基于GPR-TOPSIS方法的充填配比多目标多属性优化

为获得某金矿尾砂胶结充填材料最优配比,基于试验结果,以海水比例、灰砂比和料浆质量浓度为输入参数,以充填体强度、塌落度及泌水率为输出参数,建立了充填配比与其响应量的高斯过程回归模型,分析了不同因素对充填性能的影响程度;采用遗传算法对高斯过程回归模型进行多目标参数优化,获得了Pareto非劣解,在此基础上,引入多属性决策的TOPSIS法对Pareto非劣解进行方案优选,确定了充填最优配比。研究结果表明:高斯过程回归模型相对误差值均小于6%,可靠性高;灰砂比及料浆质量浓度对充填性能影响较为显著,采用海水作为充填水源将降低充填体的强度;经优化后的充填配比与试验结果相符。     

基于情景构建的应急预案体系优化策略及方法

为了进一步优化我国现有应急预案体系,从应急管理实践中分析梳理出4方面问题,包括:“在指导理念上依然没有充分体现应急准备的理念”“应急预案体系在微观、中观和宏观层面依然存在结构性问题”“应急预案的内容存在‘概念性’内容较多的情况,导致操作性和针对性不强”“预案动态管理滞后,持续改进机制尚未形成”;针对现存问题,提出基于情景构建的优化策略和方法,认为“情景构建”不但可以指导编制者分析应急需求、明确应急目标、规划应急程序,有效支撑应急预案的编制,而且可以派生出“基于情景链条的预案衔接策略”“基于任务协同的预案衔接策略”“基于资源约束的预案衔接策略”,进而从微观层面上推进预案体系的优化。研究结果可以作为各级政府和企业应急预案体系构建的参考和借鉴。     

公路隧道火灾发生位置与人群疏散通道仿真研究

利用EXODUS建立隧道的仿真场景,确定疏散人群仿真参数,并将出口工效OPS作为评价疏散效率的指标,分析不同火灾发生位置对疏散时间的影响。采用K-means算法分别对火灾发生位置和人群疏散通道位置进行聚类,并建立基于两者影响下的出口工效模型,通过对该模型求偏导,得出隧道火灾发生位置和人群疏散通道选择之间的关系。研究结果表明:火灾发生位置越接近人行横通道,疏散时间波动越大,人行横通道和隧道入口的疏散时间随人群疏散区域分界线变化,当火灾发生距人行横通道20~110 m时,变化明显,当距140~350 m时,变化平稳;出口工效OPS总体呈现不稳定的阶梯状变化趋势;火灾发生位置和人群疏散通道的最优位置呈线性递减关系。研究结果可应用于隧道应急指挥中心管理人员制定有效疏散路径和采取诱导分流人群措施。     

气固两相流90°弯管抗冲蚀结构优化

为了提高天然气输送管道90°弯管的耐磨性能,提出了1种三段弯曲式弯管,通过对弯管弯曲段进行三段式改进来减小弯管中二次流的大小,优化弯管内的流场,改善弯管的冲蚀磨损状况。利用COMSOL仿真软件建立三段式弯管模型,并以弯管弯曲段和出口段二次流平均值之和最小为优化目标,在约束条件下凭借COMSOL中的COBYLA优化算法得到了最优管形;用Fluent对优化后的三段式弯管进行冲蚀数值模拟并与一段式弯管的模拟结果进行对比分析。研究结果表明:与一段式90°弯管相比,优化后的三段式弯管流场更加平稳,其弯曲段的二次流强度大幅降低,弯管壁面的冲蚀磨损程度得到较大的改善。     

Hough变换在PCB在线检测系统的应用

在印刷电路板(PCB)视觉检测系统中,图象边缘提取的质量和对瑕疵图象边缘的快速而准确的识别是达到实时检测的关键因素,Hough变换是一种应用非常广泛的图像边缘检测技术,运用快速的Hough变换方法,来完成PCB检测的圆心定位和半径测定,并通过针时PCB在线检测的具体应用情况加以改进并应用,实验分析表明,该算法在PCB在线检测的可行性和优越性.图5,参5.     

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.     

米曲霉产氨基酰化酶条件及部分酶学性质研究

通过单因子和多因子摇瓶正交优化试验,确定了米曲霉液态发酵产氨基酰化酶的最佳发酵条件.优化发酵培养基组成(ρ/gL-1):葡萄糖40,蔗糖10,可溶性淀粉20,蛋白胨2.5,马铃薯液1000mL,pH自然.培养基装量50mL/250mL三角瓶,接种量4%.培养温度30℃,转速100r/min,发酵时间42h.每50mL培养物的总酶活由优化前的2627u提高到7338u,是优化前的2.79倍.研究了米曲霉氨基酰化酶的部分酶学性质.该酶催化反应的最适pH为7.0,最适温度为40℃,低浓度的Co2 (5×10-4mol/L)对酶活激活作用显著.图5表2参8     

Incorporating the Effects of Socioeconomic Uncertainty into Priority Setting for Conservation Investment

Abstract:  Uncertainty in the implementation and outcomes of conservation actions that is not accounted for leaves conservation plans vulnerable to potential changes in future conditions. We used a decision-theoretic approach to investigate the effects of two types of investment uncertainty on the optimal allocation of global conservation resources for land acquisition in the Mediterranean Basin. We considered uncertainty about (1) whether investment will continue and (2) whether the acquired biodiversity assets are secure, which we termed transaction uncertainty and performance uncertainty, respectively. We also developed and tested the robustness of different rules of thumb for guiding the allocation of conservation resources when these sources of uncertainty exist. In the presence of uncertainty in future investment ability (transaction uncertainty), the optimal strategy was opportunistic, meaning the investment priority should be to act where uncertainty is highest while investment remains possible. When there was a probability that investments would fail (performance uncertainty), the optimal solution became a complex trade-off between the immediate biodiversity benefits of acting in a region and the perceived longevity of the investment. In general, regions were prioritized for investment when they had the greatest performance certainty, even if an alternative region was highly threatened or had higher biodiversity value. The improved performance of rules of thumb when accounting for uncertainty highlights the importance of explicitly incorporating sources of investment uncertainty and evaluating potential conservation investments in the context of their likely long-term success.