基于BP神经网络的上市公司CEO报酬实证研究

近年来的研究表明,CEO报酬不仅受公司业绩的影响,还受到其他诸多因素的影响,而且,CEO报酬与其决定因素之间往往存在着非线性关系。本文以2003-2005年沪深股市的A股上市公司为样本,采用BP神经网络对CEO总报酬、CEO年薪、CEO持股价值及其决定因素分别进行训练和学习,结果表明：（1）网络训练输出值与实际值的拟合度分别达到91.09%、97.23%和78.44%;（2）网络的预测能力相对于传统的线性回归模型分别提高了92.72%、92.08%和53.89%。因此,本文认为在分析和确定CEO报酬水平时引入神经网络模型是可行的。     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

超速行驶违法行为成因及预防对策

超速行驶是引起道路交通事故的重要原因之一,针对目前我国超速行驶违法行为的现状和综合治理情况,阐述了超速行驶违法行为形成的主要原因,并从提高交通参与者的交通安全意识,改善道路安全设计,完善道路交通配套设施,提高车辆性能,加大测速执法设备的应用,加强执法策略等方面入手,提出超速行驶违法行为预防对策.     

环境检测机构人员培训工作探讨

环境检测人员培训在整个生态文明建设中发挥着至关重要的作用,本文从培训计划、培训内容、培训方式、有效评价和记录归档五个方面探讨了环境检测机构人员培训工作流程,以确保机构行之有效地开展人员培训。     

燃煤电厂锅炉袋除尘器用PPS滤料失效原因分析

分析了燃煤电厂锅炉袋式除尘器用聚苯硫醚(PPS)破损滤袋样品的性能,并与新袋样品进行对比,得出工况含氧量、SOX浓度偏高,且有结露现象为滤袋破损的主要原因。     

西安f7地裂缝发展变化的预测研究

论文首先分析和总结了影响西安地裂缝发展变化的主要人为因素。随后,利用三维非稳定渗流分析方法研究了人类活动对地下水位的影响;根据西安市新增固定资产投资的变化,预测了地面荷载的变化;以时间、地下水位和地面荷载为基本变量,建立了预测f 7地裂缝活动趋势的BP神经网络模型;最后,借助MATLAB语言进行编程,利用训练稳定的网络模型,预测了f 7地裂缝的活动趋势以及年平均的垂直位移沉降量,为进一步研究西安地铁2号线安全运行和防护提供参考依据。     

基于产业链的区域环境污染物排放的产业贡献

区域经济增长与环境质量之间的关系研究是目前学者们探讨的重要学术议题之一.其中较多的是对EKC曲线的验证,近几年部分学者从国民经济各部门中的产业自身特征、产业结构、技术进步、FDI效应等方面考察产业发展对污染物排放的影响.然而以上研究议题中学者均没有讨论污染物的发生主体-各产业部门与排污的直接关系.故本文将从宏观尺度下的综合水平测度区域经济发展与环境质量关系、中观尺度下的产业属性特征与排污关系的研究视角转移至分析具体产业部门的污染物排放效应,同时将产业置于产业链的结构形式中,研究产业链上产业发展与污染物排放的关系.发现:第一,通过借助复杂网络思想的社区划分方法,将山东省39个产业部门分为3个社团.其中社团I主要由制造业部门组成,共有18个产业部门,社团II包括了15个部门,主要是第三产业,杜团III由6个产业部门组成且内部异质性高.第二,选择其中以制造业为主的社团I,并在社团I内识别出一条彼此间联系最为紧密的产业链,包括农林牧渔业、食品制造及烟草加工业、化学工业、纺织工业、服装皮革羽绒及其制品业、通用/专用设备制造业和交通运输设备制造业.以一种定量的方法获取了通过价值流传递而串在一起的产业链条.该产业链的经济规模、污染物规模在山东省均有重要地位.第三,采用岭回归分析方法,构建了6个制造业与产业链工业废水、固体废弃物排放的关系模型,6个制造业中对工业废水、固体废弃物排放相对贡献度最大的部门分别为服装皮革羽绒及其制品业、食品制造及烟草加工业.这是由于上游产业排污的链式传递效应与产业自身污染物排放效应的共同叠加作用.     

Transnational environmental collective action facing implementation constraints – the case of nutrient leakage in the Baltic Sea Action Plan

While scholars have showed a long-standing interest for how to design effective environmental treaties and other international agreements, less interest has been paid to implementation phases of these agreements. This article takes the Eutrophication Segment in the Baltic Sea Action Plan as an example of a regional effort to reduce nutrient leakages, where national reporting of adopted strategies has been a key mechanism to improve implementation effectiveness. It is shown that although transnational collective action theory is a powerful tool to analyse underlying drivers and priorities in state implementation policies, a deeper analysis of domestic and external constraints can shed additional light on observed implementation gaps. Varying views among countries on, for example, the role of stakeholder participation, legitimacy and top-down governing versus multi-stakeholder governance approaches may comprise domestic constraints that make effective and efficient implementation problematic. In terms of external constraints, states’ balancing of action plan objectives versus other international commitments, such as other environmental treaties and EU Directives, is shown to potentially reduce implementation efficiency as well.     

人工神经网络方法在拟建小区域环境质量评价中的应用

人工神经网络的评价方法用于小区域环境质量评价中,根据本地区特点因地制宜地选择环境质量参数,代入模型中进行环境质量评价及预测,对用于环境质量评价的BP人工神经网络模型进行了改进,即对网络模型的训练样本进行了扩充,从而提高了模型的抗干扰能力和准确性.将改进了的BP人工神经网络模型应用于四川省资阳市沱江二桥拟建项目小区域的大气、地表水环境质量评价中, 对该市小区域大气、地表水环境质量状况进行评价,评价结果表明,BP人工神经网络模型用于环境质量评价是可行的,且评价结论客观,评价模型普遍适用.     

基于模糊神经网络的机动车驾驶教练员职业适宜性研究

提出应用模糊神经网络系统,建构教练员职业适宜性的3个要素(即心理素质、驾驶技能和知识的表达阐述能力)的学习样本,分析"三要素"的8项特征参数指标——场依存性、速度估计能力、交通安全意识、简单反应、选择反应、跟踪能力、行车注意力、表达阐述能力等,使用K-均值法对实验样本进行初始分类,形成标准学习样本,使用该样本对所构建系统进行训练和调试。利用经调试训练后的系统,依据所测教练员的心理、心理参数对其职业适宜性进行评价。试验表明:建立的教练员职业适宜性仿真模型能取得很好的评价效果。