A comparison of swarm intelligence algorithms for structural engineering optimization

This paper compares the performance of three swarm intelligence algorithms for the optimization of hard engineering problems. The algorithms tested were bacterial foraging optimization (BFO), particle swarm optimization (PSO), and artificial bee colony (ABC). Besides the regular BFO, two other variants reported in the literature were also included in the study: adaptive BFO and swarming BFO. Both PSO and ABC were tested using the regular algorithm and variants that include explosion (mass extinction). Three optimization problems of structural engineering were used: minimization of the cost of a welded beam, minimization of the construction cost of a pressure vessel, and minimization of the total weight of a 10‐bar plane truss. All problems are strongly constrained. The algorithms were evaluated using two criteria: quality of solutions and the number of function evaluations. The results show that PSO presented the best balance between these two criteria. For the optimization problems approached in this paper, we can also conclude that the explosion procedure resulted in no significant improvements. Copyright © 2012 John Wiley & Sons, Ltd.     

高光谱技术结合改进LSSVM的大米脂肪酸检测方法

目的:解决食品企业现有大米品质检测方法存在的准确性低和效率差等问题。方法:基于高光谱数据采集系统,提出一种结合改进细菌觅食算法和最小二乘支持向量机的贮藏大米品质快速无损检测方法。通过改进的细菌觅食算法对最小二乘支持向量机超参数(正则化参数和核参数)进行寻优,实现贮藏大米品质的快速无损检测。通过试验分析其性能。结果:所提方法可以实现贮藏大米脂肪酸含量的快速无损检测,决定系数为0.940 5,均方根误差为0.543 5,平均检测时间为1.12 s。结论:所提检测方法具有较高的检测性能,可用于大米品质的鉴别与检测。     

The central executive as a search process: Priming exploration and exploitation across domains.

The trade-off between exploration and exploitation is common to a wide variety of problems involving search in space and mind. The prevalence of this trade-off and its neurological underpinnings led us to propose domain-general cognitive search processes (Hills, Todd, & Goldstone, 2008). We propose further that these are consistent with the idea of a central executive search process that combines goal-handling across subgoal hierarchies. In the present study, we investigate 3 aspects of this proposal. First, the existence of a unitary central executive search process should allow priming from 1 search task to another and at multiple hierarchical levels. We confirm this by showing cross-domain priming from a spatial search task to 2 different cognitive levels within a lexical search task. Second, given the neural basis of the proposed generalized cognitive search process and the evidence that the central executive is primarily engaged during complex tasks, we hypothesize that priming should require search in the sense of a self-regulated making and testing of sequential predictions about the world. This was confirmed by showing that when participants were allowed to collect spatial resources without searching for them, no priming occurred. Finally, we provide a mechanism for the underlying search process and investigate 3 alternative hypotheses for subgoal hierarchies using the central executive as a search process model (CESP). CESP envisions the central executive as having both emergent and unitary processes, with one of its roles being a generalized cognitive search process that navigates goal hierarchies by mediating persistence on and switching between subgoals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

一种基于竞选领导策略的改进粒子群算法

针对标准粒子群算法由于粒子多样性的大量丧失而导致的算法易陷入局部最优解,收敛精度不高的问题,提出一种基于竞选领导策略的改进粒子群算法,该算法在全局最优粒子的领导能力丧失时,通过引进细菌觅食算法的趋化算子对精英粒子进行优化,然后选出更具领导能力的粒子作为新的领导粒子来带领种群跳出局部最优解,以增强算法的全局搜索能力。通过四个典型函数的测试,结果表明改进算法在较好保留了标准粒子群算法快速收敛优点的前提下,有效地预防了早熟现象的产生,提高了收敛精度。     

递推最小二乘法与细菌觅食算法相结合的光伏阵列MPPT控制方法

要： 针对复杂应用环境下光伏阵列的P-V输出特性曲线呈现多峰值的问题,提出了一种递推最小二乘法与细菌觅食算法相结合的光伏阵列最大功率点跟踪算法,分析了复杂应用环境对光伏最大功率点跟踪控制的影响。针对状态变化造成的多功率极值问题,首先运用递推最小二乘法进行滤波预处理,再采用细菌觅食优化算法准确跟踪到了全局最大功率点。MPPT仿真和试验结果均表明,该算法成功摆脱了局部最优解的约束,可准确跟踪阵列全局最大功率点且有效抑制了电磁噪声。与单纯的细菌觅食算法相比,本文算法精度更高,为光伏阵列最大功率点跟踪提供了一种实现方法。     

Effects of rumen fill on short-term ingestive behavior and circulating concentrations of ghrelin, insulin, and glucose of dairy cows foraging vegetative micro-swards

The objective of this study was to investigate changes in foraging behavior, hunger-related hormones, and metabolites of dairy cows in response to short-term variations in rumen fill (RF). The effect of RF on intake rate, jaw movements, bite rate and dimensions, and concentrations of plasma ghrelin, and serum insulin and glucose were measured in 4 rumen-cannulated lactating dairy cows (612 ± 68 kg, empty live weight; 237 ± 29 d in milk) foraging micro-swards of vegetative orchardgrass (Dactylis glomerata L.). The treatments compared were the removal of different proportions of total rumen contents: 1.00 (RF0), 0.66 (RF33), 0.33 (RF66), or 0 (RF100). Treatments were randomly applied 2 h before foraging sessions in a 4 × 4 Latin square design. Micro-swards were weighed before and after foraging sessions. Cows were allowed to take a maximum of 15 bites with no time restriction. Eating time, intake rate, total jaw movements, and bite mass, depth, area, and rate were determined. Plasma was analyzed for ghrelin and serum for insulin and glucose immediately before and 2 h after the treatments were applied. Intake rate, bite mass, and bite area increased, whereas bite depth decreased as RF decreased. The RF did not affect bite rate or total jaw movements. Decreasing RF resulted in increased plasma concentrations of ghrelin and tended to increase serum insulin, with reduced concentrations of serum glucose. Incremental variation in plasma ghrelin and serum insulin correlated with bite depth and mass, whereas changes in serum glucose correlated with intake rate, bite area, depth and mass, as well as with herbage intake per jaw movement. The present study elucidates some of the underlying endocrine physiology of cattle with short-term temporal variations of RF and their effects on some components of foraging behavior.     

BF-PSO算法在电网CPS标准经济考核中的应用

对于如何减少调度控制性能标准CPS(control performance standard)的考核罚款及机组的运行成本,提出了一种基于混合粒子群优化的细菌觅食算法BF-PSO(bacterial foraging-particle swarm optimization)自整定PI控制。文中首先详细介绍了粒子群算法和细菌觅食算法的基本原理,在结合两种算法的基础上,以发电成本和考核罚款之和最小为目标提出了一种新的PI整定方法,通过Matlab的Simulink仿真软件建立了一个多区域电力系统的CPS考核系统模型,对优化前后的控制效果进行了对比,仿真结果说明新的控制方法在保持CPS控制效果的基础上,实现了对电网的经济调度。     

Reviewing the world's edible mushroom species: A new evidence-based classification system

Wild mushrooms are a vital source of income and nutrition for many poor communities and of value to recreational foragers. Literature relating to the edibility of mushroom species continues to expand, driven by an increasing demand for wild mushrooms, a wider interest in foraging, and the study of traditional foods. Although numerous case reports have been published on edible mushrooms, doubt and confusion persist regarding which species are safe and suitable to consume. Case reports often differ, and the evidence supporting the stated properties of mushrooms can be incomplete or ambiguous. The need for greater clarity on edible species is further underlined by increases in mushroom-related poisonings. We propose a system for categorizing mushroom species and assigning a final edibility status. Using this system, we reviewed 2,786 mushroom species from 99 countries, accessing 9,783 case reports, from over 1,100 sources. We identified 2,189 edible species, of which 2,006 can be consumed safely, and a further 183 species which required some form of pretreatment prior to safe consumption or were associated with allergic reactions by some. We identified 471 species of uncertain edibility because of missing or incomplete evidence of consumption, and 76 unconfirmed species because of unresolved, differing opinions on edibility and toxicity. This is the most comprehensive list of edible mushrooms available to date, demonstrating the huge number of mushrooms species consumed. Our review highlights the need for further information on uncertain and clash species, and the need to present evidence in a clear, unambiguous, and consistent manner.     

异型断面型钢冷却预弯模型及其算法的研究与应用

针对异型断面钢轨在冷床不受约束条件下冷却后产生弯曲变形的问题,需提前进行反向预弯。采用先进控制理论,对钢轨预弯模型及算法进行了研究,采用工业相机对冷床上轧件进行实时扫描,获得钢轨实际弯曲数据,采用最小二乘算法,回归得到模型参数;采用细菌觅食方法,选取控制系统最优调节参数。经过仿真计算及现场生产试验,表明该模型及算法能有效提高钢轨平直度;同一批次轧件随算法应用次数的增加,轧件弯曲度减小;在算法应用前期,轧件弯曲度减小的速度明显比后期要快,后期轧件弯曲度改变较稳定。     

随机扰动下多源群体觅食系统建模与仿真

群集智能是指复杂的集体智能来自简单个体之间以及个体同环境之间的相互作用. 通常对群集智能的研究主要借助于群居生物行为的观察. 蚁群觅食行为是研究简单个体产生复杂行为的一个典型的例子. 首先建立群体觅食宏观序参数模型. 模型考虑了食物源的量和分布以及环境噪声对个体决策的随机影响. 给出2个食物源下系统模型的数值解,表明在较大的噪声影响下,系统有一定的概率会脱离最优解,到达次优解. 在Starlogo仿真平台下的实验结果表明,觅食蚂蚁的数量同任务完成时间以及碰撞频率之间呈现出幂指数关系. 这对自组织系统和群集智能的研究有一定的理论意义,并可以用来指导设计更加有效、适应、可靠的智能系统.