Pollen record and environmental evolution of Caotanhu wetland in Xinjiang since 4550 cal. a BP

This paper presents a multi-proxy reconstruction of the climate change in Caotanhu wetland using pollen, phytolith and charcoal records, and the data of loss of ignition （LOI）, grain size analysis, and susceptibility. Results reveal that between 4550 and 2500 cal. a BP, a dry climatic condition was not favorable for the accumulation of peat. Since 2500 cal. a BP, the climate became humid and the wetland developed with abundant freshwater aquatic plants, which contributed to peat accumulation. Never-theless, alternate periods of rain and dry climate occurred during that period. Between 2500 and 1810 cal. a BP （550 BC-140 AD）, the climate was more humid than at present. A lot of emerged plants, such as Phragmites, Typha and Sparganium, and freshwater green algae grew in the wetland which was sur-rounded by desert-steppe vegetation composed mainly of Chenopodiaceae, Artemisia, Compositae and Thalictrum. However, from 1810 to 1160 cal. a BP （140--790 AD）, the water level started to decrease and hydrophyte species reduced greatly, but some Phragmites still grew in the wetland and around it was desert vegetation with high proportion of Chenopodiaceae and Artemisia. Then from 1160 to 650 a BP （790--1300 AD）, it entered a period of desert-steppe with abundant mesic and xerophytic plants. And a lot of aquatic plants prevailed in the wetland. Here, what is noticeable is that percentages of arboreal pollen, consisting mainly of Betula and Picea, increased greatly and reached a maximal value of 27.2%, in which, Betula percentages rose to 23.2%. Hence, it is reasonable to conclude that Betula grew in the highland of the wetland, or Picea timberline shifted downward resulting in the increase of percentages of Betula and Picea pollen, which were transported into the wetland by flood or wind. But since 650 cal. a BP, desert vegetation prevailed around the wetland again with dominant Chenopodiaceae and Artemisia, and the climate was similar to modern one. Despite some aquatic plants still growing in the wetland at     

岩体弹性模量反分析的进化差分方法

考虑到岩体弹性模量反分析本质上是一个复杂的非线性函数优化问题,采用全局优化算法是解决这个问题的理想途径.本文将具有收敛速度快、易于实现和全局寻优能力强大等优点的差分进化算法(Differential Evolution,DE)融入到岩土工程数值计算程序(FLAC3D)中,提出了基于DE算法的岩体弹性模量反分析方法,并通过一个简单算例验证了该方法的正确性,结果也表明该方法是科学可行的,具有较高的精度.     

一类非线性演化方程的新的精确波类解

通过Fan-辅助方程展开法,得到了一类非线性演化方程的一系列显式精确解,包括孤立波解、类孤立波解、奇异类孤立波解,以及纽结波解、奇异纽结波解和三角函数周期解.     

多线程可动态演化程序的设计

为满足软件系统24/7/365不中断运行的需求,提出了对运行中的软件进行动态演化的要求.分析了软件演化的基本种类,叙述了多线程可动态演化软件的演化步骤,并对该类程序设计中涉及到的一些关键问题展开讨论.最后以数据集成软件为例分析了多线程可动态演化程序实例的运行状况.     

灰色GM(1,1)模型建模的理论探讨

在分析GM(1,1)建模中灰导数及其白化背景值对模型精度与适应性的影响的基础上,从灰导数、灰导数的白化背景值的构造证明了原始时间序列数据变化越平缓,发展系数的绝对值越小,GM(1,1)模型的拟合与预测精度越高,模型的适应性越强,同时提出了原始序列数据的一些处理方法。     

基于迁徙策略的PSO集成及其在序列模体识别中的应用

对优化问题和游牧民族迁徙行为的比较研究表明,两者存在相似之处,文中模拟了游牧民族迁徙机制,提出了一种迁徙策略,并且与粒子群优化算法相结合,提高了算法摆脱局部极值的能力,通过集成技术,充分发挥各种粒子群优化算法的优点,实现协同演化,提高了算法的全局搜索能力。最后应用于求解计算分子生物学中的一个复杂问题——生物序列模体识别,实验表明,该算法是有效的。     

西方公共财政理论演进与评价

在回顾西方公共财政理论产生与发展的基础上,分析了公共财政理解的线索主要是弥补市场失灵与矫正政府失效,指出公共财政需要处理政府与市场、各级政府之间以及政府各部门之间等几个关系,提出了建立“政府-财政-市场”的分析框架以及用发展的眼光看待公共财政。     

基于差异演化的粒子群优化算法

针对粒子群优化算法由于缺乏种群多样性而导致早熟收敛的不利因素.提出了一种把差异演化算法中的后代产生机制引入粒子群优化算法的更新规则中以保持粒子群的种群多样性和加快收敛速度的算法.这种思想能有效改善摆脱极值点的能力.基于几个高维测试函数的试验结果显示,该算法在收敛速度快和精度方面都优于粒子群优化算法.     

Supply China Production-distribution Cost Optimization under Grey Fuzzy Uncertainty

Most supply chain programming problems are restricted to the deterministic situations or stochastic environments. Considering twofold uncertainty combining grey and fuzzy factors, this paper proposes a hybrid uncertain programming model to optimize the supply chain production-distribution cost. The programming parameters of the material suppliers, manufacturer, distribution centers, and the customers are integrated into the presented model. On the basis of the chance measure and the credibility of grey fuzzy variable, the grey fuzzy simulation methodology was proposed to generate input-output data for the uncertain functions. The designed neural network can expedite the simulation process after trained from the generated input-output data. The improved Particle Swarm Optimization (PSO) algorithm based on the Differential Evolution (DE) algorithm can optimize the uncertain programming problems. A numerical example was presented to highlight the significance of the uncertain model and the feasibility of the solution strategy.     

复杂系统理论在创新研究中的应用——兼谈复杂理论视角下创新的起源、结构和演化

人类的创新过程作为社会活动的一部分具有复杂系统的特征.在此,综合介绍了学者们用复杂系统理论对创新活动研究的一些成果,特别介绍了近期在创新的起源、结构和演化方面的进展.然而,这方面大多数的研究都是基于复杂系统理论在生物系统中所建立的模型来诠释创新活动的规律,而社会系统和生物系统是完全不在一个层次的复杂系统.因此,在发现不同层次的复杂系统的通用规律之时,也需要思考社会系统,包括创新活动的独特规律.另外,创新研究是一个新兴的交叉学科,由于自然科学家和人文科学家知识结构互补,如果联合研究,将使该项研究迈上一个崭新的台阶.