面向山地徒步应急救援路径规划的改进蚁群算法研究

当消防事故发生在无明显道路或道路稀疏的野外复杂山区时,如何在复杂山地环境中规划安全、快速通过的路线至关重要。针对蚁群算法在复杂山地路径规划中容易陷入局部最优以及搜索时间较长的问题,本文提出一种适用于细粒度野外山地环境的徒步应急救援路径规划算法。本文首先根据已有文献分析地表信息与人类运动速度之间的关系,综合地表灌木盖度与地形坡度因素设计寻优算法的目标函数和启发函数;接着采用定向范围视野的蚂蚁搜索方式,决定蚁群算法寻优过程中每一步的网格选择;最后采用拉普拉斯分布调整初始信息素、添加隔离信息素、融合遗传算子与分组更新常规信息素的方法改进蚁群算法。将算法应用到400×400、1000×1000、5000×5000、10 000×10 000网格数的野外山地环境进行实验对比,实验结果表明,采用定向范围视野与优化启发函数的各蚁群算法在四组实验中均能得到可行路径,验证了方法的有效性;本文算法求解的路径质量优于另外三种算法,在四组实验中分别提高了0.52%～4.95%、4.71%～5.39%、2.26%～13.11%、3.84%～9.16%;此外,在野外三维山地环境中,定向范围视野的搜索方式缩减了搜索...     

基于粒子群算法的浮筒配置优化问题的研究

针对传统的验证法在解决浮筒配置问题中存在的计算量大、计算时间长、工作重复性强等缺点,提出了一种将浮筒纵向位置配置和浮筒充气量综合考虑、一体优化的方法。文章将各种合理性校验准则作为约束条件,通过逼近沉艇起浮瞬间和浮起后的平衡状态,来求取各对浮筒的纵向位置和充气量,将浮筒配置问题转换为一个多目标、多约束的最优化问题。在此基础上,根据粒子群优化算法的特点,提出了一种双向搜索策略,来求解浮筒配置优化问题。这种方法简单实用,计算时间短,无需人工干预,算法运行一次可获得多组配置方案供决策人员选择。算例表明用这种方法来解决浮筒配置问题是可行的、有效的。     

Die neue EG‐Wasserrahmenrichtlinie: Bewertung der chemischen und ökologischen Qualität von Oberflächengewässern

The New EC Framework Water Directive: Assessment of the Chemical and Ecological Status of Surface Waters The main objective of the draft EC Framework Water Directive is the good quality of all surface waters. The directive provides for an assessment of the chemical status of surface waters (EU‐wide valid environmental quality standards for approximately 30 priority substances) and a five‐stage ecological classification of waters, comprising the stages high, good, moderate, poor, and bad. The starting point for the assessment are the reference conditions, which are defined as corresponding to high water quality and characterising a water status with no significant anthropogenic impact. The reference sites in the various water body types are to be selected using hydromorphological and physico‐chemical parameters and subsequently characterised by means of biological parameters. For surface waters, three groups of characteristics are provided for, namely: 1. with priority the biology – in the case of surface waters – with the four elements phytoplankton, macrophytes/phytobenthos, benthic invertebrate fauna, and fish fauna; 2. supporting the hydromorphology, e.g. flowing waters with the three elements hydrological regime, river continuity, and morphological conditions and 3. supporting the physico‐chemical conditions with the three elements general conditions, specific synthetic pollutants, and specific non synthetic pollutants (other than the priority substances of the chemical status).     

基于PSO-BP神经网络的地表下沉系数选取研究

针对BP神经网络自身收敛速度慢、容易陷入局部极小点的缺点,引入粒子群优化算法,建立地表下沉系数的PSO-BP选取模型。利用粒子群算法反复优化BP网络的权值和阈值,将其作为BP网络的初始值,并将上覆岩层岩性、开采深厚比、松散层厚度、覆岩中坚硬岩层所占比例、是否为重复采动和顶板管理方法等主要影响因素作为网络输入,进行BP算法,直至网络达到训练指标。利用实测资料数据,建立PSO-BP预计模型,并同普通BP神经网络预计结果对比。结果表明：PSO-BP神经网络不仅训练速度快,而且预测精度明显提高,该模型对地表下沉系数选取具有一定的应用价值。     

粤北青嶂山岩体江头矿区铀矿微区矿物学、年代学特征及其成矿动力背景制约

粤北诸广和贵东是华南最重要的两个花岗型铀矿密集区,青嶂山(龙源坝)岩体位于两者之间,是华南花岗岩型铀矿研究薄弱地区。江头铀矿区地处青嶂山岩体北部与南雄断陷盆地的结合部位,该矿区的铀成矿年代学研究几为空白。本文通过电子探针方法研究了青嶂山岩体、及与该岩体密切相关的江头矿区中的铀矿物微区矿物学特征,获得岩浆成因的晶质铀矿与热液成因的沥青铀矿的U-Th-Pb化学年龄,探讨了华南铀成矿作用动力学背景及成矿地质体。研究表明:青嶂山岩体粗粒斑状黑云母花岗岩和中粒斑状黑云母花岗岩中的铀矿物主要有晶质铀矿、铀石,部分晶质铀矿存在明显铀释放的特征,其晶质铀矿化学年龄分别为246.8±8.8Ma、161.5±8.0Ma,与前人获得的锆石U-Pb年龄结果在误差范围内一致,分别代表了区内印支期与燕山期花岗岩体的成岩年龄,表明在南雄断陷盆地形成之前,青嶂山岩体与诸广岩体可能为一有机整体,有着相同的成岩、成矿环境。江头矿区矿石中铀矿物主要为沥青铀矿,伴有少量钛铀矿、铀石等,沥青铀矿化学年龄分别为121.3±9.8Ma、98.8±8.0Ma、73.2±8.8Ma,分别代表区内3期铀成矿作用的时代,结合华南中生代以来构造运动特征,认为区内铀成矿作用是受中-新生代盆地边缘深大断陷活动、产铀花岗岩体分布的双要素成矿动力学背景制约,青嶂山岩体应与诸广、贵东岩体具有相似的找矿前景。     

珠江口盆地荔湾凹陷上渐新统—早中新统物源特征及其对沉积充填的影响

利用化学蚀变指数法恢复物源区的风化历史及沉积物通量是一种经济实用、行之有效的方法。前人对珠江口盆地荔湾凹陷对应物源区的研究相对薄弱。本文通过对区内岩心测试数据进行化学蚀变指数分析,恢复晚渐新世—早中新世物源区的风化历史,并进行沉积物通量的估算,在此基础上探讨物源特征对研究区内沉积充填的控制作用。研究表明,晚渐新世研究区对应物源区经历了强烈风化阶段,该阶段产生的丰富的沉积物供给是研究区西北部快速进积、规模壮观的陆架边缘三角洲及斜坡重力流沉积体系发育的重要控制因素之一;早中新世,西北物源区风化减弱,沉积供给减少,但研究区东部沉积物供应较西部要充分得多,表明早中新世,研究区南部除了来自西北部的主要物源外,局部物源对该时期的沉积具有重要影响;推测东部物源(东部古隆起、兴宁古隆起)的突然复活是促进研究区东部早中新世沟槽形成发育的重要原因之一。在超深水区进行沉积物源区的研究中,这种半定量的方法对盆内局部物源的确定具有重要的指示意义。     

Time-frequency decomposition of seismic signals via quantum swarm evolutionary matching pursuit

Matching pursuit belongs to the category of spectral decomposition approaches that use a pre-defined discrete wavelet dictionary in order to decompose a signal adaptively. Although disengaged from windowing issues, matching point demands high computational costs as extraction of all local structure of signal requires a large size dictionary. Thus in order to find the best match wavelet, it is required to search the whole space. To reduce the computational cost of greedy matching pursuit, two artificial intelligence methods, (1) quantum inspired evolutionary algorithm and (2) particle swarm optimization, are introduced for two successive steps: (a) initial estimation and (b) optimization of wavelet parameters. We call this algorithm quantum swarm evolutionary matching pursuit. Quantum swarm evolutionary matching pursuit starts with a small colony of population at which each individual, is potentially a transformed form of a time-frequency atom. To attain maximum pursuit of the potential candidate wavelets with the residual, the colony members are adjusted in an evolutionary way. In addition, the quantum computing concepts such as quantum bit, quantum gate, and superposition of states are introduced into the method. The algorithm parameters such as social and cognitive learning factors, population size and global migration period are optimized using seismic signals. In applying matching pursuit to geophysical data, typically complex trace attributes are used for initial estimation of wavelet parameters, however, in this study it was shown that using complex trace attributes are sensitive to noisy data and would have lower rate of convergence. The algorithm performance over noisy signals, using non-orthogonal dictionaries are investigated and compared with other methods such as orthogonal matching pursuit. The results illustrate that quantum swarm evolutionary matching pursuit has the least sensitivity to noise and higher rate of convergence. Finally, the algorithm is applied to both modelled seismograms and real data for detection of low frequency anomalies to validate the findings.     

湖泊沉积物中元素相态的连续提取分析—以岱海为例

如何利用湖泊/海洋沉积物地球化学代用指标有效地指示环境很大程度取决于元素的来源及其在沉积物中赋存形态的确定.对位于半干旱区的内蒙古岱海14个沉积物样品的连续提取实验及18个元素在水可溶态、可交换态、碳酸盐结合态、铁锰氧化物结合态、有机物结合态及残留态等六种赋存相态中含量变化进行了测试和研究,结合沉积物的矿物组成,结果表明在岱海流域内只经历了较弱的化学风化过程,除了Ca和Sr外,其他元素主要赋存于残留态中,只发生了很小程度的活化溶解.受元素亲合性和湖水物理化学状态的制约,出溶的Sr与Ca的赋存相态基本一致,而出溶的Pb、Be、Co、Cu、K、Mn、Fe等元素则与自生碳酸盐、有机质表现出一定的亲合性.元素在不同赋存相态中分布为地球化学环境代用指标的提取和解释提供了机理性的实验依据.     

http://dx.doi.org/10.1016/j.gsf.2016.09.005

We propose the nuclear geyser model to elucidate an optimal site to bear the first life.Our model overcomes the difficulties that previously proposed models have encountered.Nuclear geyser is a geyser driven by a natural nuclear reactor,which was likely common in the Hadean Earth,because of a much higher abundance of ~(235)U as nuclear fuel.The nuclear geyser supplies the following:(1)high-density ionizing radiation to promote chemical chain reactions that even tar can be used for intermediate material to restart chemical reactions,(2)a system to maintain the circulation of material and energy,which includes cyclic environmental conditions(warm/cool,dry/wet,etc.)to enable to produce complex organic compounds,(3)a lower temperature than 100℃ as not to break down macromolecular organic compounds,(4)a locally reductive environment depending on rock types exposed along the geyser wall,and(5)a container to confine and accumulate volatile chemicals.These five factors are the necessary conditions that the birth place of life must satisfy.Only the nuclear geyser can meet all five,in contrast to the previously proposed birth sites,such as tidal flat,submarine hydrothermal vent,and outer space.The nuclear reactor and associated geyser,which maintain the circulations of material and energy with its surrounding environment,are regarded as the nuclear geyser system that enables numerous kinds of chemical reactions to synthesize complex organic compounds,and where the most primitive metabolism could be generated.     

BFA-CM最优化测井解释方法

最优化测井解释方法能充分利用各种测井资料及地质信息,可以有效地评价复杂岩性油气藏.优化算法的选择是最优化测井解释方法的关键,影响着测井解释结果的准确性.细菌觅食算法(BFA)是新兴的一种智能优化算法,具有较强的全局搜索能力,但在寻优后期收敛速度较慢.复合形算法(CM)局部搜索能力极强,将其与BFA算法相结合构成BFA-CM混合算法,既提高了搜索精度又提高了搜索效率.利用BFA-CM最优化测井解释方法对苏里格致密砂岩储层实际资料进行了处理,计算结果与岩心及薄片分析资料吻合得很好.