三维DNA自组装在多维背包问题中的应用研究

利用DNA自组装执行计算的思想已从实验上被证明了其可行性．已有多种理论模型被提出用以解决各种NP问题．基于DNA Tile自组装模型理论在二维下的扩展,本文设计了可以实现这一算法的三维DNA Tile组装系统,提出了一种用于解决多维背包问题的三维DNA自组装模型．该模型可以非确定性的输出可行性解决方案．分析表明系统可以在线性组装步骤内完成计算,所需的Tile种类数与问题维数无关．为探索三维DNA自组装的计算能力进行了一次有意义的尝试．     

A novel DNA computing model based on RecA-mediated triple-stranded DNA structure

The field of DNA computing emerged in 1994 after Adleman’s paper was published. Henceforth,a few scholars solved some noted NP-complete problems in this way. And all these methods of DNA computing are based on conventional Watson-Crick hydrogen bond of doublehelical DNA molecule. In this paper, we show that the triple-stranded DNA structure mediated by RecA protein can be used for solving computational problems. Sequence-specific recognition of double-stranded DNA by oligonucleotide-directed triple helix (triplex) formation is used to carry out the algorithm. We present procedure for the 3-vertex-colorability problems. In our proposed procedure, it is suggested that it is possible to solve more complicated problems with more variables by this model.     

Solid phase based DNA solution of the coloring problem

DNA computing has the potential to tackle computationally difficult problems that have real-world implications.The parallel search capabilities of DNA make it a valuable tool for approaching intractable computational problems,for which conventional computers have limited potentials.Up to now,many accomplishments have been achieved to improve its performance and increase its reliability.In this paper,the coloring problem has been solved by means of molecular biology techniques.The coloring problem is a well-known NP-complete problem.This work represents further evidence for the ability of DNA computing to solve NP-complete problems.     

关系-映射-反演方法在高等数学问题解决中的应用

在高等数学问题解决过程中,用本领域的知识解决一些问题比较困难,但有时将问题转化到其它领域去解决,会使一些百思不得其解的问题得到比较容易的解答．关系-映射-反演方法就是这样一种重要方法．关系-映射-反演方法用于解决高等数学问题有以下几个方面：用几何知识解决代数问题：用代数方法解决几何问题;用积分方法解决级数问题;用概率方法解决高等数学问题;用线性代数方法解决高等数学问题;用计算方法解决高等数学问题;用物理方法解决数学问题等．分别举例对上述应用进行了说明．关系-映射-反演方法的运用能增强知识间的纵向和横向联系,培养学生思维的灵活性和创造性．     

DNA杂交测序算法研究进展

DNA杂交测序是计算生物学的核心问题之一,其研究目标是在杂交实验的基础上重构DNA序列,已证明带有错误的杂交测序属于强NP-难问题。随着组合优化的研究,精确算法和启发式搜索算法,尤其是后者,被用于求解此类问题。目前,许多文献已提出了重构算法,但现有算法在解决实际问题时仍存在缺陷。综述了国内外已提出的重构算法,在此基础上进行了比较,分析了存在的主要问题,指出了当前新的研究热点,对未来的研究与发展趋势进行了展望。     

Multiple structure computational model and its application in optimization

The paper proposes an evolutionary computational model, multiple structure computational model, from simulating the behavior of the ecosystem. Some numerical experiments show the new model can solve some GA-hard problems. Using the concept of adaptability in ecology, we give a theoretical analysis to explain why the new model is efficient.     

DNA computing on surfaces

DNA computing was proposed as a means of solving a class of intractable computational problems in which the computing time can grow exponentially with problem size (the 'NP-complete' or non-deterministic polynomial time complete problems). The principle of the technique has been demonstrated experimentally for a simple example of the hamiltonian path problem (in this case, finding an airline flight path between several cities, such that each city is visited only once). DNA computational approaches to the solution of other problems have also been investigated. One technique involves the immobilization and manipulation of combinatorial mixtures of DNA on a support. A set of DNA molecules encoding all candidate solutions to the computational problem of interest is synthesized and attached to the surface. Successive cycles of hybridization operations and exonuclease digestion are used to identify and eliminate those members of the set that are not solutions. Upon completion of all the multistep cycles, the solution to the computational problem is identified using a polymerase chain reaction to amplify the remaining molecules, which are then hybridized to an addressed array. The advantages of this approach are its scalability and potential to be automated (the use of solid-phase formats simplifies the complex repetitive chemical processes, as has been demonstrated in DNA and protein synthesis). Here we report the use of this method to solve a NP-complete problem. We consider a small example of the satisfiability problem (SAT), in which the values of a set of boolean variables satisfying certain logical constraints are determined.     

基于遗传算法的DOA估计

针对阵列天线上对多个远场信号源入射方向、功率估计问题 ,提出了一种基于实数遗传算法的解决方法 .通过增加合并算子 ,使遗传算法成为解决此类问题的有效方法之一 .仿真实验获得了良好的结果 .这一算法无需进行特征值分解 ,减小了计算量 .     

高职高专英语词汇教学现状分析及策略研究

作为英语教学的基础环节,英语的词汇教学历来都很受重视。随着近年来英语教学改革的不断深入,很多从事高职高专英语教学的教师都在探究英语词汇教学的新方法。本文作者从分析现状入手,指出了高职高专英语词汇教学中存在的一些问题,并由此阐述了相应的策略思考。     

DNA计算在二次分配问题中的应用研究

DNA计算（DNA computing）是一种新的计算方法,其高度并行性和巨大的信息存储能力为NP-完全问题的解决提供了一种全新的方法。本文采用了该算法去解决二次分配问题,构造了该问题的表达方法,建立了算法模型,对于我们将DNA计算的方法应用于组合优化问题具有启发性,并为我们进一步深入研究奠定了基础。     

基于人工神经网络的圆孔电磁耦合预测

孔缝电磁耦合问题历来是电磁兼容领域中的一个重要部分,多年来人们已经采用多种方法对孔缝电磁耦合问题进行了深入研究.随着电子系统的日益复杂,无论是全波分析还是解析方法在孔缝电磁耦合问题研究中都存在很大的局限性.为了更好的解决这个问题,本文探讨了人工神经网络用于孔缝耦合分析的可行性.以大量数值计算结果为训练样本,建立了适用于...     

A surface-based DNA algorithm for the minimal vertex cover problem

Abstract DNA computing was proposed for solving a class of intractable computational problems, of which the computing timewill grow exponentially with the problem size. Up to now, many achievements have been made to improve its performance and increase itsreliability. It has been shown many times that the surface-based DNA computing technique has very low error rate, but the technique hasnot been widely used in the DNA computing algorithms design. In this paper, a surface-based DNA computing algorithm for minimal ver-tex cover problem, a problem well-known for its exponential difficulty, is introduced. This work provides further evidence for the abilityof surface-based DNA computing in solving NP-complete problems.     

小水电站发电机起励自动并网系统

由于全国电力供应紧张，上网电价上扬，农网改造的完成及电力体制改革的深入，使得小水电上网变得即方便又有较好的经济效益。但一些小水电站因建站时间已久，发电机的起励、并网系统较落后，操作也不方便，已不适应上网要求。为此，我们设计了一套简洁、实用、价廉的半自动系统，满足了发电机的起励，并网及励磁的要求。     

基于深度神经网络-近似线性网络混合模型的电力系统状态估计方法

为提高电力系统实时状态估计的精度和计算效率,解决电网电压波动频发、潮流分布的不确定性剧增等问题,通过提出一种基于深度神经网络和近似线性网络模型的电力系统状态估计方法,研究了其在电网的应用。该方法将混合系统量测数据通过粒子滤波算法得到样本集,利用训练样本训练所提出的混合神经网络模型,最后将测试样本输入已建立的模型中获得系统状态的估计结果。通过IEEE118节点系统进行的负载数据仿真实验表明：基于混合神经网络模型的电力系统状态估计方法不仅能快速进行海量数据训练,还能有效避免过拟合;在实时状态估计的精度和计算效率方面相较于高斯-牛顿法均有提高。可见所提方法在电力系统实时状态估计方面具有一定的应用价值。     

基于进化策略的随机存储模型求解

采用进化策略和基于随机模拟的进化策略求解随机存储模型，给出了基于Matlab的算法实现和典型存储问题的计算结果，并通过对几个典型实例的分析说明上述方法是有效可行的。     

带条件风险约束的发电商最优投标模型及计算

采用条件风险(CVaR)作为风险度量指标,建立了双层优化的发电商投标模型,上层解决社会效益最大和风险最小问题,下层解决发电商利润最大问题,设计了启发式粒子群算法(PSO)求解该复杂的双层优化模型.在4节点2机系统和9节点3机系统进行了实验,说明该模型和算法具有较好的计算效果和时效性,通过实验数据比较显示CVaR比VaR更准确地度量了发电商的风险.     

DNA computing model based on lab-on-a-chip and its application on solving the timetabling problem

The essential characteristic of DNA computation is its massive parallelism in obtaining and managing information. With the development of molecular biology technique, the field of DNA computation has made a great progress. By using an advance technique of biochip, laboratory-on-a-chip, in this paper a new DNA computing model was presented to solve a simple timetabling problem, which is a special version of the optimization problems and plays an important role in education. With a simulated biological experiment, the result suggested that DNA computation with lab-on-a-chip has the potential to solve a real complex timetabling problem.     

混合动力汽车电池管理系统SOC的评价

为建立混合动力汽车电池管理系统的需要，探索镍氢电池荷电状态(SOC)的实时测量和估计方法，分析当前一般SOC定义在变电流放电情况下出现不适应的原因，和现有各种荷电状态估计方法存在的问题。为此，根据能量守恒原理，提出了一种新SOC的概念，使之能很好地适应混合动力汽车用电池在变电流状态下的实时荷电状态估计，并且基于新的SOC定义，建立电池荷电状态计算模型，进行仿真分析，简化计算，明确物理意义，提高了SOC的判断精度，减少混合动力汽车的复杂性，减少整车的成本，为混合动力汽车系统优化匹配提供了依据。     

基于新LOM原理的分层切片算法

针对以金属板材为造型材料的分层快速制造方法中存在的问题，提出了新LOM方法，指出了新LOM方法对分层切片参数的要求，推导出相应的计算公式，实现了新LOM方法对造型实体CAD模型的分层处理。     

STUDY OF KINETIC ANALYTICAL METHOD BASED ON CATALYTIC REACTIONS

In this thesis a reviwe is presented for the advances of catalytic spec trophotometric method, three new catalytic reaction systems were presented, and its rela live catalytic spectrophotometric methods have been established by flow injection tech nique. Particulary the relative chemometric methods and theories were used in the field of kinetic - catalytic analysis, in order to solve the problems of multicomponents analysis.