基于Floyd算法的海温时间序列分割

时间序列数据的处理及挖掘一直是业界关注的热点,而海表温度也一直是人们观测、研究和预报的重要对象。本文主要考虑对一年的跨度进行切割,使得落在每个切割区间的海表温度数据满足最优的正态分布,以便对遥感数据的异常性作出检验。结合2003-2011年南海和东海海表温度数据集,本文引入Floyd算法,将寻求数据集最优分割问题转化为图论中网络中最短路求解问题,将不超过30天的点之间的距离设定为无穷大,以避免分割点过于密集的情况,并将频率与概率的距离定义的误差转化为线路权重,实现了动态全局最优分割。且正态分布下的3σ异常值检验法,实现了对异常值的识别。     

基于人工鱼群和分形学习的雾霾天气预报方法

针对目前较严重的雾霾污染,雾霾天气预报显得十分重要,通过将改进人工鱼群算法和分形学习相结合,提出了基于人工鱼群和分形学习的雾藕天气预报方法.首先对人工鱼群算法离散化改进,结合分形学习理论降维雾霾数据;其次运用支持向量机和5-折交叉验证技术分类分布可能不平坦的数据集;最后建立雾霾天气预报模型.实验结果表明,数据降维后更有利于提高分类器性能,与传统预报方法相比,预报性能更优,具有较高的稳定性和可信性.     

彗木相撞预报 *

以太阳系天体动力学数值模型为基础,探研方法理论,编制软件,向国内外发出了多次Shoemaker-Levy 9号彗星与木星相撞预报,预报结果和实际基本吻合.阐述预报的方法理论,并将预报的碰撞时间和国际确认的实际碰撞时间予以比较分析.     

基于随机森林算法的某型飞机燃油消耗情况研究

为确定某型飞机燃油消耗量同其它因素之间的相关关系,首先将预处理后的某场站近三年燃料油消耗的实际数据随机地分成10份;然后,分别借助决策树和随机森林算法,对数据建立回归模型,并采用10折交叉验证法,判断上述结果的可靠性;最后,使用平均的标准化均方误差来评价模型,得出结论.     

城市房地产预警技术研究

本文通过构建我国城市房地产预警预报系统,详细分析其中的技术要点,并运用有关城市的经验数据对系统的预警预报功能进行检验。结果表明,构建的房地产预警预报系统能准确地反映城市的房地产市场运行状况,起到预警预报的作用。     

桥联理论研究的最新进展

欲根据组分材料——纤维和基体性能参数预报复合材料的强度,必须解决3个方面的问题.首先,必须准确计算出纤维和基体中的内应力;其次,必须基于这些内应力,建立起复合材料的有效破坏判据,即细观力学强度理论;最后,必须根据独立测试的基体性能,准确定义其现场强度输入数据,因为后者无法测量.复合材料强度预报之所以困难,在于所涉及的每一个问题都极具挑战.由黄争鸣创建和发展的桥联理论,系统给出了这3方面问题的有效解决方案.该文简要介绍这些解决方案,包括桥联理论的最新进展及有待进一步研究的课题.     

多元线性回归模型的漠河站开河预测

在黑龙江漠河站的天然河道,开河时期的冰坝和凌汛形成的机制复杂.目前许多冰动力学模型很难模拟和预报开河期,常用的的预报一般采用传统的统计学方法和经验判别式法.为应对严重的防凌形势,需要找到冰情预报的全新方法.提出了一种多元线性回归模型的方法.方法要求有冰层厚度、温度、降水量及与开河密切相关的冰情相应参数.冰层厚度、温度可以从实验室研制的温度梯度传感器测得相应的参数.预报方法应用在黑龙江漠河站的天然河段上,效果较好.     

模糊数学理论在水库长期径流预报中的应用

本文运用模糊数学的理论方法对汛期径流预报进行了探讨 ,即首先对汛期来水的理论实测资料 ,运用最大树法和软化分法进行了模糊聚类分析 ,得到汛期来水的多个预报模式 ;进而利用Gamma分布和模糊概率的方法 ,预报出汛期的来水流量及其实现的概率     

主成分分析与支持向量机相结合的区域降水预测应用

将主成分分析和支持向量机回归相结合,以广西5、6月区域平均日降水量作为预报对象,进行区域日降水量预测研究.首先,整理分析大量的T213数值预报产品信息数据进行主成分分析,得到主成分数据序列;其次,根据主成分数据序列建立训练集训练支持向量机,并利用遗传算法优化参数;最后,输入支持向量机所需数据,得到主成分预测结果,建立广西日降水预报模型.实例计算结果表明,支持向量机回归模型比逐步回归模型有更好的预测能力.     

基于动态BP神经网络的非线性预测及在港口货物吞吐量中的应用

文章给出了非线性预测的一般理论方法，运用动态ＢＰ神经网络对实际问题的历史数据进行学习，然后根据学习后获得的非线性机理来进行预测。并将此方法应用于港口货物吞吐量及出口量预报。仿真表明此方法是有效的。     

Marine system dynamical response to a changing climate in frame of power law,exponential decay,and Mittag-Leffler kernel

The increase of sea surface temperature in ocean changes the photosynthetic production rate of phytoplankton. Therefore, it is crucial to understand the relation between temperature and phytoplanktons photosynthesis to deal the extinction caused by excessive increase in temperature. It is worth observing that temperature is one of the most principal limiting factors for phytoplanktons production due to photosynthetic enzymes work at their optimum temperature levels. In this study, the fractional oxygen-phytoplankton-zooplankton model is considered by singular and nonsingular fractional operators within Caputo, Caputo-Fabrizio, and Atangana-Baleanu in Caputo sense. The rate of oxygen production is considered by a function of temperature account for the sea surface warming. At first, the temperature function is constant and then it starts to increase, after a certain time of increase, before the oxygen depletion begins, the temperature is set to a higher secure value. With this temperature function choice, detailed numerical simulations are carried out to provide details of the internal structure of the system. We observe that the species are more sustainable in Caputo model than its corresponding integer-order model.     

Critical temperature of soliton state stability in quasi-one-dimensional systems

The temperature effect on soliton state formation in quasi-one-dimensional systems is considered in the self-consistent field approximation. The critical temperature above which soliton states are nonstable is shown to exist. The crirical temperature dependence on nonlinearity parameter and system dimension is found. Soliton density at which the critical temperature is maximal is calculated.     

MATHEMATICAL ESTIMATION OF PHYSIOLOGICAL DISTURBANCES IN HUMAN DERMAL PARTS AT EXTREME CONDITIONS： ONE DIMENSIONAL STEADY STATE CASE

A mathematical model for the thermoregulation in the dermal layers of the human body is proposed. The skin is composed mainly of three layers — epidermis, dermis and subcutaneous tissues. The relative constancy of the body temperature is remarkable because there is a continuous exchange of heat with the external environment as well as within the different compartments of the body. A model describes the distribution of dermal temperature as a function of internal and external parameters, such as temperature of the incoming arterial blood, blood flow, ambient temperature, and heat exchange with the environment. It is shown that substantial changes in human dermal temperature can be accomplished only through changes in the temperature of the incoming arterial blood or substantial suppression of blood flow. Other parameters can lead only to temperature changes near the skin surface.     

Effect of increasing temperature due to depletion of ozone layer caused by CFC on the dynamics of two competing populations: a model

It is well recognized that the greenhouse gas such as Chlorofluoro Carbon (CFC) is responsible for the increase in the average global temperature. The presence of CFC is responsible for the depletion of ozone concentration in the atmosphere due to which the heat accompanied with the sun rays are less absorbed causing increase in the atmospheric temperature of the Earth. The increase in temperature level may directly or indirectly affect the dynamics of interacting species systems. Therefore, in this paper, a mathematical model is proposed and analysed to asses the effects of increasing temperature on the survival or extinction of two competing populations.     

The interacting-particle algorithm with dynamic heating and cooling

We consider an interacting-particle algorithm which is population-based like genetic algorithms and also has a temperature parameter analogous to simulated annealing. The temperature parameter of the interacting-particle algorithm has to cool down to zero in order to achieve convergence towards global optima. The way this temperature parameter is tuned affects the performance of the search process and we implement a meta-control methodology that adapts the temperature to the observed state of the samplings. The main idea is to solve an optimal control problem where the heating/cooling rate of the temperature parameter is the control variable. The criterion of the optimal control problem consists of user defined performance measures for the probability density function of the particles’ locations including expected objective function value of the particles and the spread of the particles’ locations. Our numerical results indicate that with this control methodology the temperature fluctuates (both heating and cooling) during the progress of the algorithm to meet our performance measures. In addition our numerical comparison of the meta-control methodology with classical cooling schedules demonstrate the benefits in employing the meta-control methodology.     

AN UNCONDITIONALLY STABLE HYBRID FE-FD SCHEME FOR SOLVING A 3-D HEAT TRANSPORT EQUATION IN A CYLINDRICAL THIN FILM WITH SUB-MICROSCALE THICKNESS

Heat transport at the microscale is of vital importance in microtechnology applications.The heat transport equation is different from the traditional heat transport equation since a second order derivative of temperature with respect to time and a third-order mixed derivative of temperature with respect to space and time are introduced. In this study,we develop a hybrid finite element-finite difference (FE-FD) scheme with two levels in time for the three dimensional heat transport equation in a cylindrical thin film with submicroscale thickness. It is shown that the scheme is unconditionally stable. The scheme is then employed to obtain the temperature rise in a sub-microscale cylindrical gold film. The method can be applied to obtain the temperature rise in any thin films with sub-microscale thickness, where the geometry in the planar direction is arbitrary.     

Axi symmetric 2D simulation and numerical heat transfer characteristics for the calibration furnace in a rectangular enclosure

This paper presents axi symmetric 2D numerical investigation of the spherical thermocouple calibration furnace in a rectangular enclosure. The focus is on the flow structure inside the Saturn (a hollow spherical cavity), external flow behavior due to annulus block heating and the surface temperature uniformity. Mesh sensitivity analysis is adopted to extract the mesh with minimum number of nodes but with fast convergent finite element solution. The basic strategy here is that temperature perturbation error at a single point instead of a single element contributed to the total perturbation error qualitatively remains the same. Agreement between numerical simulation results and the experiment results is good with a maximum temperature deviation 10 °C for the cavity temperature 400 °C. Finally, standard numerical temperature uncertainty due to variation in thermal conductivity is computed through the sensitivity coefficient using uncertainty analysis.     

1961～2005年漠河年均温和年均高低温的变化分析

对近四十五年来中国漠河的气温变化作了一个初步分析.根据中国漠河1961～2005年逐日平均、最高、最低气温资料,求得了相应的年均温、年均高温和年均低温,分别对它们进行了线性拟合,结果表明它们在这45年都有所升高,并且由t检验得出线性趋势都是显著的.之后用线性回归模型拟合了年均温与年均高温和年均低温的关系,得出了拟合方程,并由F检验说明了线性回归关系的显著性.最后又采用变系数回归模型的局部线性拟合方法拟合了年均温与年均高温和年均低温的变化关系,从而揭示了年均高温和年均低温对年均温的影响随时间变化的规律,对研究年均温升高的原因具有一定的参考意义.     

N-dimensional Schrödinger equation at finite temperature using the Nikiforov–Uvarov method

The N-radial Schrödinger equation is analytically solved. The Cornell potential is extended to finite temperature. The energy eigenvalues and the wave functions are calculated in the N-dimensional form using the Nikiforov–Uvarov (NV) method. At zero temperature, the energy eigenvalues and the wave functions are obtained in good agreement with other works. The present results are applied on the charmonium and bottomonium masses at finite temperature. The effect of dimensionality number is investigated on the quarkonium masses. A comparison is discussed with other works, which use the QCD sum rules and lattice QCD. The present approach successfully generalizes the energy eigenvalues and corresponding wave functions at finite temperature in the N-dimensional representation. In addition, the present approach can successfully be applied to the quarkonium systems at finite temperature.     

EMD-SVM在南京市月平均气温预测中的应用

南京市月平均气温具有非平稳性、噪声大、序列宽频等特征.为了提高温预测精度,本文提出一种经验模态分解(EMD)和支持向量机(SVM)回归相组合的预测模型(EMD-SVM).首先应用EMD分解算法把南京市月平均气温分解成不同尺度的基本模态分量(IMF),再运用支持向量机回归模型对每个IMF预测,最后将预测结果重构得到南京市月平均气温预测值.结果表明:EMD-SVM模型预测与单一支持向量机回归模型预测相比,平均预测精度提高0.59度,是一种有效的预测气温的模型.