these two operations are linked. We developed the conceptual model for the decision part of this computer model. We performed a survey of 28 farmers conducted over the five French production areas investigating a diversity of growing conditions to identify the set of possible constraints and farmers' decision rules. To analyze the survey, we first used a general inductive approach on individual cases and then built a conceptual model of the decision with a bottom-up approach. We identified four decision sequences for fertilization (N splitting, choice of N fertilizer, rate of application, fertilization triggering) and five for irrigation (irrigation period, anticipated number of irrigation cycles, irrigation cycles organization, irrigation triggering and irrigation cycle specificities). For each operation, the first three decision sequences refer to strategic decisions. The other decision sequences refer to tactical decisions. Coupling this model with a crop model could provide guidelines for managing durum wheat in the current climatic and economic changing context.     

基于B-S模型的环保项目投资评价

以ABC公司环保产品开发为例,针对传统项目投资评价在环保项目上的缺点,分析了将实物期权理论运用到环保项目投资评价中的可行性,并运用B-S模型进行定量分析,以期为环保项目投资提供一个新的思路,同时也使环保项目决策变得更加合理。