Revisiting Lévy flight search patterns of wandering albatrosses, bumblebees and deer

The study of animal foraging behaviour is of practical ecological importance, and exemplifies the wider scientific problem of optimizing search strategies. Lévy flights are random walks, the step lengths of which come from probability distributions with heavy power-law tails, such that clusters of short steps are connected by rare long steps. Lévy flights display fractal properties, have no typical scale, and occur in physical and chemical systems. An attempt to demonstrate their existence in a natural biological system presented evidence that wandering albatrosses perform Lévy flights when searching for prey on the ocean surface. This well known finding was followed by similar inferences about the search strategies of deer and bumblebees. These pioneering studies have triggered much theoretical work in physics (for example, refs 11, 12), as well as empirical ecological analyses regarding reindeer, microzooplankton, grey seals, spider monkeys and fishing boats. Here we analyse a new, high-resolution data set of wandering albatross flights, and find no evidence for Lévy flight behaviour. Instead we find that flight times are gamma distributed, with an exponential decay for the longest flights. We re-analyse the original albatross data using additional information, and conclude that the extremely long flights, essential for demonstrating Lévy flight behaviour, were spurious. Furthermore, we propose a widely applicable method to test for power-law distributions using likelihood and Akaike weights. We apply this to the four original deer and bumblebee data sets, finding that none exhibits evidence of Lévy flights, and that the original graphical approach is insufficient. Such a graphical approach has been adopted to conclude Lévy flight movement for other organisms, and to propose Lévy flight analysis as a potential real-time ecosystem monitoring tool. Our results question the strength of the empirical evidence for biological Lévy flights.     

Scaling laws of marine predator search behaviour

Many free-ranging predators have to make foraging decisions with little, if any, knowledge of present resource distribution and availability. The optimal search strategy they should use to maximize encounter rates with prey in heterogeneous natural environments remains a largely unresolved issue in ecology. Lévy walks are specialized random walks giving rise to fractal movement trajectories that may represent an optimal solution for searching complex landscapes. However, the adaptive significance of this putative strategy in response to natural prey distributions remains untested. Here we analyse over a million movement displacements recorded from animal-attached electronic tags to show that diverse marine predators-sharks, bony fishes, sea turtles and penguins-exhibit Lévy-walk-like behaviour close to a theoretical optimum. Prey density distributions also display Lévy-like fractal patterns, suggesting response movements by predators to prey distributions. Simulations show that predators have higher encounter rates when adopting Lévy-type foraging in natural-like prey fields compared with purely random landscapes. This is consistent with the hypothesis that observed search patterns are adapted to observed statistical patterns of the landscape. This may explain why Lévy-like behaviour seems to be widespread among diverse organisms, from microbes to humans, as a 'rule' that evolved in response to patchy resource distributions.     

含多微网系统的主动配电网分层能量优化管理

为实现含多微网系统的主动配电网的经济效益最优,通过引入自适应权重系数来进行动态优化.构建一种主动配电网层以发电机组运行成本最低,多微网系统层以经济成本和环境成本最低的分层能量优化管理模型.采用变异、杂交和竞争策略以及Lévy飞行策略改善麻雀搜索算法,提高算法的种群多样性和收敛精度.基于所设计的多微网系统混合配置运行策略...     

网络论坛人类行为动力学实证分析

从帖子和用户两个角度对网络论坛的人类行为动力学特征进行实证统计和分析.对帖子属性的统计分析发现,帖子的回复次数、吸引的不同用户数均服从幂律分布,而帖子的浏览次数分布没有明显的规律性;帖子的浏览次数和回复次数之间存在明显的正相关性,且二者的比值大于等于10.对用户发帖、回帖行为的统计分析发现,用户发帖数、回帖数、回复的不同主帖数均服从幂律分布,说明网络论坛用户行为具有很强的异质性,大多数用户很少发帖或回帖,关注范围也比较小,只有少数活跃用户经常发帖或回帖,关注面非常广;还发现单个用户单日回帖数以及单个用户针对单个主帖的回复数也均服从幂律分布,存在少数用户在个别日子里发表大量回帖和少数用户针对少量主帖发表大量回帖的现象.这些结论对于在线用户行为建模具有重要的指导意义,也为网络舆情监控和网络水军发现提供了新的思路.     

基于分形理论的液塞长度分析

利用以自相似性为基础的分形理论对管内径为 5 0mm的水平管道的段塞流液塞长度分布进行了统计分析。结果表明 ,水平管中的液塞长度分布遵循分形统计规律 ,充分发展段的平均液塞长度为管径的 11～ 17倍 ,最大液塞长度为管径的 2 5～ 39倍 ,平均液塞长度和最大液塞长度均与气液相混合速度之间具有线性关系。试验研究还表明 ,重标度极差分析法是计算反映液塞长度波动过程具有长程相关性的Hurst指数的有效方法。Hurst指数与气液相混合速度之间具有缓降的线性关系 ,可以用Hurst指数反映出的FBM随机过程的持久性和反持久性预测液塞长度的发展趋势     

基于多蜂群的多无人机协同自适应搜索

针对多无人机(unmanned aerial vehicle, UAV)在未知海域环境下协同搜索这一重要研究课题,提出基于精英学习的多蜂群协同自适应搜索路径规划算法。首先,建立考虑飞行高度时变的无人机模型、传感器模型以及海域模型。其次,在该模型基础上建立了包括目标发现收益、期望探测收益及避碰等多目标效能函数。在考虑到UAV飞行高度动态变化时采用不同搜索策略,由于传统蜂群算法在搜索中存在适应性差、速度慢等缺点,提出基于精英学习的多蜂群算法,保证了搜索效益的最大化。最后,通过仿真实验验证了算法的有效性和实用性。     

一种基于反馈策略的自适应选择人工蜂群算法

雇用蜂觅食策略对人工蜂群算法性能有较大影响,而单一的觅食策略难以适用于所有问题的搜索空间,并且算法运行的不同阶段所适合的搜索策略也不尽相同.因此,如何为一个给定的函数优化问题选择最佳的觅食策略尤为重要.针对这一问题,提出了一种基于反馈的觅食策略自适应人工蜂群算法SSABC,该算法能够在优化过程中为一个给定的优化问题自动选择最佳的觅食策略.实验表明,与经典ABC(artificial bee colony algorithm),PSO(particle swarm optimization),DE(differential evolution),GA(genetic algorithm)算法相比,SSABC算法的寻优能力有较大提高.     

一种双种群协同多目标粒子群优化算法及应用

针对当前我国油田开采难度大、 经济效益较低等问题, 建立以利润最大化为优化指标, 以年度增油目标、 增液目标、 增注目标为约束条件的多目标油田开采优化模型, 并提出一种双种群协同多目标粒子群优化算法求解该优化模型. 该算法通过双种群协同进化策略扩大搜索空间, 提高算法的全局搜索能力, 并结合Lévy飞行保证种群多样性, 提高算法收敛效率. 实验结果表明, 该算法能有效求解油田开采优化模型, 可优选出满足目标和约束条件的结果.     

The depolymerizing kinesin MCAK uses lattice diffusion to rapidly target microtubule ends

The microtubule cytoskeleton is a dynamic structure in which the lengths of the microtubules are tightly regulated. One regulatory mechanism is the depolymerization of microtubules by motor proteins in the kinesin-13 family. These proteins are crucial for the control of microtubule length in cell division, neuronal development and interphase microtubule dynamics. The mechanism by which kinesin-13 proteins depolymerize microtubules is poorly understood. A central question is how these proteins target to microtubule ends at rates exceeding those of standard enzyme-substrate kinetics. To address this question we developed a single-molecule microscopy assay for MCAK, the founding member of the kinesin-13 family. Here we show that MCAK moves along the microtubule lattice in a one-dimensional (1D) random walk. MCAK-microtubule interactions were transient: the average MCAK molecule diffused for 0.83 s with a diffusion coefficient of 0.38 microm2 s(-1). Although the catalytic depolymerization by MCAK requires the hydrolysis of ATP, we found that the diffusion did not. The transient transition from three-dimensional diffusion to 1D diffusion corresponds to a "reduction in dimensionality" that has been proposed as the search strategy by which DNA enzymes find specific binding sites. We show that MCAK uses this strategy to target to both microtubule ends more rapidly than direct binding from solution.     

复杂网络幂律函数标度指数的估计与检验

针对度分布以及群规模分布的幂律函数,提出了基于最大似然估计的幂律分布的标度指数估计方法;针对幂律形式的层次聚集函数的标度指数估计,则采用了构建方程组的方法.此外,还引入KS检验统计量和欧几里得距离来检验新方法的估计效果.最后,通过CNN模型网络和爵士音乐家网络两个应用例,证实了新方法对3种标度指数的估计效果均好于图形方法.     

一类新的多元t-型分布

为了在椭球等高分布的基础上建立样本的理论,需将随机向量的分布推广到随机矩阵的形式.运用3种不同的方法(密度生成函数方法,逆维希特分布方法,2个独立的随机矩阵构造新的随机矩阵的方法)分别提出了矩阵Kotz-型分布,矩阵逆Γ分布和矩阵t-型分布,证明了它们是一个矩阵分布密度,并着重研究了矩阵t-型分布的有关分布性质,包括其随机表示、期望、线性组合分布及二次型等.     

基于改进蚁群算法和共用航段的搜索救援通道规划

针对战斗搜救任务场景中,空中搜索救援等待区至跳伞区之间的往返路径规划问题,提出一种基于改进蚁群算法和共用航段的搜索救援通道规划方法。首先,针对基本蚁群算法易出现局部极值及收敛速度慢等缺点,对启发函数、状态转移策略、信息素更新策略进行了改进。然后,针对单起点多目标点的路径规划问题,提出了设置分航点以生成共用航段的搜索救援通道规划方法,并以总路径长度表征任务准备负荷量与分别规划航路进行对比。实验结果表明,在本文测试环境下,改进蚁群算法规划的路径长度分别缩减15.4%和14.2%,搜索救援通道的任务准备负荷量减少25.4%。所提出的搜索救援通道规划方法有一定的理论和应用价值。     

Trail geometry gives polarity to ant foraging networks

Pheromone trails are used by many ants to guide foragers between nest and food. But how does a forager that has become displaced from a trail know which way to go on rejoining the trail? A laden forager, for example, should walk towards the nest. Polarized trails would enable ants to choose the appropriate direction, thereby saving time and reducing predation risk. However, previous research has found no evidence that ants can detect polarity from the pheromone trail alone. Pharaoh's ants (Monomorium pharaonis) produce elaborate trail networks throughout their foraging environment. Here we show that by using information from the geometry of trail bifurcations within this network, foragers joining a trail can adaptively reorientate themselves if they initially walk in the wrong direction. The frequency of correct reorientations is maximized when the trail bifurcation angle is approximately 60 degrees, as found in natural networks. These are the first data to demonstrate how ant trails can themselves provide polarity information. They also demonstrate previously unsuspected sophistication in the organization and information content of networks in insect societies.     

基于无标度网络的最大度二分度搜索策略

在复杂网络研究领域的现实网络中,大多数实际网络的分布都呈现幂律分布的无标度网络,因此在研究这些网络搜索算法的过程中,如何在同一个网络的不同网络结构中采用更为有效的搜索算法成为在网络搜索算法策略研究的重点.基于最大度的搜索算法在复杂网络的网络结构中更适用于幂律分布指数区间内的无标度网络,因此为了更加充分地利用无标度网络的度分布特性,将最大度搜索策略与二分度策略有效结合进行搜索,从而使得相关搜索策略存在的问题得以改善,并得到高效的搜索结果 .文章从理论分析和实验结果证明了这一点.     

基于Mike Farmer委托驱动模型的研究

Mike-Farmer微观模型是功能强大的委托驱动模型,能再现很多经典的统计规律.本文介绍了Mike-Farmer委托驱动模型的构建过程,Mike-Farmer委托驱动模型生成的收益率,发现收益率在不同时间尺度下遵循幂律分布,服从负三次方定律.以Mike-Farmer委托驱动模型为平台,进行收益率幂律分布和波动率聚簇效应的成因研究,发现收益率的幂律分布和市价订单委托价格的概率分布相关,而波动率的聚簇效应与订单委托价格时间序列的时间记忆性保持一致性.最后简要介绍了模型的应用前景.     

螺旋桨式小型无人机可用功率计算研究

简要分析总结了螺旋桨式活塞发动机功率特性的相关理论及经验公式,以此为基础,研究了滑移现象和机身对螺旋桨效率的影响问题,提出了一种新的计算螺旋桨式无人机可用功率的方法。结果表明：螺旋桨式无人机若飞行高度保持一定,可用功率、螺旋桨效率与巡航速度成正比;若巡航速度保持一定,可用功率、螺旋桨效率与飞行高度成反比。     

基于均值的云自适应鸟群优化算法

针对鸟群算法(bird swarm algorithm,BSA)在求解高维复杂优化问题时,存在收敛速度慢、寻优精度低等缺点,提出了一种基于均值的云自适应鸟群优化算法(a cloud adaptive bird swarm optimization algorithm based on mean,CAMBSA)。通过云理论引入惯性权重修正鸟群觅食策略,同时引入"均值"的概念,修改鸟群觅食策略中的"认知部分"和"社会部分",有利于协调种群全局搜索能力,避免算法陷入早熟;为了使算法在迭代后期具有较好的多样性,采用混沌扰动。仿真试验表明,所提出的算法具有较好的收敛速度和寻优精度。     

基于区域失衡子空间的领先NSGAII算法

针对传统进化算法求解多目标优化问题时存在计算量大、难以平衡收敛速度和种群分布均匀性的问题,本文提出了一种基于区域失衡子空间的领先NSGAII算法(NSGAII-URS).首先,基于NSGAII算法,结合局部搜索算法,在每次遗传过程中添加种群领先解解集,引导种群快速收敛;然后,将非支配解所在的目标空间均匀划分,提出稀疏子空间和空闲子空间的概念,通过基于稀疏度的局部搜索策略对失衡子空间优化,进一步提升种群分布的均匀性.我们将本文方法与其他5种先进的多目标进化算法比较,通过基准测试函数进行验证,并采用反世代距离(IGD)和超体积(HV)两个通用指标进行性能评价.实验结果表明,该算法在解的分布性和收敛性方面明显优于对比的其他多目标优化算法.     

低温下存在外磁场的一维各向异性海森堡铁磁体的磁性质(英文)

运用自旋波理论和格林函数方法,研究了在单场有各向异性自旋交换作用的、自旋为S=1/2的一维海森堡铁磁体的磁性质.运用霍斯坦因-普里马可夫变换得到近似哈密顿量.发现在低温区,外磁场和各向异性对关联函数和磁化率产生极大的影响.而在弱磁场的情况下,倒关联长度kx和ky不依赖于温度,并且各向异性对kx相比对ky的影响较弱.所得结果与相应的实验结果和理论值符合得很好.     

材料梯度、几何非线性和高阶剪切效应对压电纳米梁力电特性的耦合影响

目的 压电材料由于其优越的力电性能在 MEMS / NEMS 得到广泛应用。 针对目前对压电纳米结构力电响应 计算忽视了微/ 纳米尺度下压电材料的挠曲电效应以及剪切效应问题,提出了囊括挠曲电效应和压电效应的功能 梯度压电(Functionally Graded Piezoelectric,FGP)纳米梁数学模型。 纳米梁由压电层和功能梯度层组成,其中功能 梯度层材料遵循幂律指数分布。 方法 首先,基于 Reddy 三阶剪切变形理论、非局部应变梯度理论(NGST)和哈密顿 原理,并考虑了 Von Kármán 几何非线性,获得了梯度梁的非线性力电耦合控制方程及相应的边界条件;然后结合 Runge-Kutta 方法和 Galerkin 方法得到了简支梁的线性和非线性固有频率以及均方根(RMS)输出电压。 结果 提出 的模型与已有文献结果对比十分吻合。 此外,数值结果表明挠曲电常数、压电常数、应变梯度尺度参数、非局部参 数、幂律指数和几何尺寸对非线性固有频率和均方根电压有影响。 结论 相较于 Euler 梁理论和 Timoshenko 梁理 论,采用 Reddy 三阶剪切变形理论得到的梯度梁在相同质量下具有更高的 RMS 电压,同时会降低非线性固有 频率。