Acquired Predator Recognition by Fathead Minnows: Influence of Habitat Characteristics on Survival

In this study we conditioned fathead minnows (Pimephales promelas) to recognize the odor of a perch (Perca flavescens) by exposing them to perch odor coupled with minnow alarm cue. We then staged encounters between the predator and prey in order to assess whether the predator odor training had any effect on survival of the prey. We tested for a survival effect in the presence and absence of shelter. Our results indicate that fish trained with alarm signals to recognize predators gained a survival benefit during staged encounters with a predator and that habitat characteristics influenced the survival of conditioned fish.     

融合黄金正弦混合变异的自适应樽海鞘群算法

针对基本樽海鞘群算法收敛速度慢、收敛精度低、易陷入局部最优的缺点,提出了一种融合黄金正弦混合变异的自适应樽海鞘群算法AGHSSA（Adaptive Salp Swarm Algorithm with Golden Sine Algorithm and Hybrid Mutation）。该算法引入了自适应变化的权重因子以加强精英个体的引导作用,提升收敛速度与精度。通过黄金正弦算法优化领导者位置更新方式,增强算法的全局搜索和局部开发能力。融合邻域重心反向学习与柯西变异对最优个体位置进行扰动,提升算法跳出局部最优的能力。通过对12个基准测试函数进行仿真实验来评估改进算法的寻优能力,实验结果表明,改进算法能显著提升寻优速度和精度,并且具备较强的跳出局部最优的能力。     

铜基仿金合金

为了寻找金的代用品,长期以来研究者竞相研制铜基仿金合金以满足制造较大的金色艺术品。文中阐述了研制铜基仿金合金的原理及其金色度和抗变色性的测试方法,分别叙述了铝、锌、锡、铟、硅、镍、稀土等元素对合金金色度和抗变色性的影响。鉴于各研究者得出的合金化学成分相差极大,最后提供了较为合理的铜基仿金合金的化学成分。     

Impoverishment of YOY‐fish assemblages by intense commercial navigation in a large Lowland river

Navigation‐induced physical forces have been suggested to modify the structure of riverine fish assemblages by impeding especially the recruitment of littoral bound species. To investigate the effect of vessel frequency on fish, we compared the composition and seasonal succession of young‐of‐the‐year (YOY) fish assemblages in three similarly degraded river reaches differing in average vessel passages (2, 6 and 41 per day). Fish were caught by electrofishing biweekly between May and September. Multivariate tests were used to analyse differences between YOY‐fish assemblages and hurdle regression models applied to determine abiotic factors predicting fish occurrence and abundance. Roach (Rutilus rutilus) and perch (Perca fluviatilis) densities were compared. Roach larvae remain in the littoral zone while perch larvae shift to the pelagic zone immediately after hatch. YOY‐fish assemblage structure substantially changed along the traffic intensity gradient. In the high traffic intensity reach, species number and total fish density were markedly reduced compared to the other reaches. Roach densities were lowest in the high traffic intensity reach whereas perch densities did not decline along the gradient. Hurdle regressions confirmed a stronger effect of commercial navigation traffic intensity on roach than on perch. The total zooplankton biomass was highest in the high traffic intensity reach. Our results provide empirical evidence that intensive commercial navigation impoverishes fish assemblages in width‐restricted waterways. They underlined that in particular those species that have their first nursery habitats in shoreline areas were more affected by intensive commercial navigation than species whose larvae live predominantly pelagic. The results indicate that the negative effect of intensive navigation on riverine fish results primarily from the navigation‐induced hydraulic disturbances along the banks. Therefore, mitigation of navigation‐induced hydraulic forces is required to prevent degradation of fish communities in waterways. Copyright © 2010 John Wiley & Sons, Ltd.     

一种基于差异演化的协同粒子群优化算法

提出一种协同进化PSO算法,用于保持粒子种群的多样性并避免发生“早熟”的问题．该方法采用两个不同的分群;其中分群一的粒子采用标准PSO算法进行搜索寻优,分群二的粒子采用差异演化算法进行搜索和寻找最优解．在搜索过程中,如果标准PSO算法的适应度变化率低于一个阈值,则按照黄金分割率用分群二中的若干优势粒子取代分群一中的劣势粒子．用所提出的PSO算法和标准PSO算法对4种常用函数进行优化．结果表明,该粒子群优化算法比标准粒子群优化算法更容易找到最优解,而且优化效率和优化性能明显提高．     

一种基于案例推理的报价决策模型

在建筑行业的投标报价过程中,如何确定对最终投标报价决策影响较大的几项因素以及如何确定这些因素与最终投标报价决策之间的关系是一个棘手的问题。为此提出了基于案例推理的报价决策模型,并研究了该模型的可行性,使报价过程规则的自动提取成为可能。     

反舰导弹航路规划的OACRR-PSO算法

为了提高反舰导弹航路规划算法的搜素效率,从几何学角度对航路规划空间进行了研究,在将功能区域概念融入 逆向航路规划的过程中发现了功能区域的几何学渐变规律,据此提出功能区域簇作为其物理载体.将功能区域簇引入粒子群优化(Particle swarm optimization, PSO)算法,提出了功能区域簇实时约束(Operational area cluster real-time restriction, OACRR)的PSO算法(OACRR-PSO).为了便于表示功能区域簇,采用航路极坐标编码方式.与传统的PSO算法不同的是,考虑到 粒子中分量之间的关联性,该算法在优化过程中并不是对粒子的整个速度分量同时进行更新,而是引入一种分步递归进化 策略对粒子的分量逐步进行更新.在粒子的更新过程中,使用功能区域簇来实时限定粒子位置分量的准确更新范围,使得 算法搜索空间逐步减小,从而加速算法收敛.仿真实验结果表明,分步递归进化策略能够非常显著地提高算法的全局搜索 性能,并且算法收敛速度快、稳定性好.     

紫苏调和油的黄金比例模型及生产配方

以中国营养学会提出的黄金比例为标准,分析国内油脂资源以及居民饮食习惯,建立以紫苏油为主的黄金比例调和油的数学模型,给出以紫苏油为主体的黄金比例调和油的配方,及其成本分析,另外根据不同的消费群体,修改模型参数,就可以得到适合的配方.     

均值黄金分割离差双选优化模型研究

在提出黄金分割离差的基础上,构建了均值黄金离差双选优化模型。在评价指标数目从少到多的过程中,评价指标体系将呈现由劣变优再变劣的过程,这个规律符合黄金分割律的应用。以岳阳石化企业节约用水考核为例,优化了岳阳石化企业节约用水考核指标体系,结果显示优化后的指标体系科学性、合理性与可操作性较强。     

多峰函数优化的黄金分割斐波那契树优化算法

针对多峰函数优化问题，基于斐波那契树优化算法，结合黄金分割思想，提出一种黄金分割斐波那契树优化算法.该算法利用斐波那契树优化算法全局局部交替寻优特性，通过在寻优过程中对优化问题解空间进行黄金分割比例压缩，从而提高算法局部搜索能力与小峰值搜索能力.多峰函数优化的仿真结果表明，该算法多峰优化能力强、速度快、精度高.