广东环境审计的现状分析

伴随着环保事业的深入开展,环境审计在环境管理监督方面有着极其重要的意义。广东环境审计已经贯穿到各级政府的施政过程中。为了更好地发挥审计监督功能,未来广东环境审计应加快立法进程,提高认识,充分利用审计资源开展联合审计和事前环境审计,并对环境管理体系运作结果进行绩效审计。     

实数编码遗传算法的评述

遗传算法是一种基于自然选择和遗传变异等生物进化机制的全局优化搜索算法．使用实数表示基因的实数编码遗传算法常用于求解连续函数优化等问题．本文阐述了实数编码遗传算法研究的有关工作进展，讨论了算法框架及特点，对实数编码遗传算法中常用的选择、交叉和变异算子进行了比较全面的形式化描述，并介绍了其未来研究方向．     

River water quality management model using genetic algorithm

Conventional mathematical programming methods, such as linear programming, non linear programming, dynamic programming and integer programming have been used to solve the cost optimization problem for regional wastewater treatment systems. In this study, a river water quality management model was developed through the integration of a genetic algorithm (GA). This model was applied to a river system contaminated by three determined discharge sources to achieve the water quality goals and wastewater treatment cost optimization in the river basin. The genetic algorithm solution, described the treatment plant efficiency, such that the cost of wastewater treatment for the entire river basin is minimized while the water quality constraints in each reach are satisfied. This study showed that genetic algorithm can be applied for river water quality modeling studies as an alternative to the present methods.     

The Value of Biodiversity in Reserve Selection: Representation, Species Weighting, and Benefit Functions

Abstract:  The limited availability of resources for conservation has led to the development of many quantitative methods for selecting reserves that aim to maximize the biodiversity value of reserve networks. In published analyses, species are often considered equal, although some are in much greater need of protection than others. Furthermore, representation is usually treated as a threshold: a species is either represented or not, but varying levels of representation over or under a given target level are not valued differently. We propose that a higher representation level should also have higher value. We introduce a framework for reserve selection that includes species weights and benefit functions for under- and overrepresentation (number of locations for each species). We applied the method to conservation planning for herb-rich forests in southern Finland. Our use of benefit functions and weighting changed the identity of about 50% of the selected sites at different funding levels and improved the representation of rare and threatened species. We also identified a small area of additional land that would substantially enhance the existing reserve network. We suggest that benefit functions and species weighting should be considered as standard options in reserve-selection applications.     

三维铝型材挤压模多参数优化

以一个导流组合模为例,利用神经网络建立模具参数的数学模型,用遗传算法对参数优化。其中由正交法设计得到实验样本,由软试模提取模具的SDV值,将其作为优化目标。最终实验结果与优化值吻合,为建立和控制挤压模参数提供了一种行之有效的手段。     

现代内部审计营销策略

现代内部审计职业中,内部审计师面临着各种潜在冲突,在组织中的人际环境也很复杂。内部审计有必要借助营销手段,从组织的利益出发,识别、预期各级管理层的管理需求,通过内部审计服务赢得各级管理层的信任和支持,进一步建立各级管理人员甚至所有成员和内部审计师的良好关系,最终形成融洽的内部审计人际环境。内部审计师应设计并执行内部审计营销策略,这些策略包括了解客户对内部审计的看法、对董事会和高级管理层的营销、对整个组织的营销等。     

基于机器学习的电热防除冰表面温度变化趋势预测

针对飞机部件周期控制律电加热防除冰的应用,提出基于机器学习以预测电加热防除冰表面温度的变化趋势.依靠大型结冰风洞及其电加热防除冰控制系统完成防除冰试验,获得有效的试验数据,以通、断电周期为分割单元,将试验数据划分成验证集和训练集.根据电热防除冰过程的换热情况,构建样本的特征参数,利用机器学习的有监督学习方式,选择KNN近邻回归算法和局部线性加权回归算法预测温度变化率,再转换为温度,得到的温度变化与测量数据的线性相关性达到80％以上的高相似度结果,表明使用机器学习可快速预测电热防除冰部件的表面温度变化趋势,且不同的回归算法针对模型不同测温点位置的预测效果存在差异.     

富安茧丝绸清洁生产实例分析

通过对富安茧丝绸清洁生产审计的实例分析，总结出了清洁生产审计，增加了企业的经济效益，降低了生产成本，提高了产品质量，减少了污染物排放。     

基于粗糙集与遗传算法的航空器空中相撞事故因素分析

为高效准确挖掘航空器空中相撞事故与相应事故致因因素间的规律,利用事故数据,提出一种基于粗糙集和遗传算法的分析模型。首先运用粗糙集理论对SHELL模型提供的第一层次因素进行重要性程度排序,并确定其权重;然后分析事故中各环节的具体因素,结合遗传算法对这些子因素进行约简,约简时重点考虑重要度高的主因素,确定最终的事故因素及其决策规则;最后,实例分析得出导致事故的主要因素为机组违规、管制差错与违规、气象和空域。实例分析结果表明,该模型与算法能适应航空事故数据特点,能客观描述几个主要因素与事故发生之间的关联关系。     

基于遗传集对分析的空气环境质量评价

集对分析是针对确定与不确定问题进行定量分析的一种方法,而表征差异度系数i的取值,一直没有确定的方法,即使在确定了同一度、差异度、对立度之后,整个联系数仍因i的不确定取值而呈现既确定又不确定的特征。文章将遗传算法应用于联系数表达式中i值的优化求解,使得联系数确定化,并结合实例对空气环境质量进行评价,评价结果与用其它方法评价结果比较表明该方法的可行性。