15 resultados para Bayes Estimator
em Chinese Academy of Sciences Institutional Repositories Grid Portal
Resumo:
Amblycipitidae Day, 1873 is an Asian family of catfishes (Siluriformes) usually considered to contain 28 species placed in three genera: Amblyceps (14 spp.), Liobagrus (12 spp.) and Xiurenbagrus (2 spp.). Morphology-based systematics has supported the monophyly of this family, with some authors placing Amblycipitidae within a larger group including Akysidae, Sisoridae and Aspredinidae, termed the Sisoroidea. Here we investigate the phylogenetic relationships among four species of Amblyceps, six species of Liobagrus and the two species of Xiurenbagrus with respect to other sisoroid taxa as well as other catfish groups using 6100 aligned base pairs of DNA sequence data from the rag1 and rag2 genes of the nuclear genome and from three regions (cyt b, COL ND4 plus tRNA-His and tRNA-Ser) of the mitochondrial genome. Parsimony and Bayesian analyses of the data indicate strong support for a diphyletic Amblycipitidae in which the genus Amblyceps is the sister group to the Sisoridae and a clade formed by genera Liobagrus and Xiurenbagrus is the sister group to Akysidae. These taxa together form a well supported monophyletic group that assembles all Asian sisoroid taxa, but excludes the South American Aspredinidae. Results for aspredinids are consistent with previous molecular studies that indicate these catfishes are not sisoroids, but the sister group to the South American doradoid catfishes (Auchenipteridae + Doradidae). The redefined sisoroid clade plus Bagridae, Horabagridae and (Ailia + Laides) make up a larger monophyletic group informally termed "Big Asia." Likelihood-based SH tests and Bayes Factor comparisons of the rag and the mitochondrial data partitions considered separately and combined reject both the hypothesis of amblycipitid monophyly and the hypothesis of aspredinid inclusion within Sisoroidea. This result for amblycipitids conflicts with a number of well documented morphological synapomorphies that we briefly review. Possible nomenclatural changes for amblycipitid taxa are noted.
Resumo:
In this paper, an efficient iterative discrete Fourier transform (DFT) -based channel estimator with good performance for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems such as IEEE 802.11n which retain some sub-carriers as null sub-carriers (or virtual carriers) is proposed. In order to eliminate the mean-square error (MSE) floor effect existed in conventional DFT-based channel estimators, we proposed a low-complexity method to detect the significant channel impulse response (CIR) taps, which neither need any statistical channel information nor a predetermined threshold value. Analysis and simulation results show that the proposed method has much better performance than conventional DFT-based channel estimators and without MSE floor effect.
Resumo:
由于Eu~(2+)离子在不同复合氟化物中存在不同的跃迁发射形式,主要有5d → 4f的宽带跃迁,位于365nm-650nm间和4f → 4f的窄带跃迁,中心位置在360nm附近。Eu~(2+)离子的跃迁形式决定于基质的化学组成。本工作就是用多种模式识别方法(KNN,ALKNN,BAYES,LLM,SIMCA和PCA)研究不同复合氟化物基质中Eu~(2+)离子的跃迁发射形式和基质晶体结构之间的关系,找出Eu~(2+)离子产生f → f跃迁其基质构成的一般规律性。收集了90个复合氟化物(AB_mF_n)作为样本集,根据其中Eu~(2+)离子跃迁形式的不同将它们分成两类,一类为具有f → f跃迁的基质45个;另一类为不具有f → f跃迁的基质45个。随机地选用63个基质作为训练集,其余的为验证集。每个基质样本利用其12个晶体结构参数作为描述。由于各参数间差别不大,对原始数据未进行标度化。特征提取是模式识别分析的一个重要步骤,本工作结合变化权重法,BAYES特征量评价法和SIMCA变量相关性评价法的特点,建立了一个以验评价判据式:d(i) = -5.0 + 2.3V(i) + 0.89f(i) + 7.2W(i)根据经验式,选取了变量Z_B/r_(kB),r_(covA)/r_(covB)和Z_B/r_(covB),并删除了变量Xσ_A,Xσ_B,r_(covA)。其它变量由于其D值接近,利用穷举法对它们进行选取,结果M,Z'_A和r_(covB)被选中。这样把这6个被选的变量作为对跃迁发射问题最相关的变量进行进一步分析。采用被选的6维变量对训练集样本施行主成份分析,结果表示前三个主成份已可解释原数据信息量的99%以上。所以分别以主成份1-3及主成份1和主成份3作了三维和二维的映射图。结果表示两类基质样本基本上分在不同区域。进一步分别用12维和6维变量对样本系进行了其它几种模式识别分析。所有这些方法对训练集的分类效果都比较理想。采取6维特征时,其正确分类率达79.4-96.8%,这说明与跃迁问题相关的大部分变量已被选入。但是结果显示,各种方法对训练集的分类有一定的差别。我们认为这是由于各种不同的方法对数据结构要求不同引起的。实验证明Bayes线性判别方法对该样本集数据的分类效果最佳。根据Bayes线性差别方法的执行得到了对基质样本分类模式,由此模式讨论了各结构参数对Eu~(2+)离子光谱结构的影响,并对七个未知基质中Eu~(2+)离子的光谱结构进行了计算机预报,结果表示KTbF_4,KBF_4,NaIn_2F_7和KLu_2F_7为具有f → f跃迁发射的基质,而NaCaF_3,MgBeF_4和MgAlF_5为不具有f → f跃迁发射的基质。
Resumo:
准确的网络流量分类是众多网络研究工作的基础,也一直是网络测量领域的研究热点.近年来,利用机器学习方法处理流量分类问题成为了该领域一个新兴的研究方向.在目前研究中应用较多的是朴素贝叶斯(nave Bayes,NB)及其改进算法.这些方法具有实现简单、分类高效的特点.但该方法过分依赖于样本空间的分布,具有内在的不稳定性.因此,提出一种基于支持向量机(support vector machine,SVM)的流量分类方法.该方法利用非线性变换和结构风险最小化(structural risk minimization,SRM)原则将流量分类问题转化为二次寻优问题,具有良好的分类准确率和稳定性.在理论分析的基础上,通过在实际网络流集合上与朴素贝叶斯算法的对比实验,可以看出使用支持向量机方法处理流量分类问题,具有以下3个优势:1)网络流属性不必满足条件独立假设,无须进行属性过滤;2)能够在先验知识相对不足的情况下,仍保持较高的分类准确率;3)不依赖于样本空间的分布,具有较好的分类稳定性.
Resumo:
The relationship between structures of complex fluorides and spectral structure of Eu(II) ion in complex fluorides (AB(m)F(n)) is investigated by means of pattern recognition methods, such as KNN, ALKNN, BAYES, LLM, SIMCA and PCA. A learning set consisting of 32 f-f transition emission host compounds and 31 d-f transition emission host compounds and a test set consisting of 27 host compounds were characterized by 12 crystal structural parameters. These parameters, i.e. features, were reduced from 12 to 6 by multiple criteria for the classification of these host compounds as f-f transition emission or d-f transition emission. A recognition rate from 79.4 to 96.8% and prediction capabilities from 85.2 to 92.6% were obtained. According to the above results, the spectral structures of Eu(II) ion in seven unknown host lattices were predicted.
Resumo:
为了进一步研究青蟹属系统进化的科学问题,并揭示我国东南沿海青蟹群体遗传结构和群体进化细节信息,本论文主要开展了以下两个方面的研究:(1)基于线粒体12S rRNA、16S rRNA和COI三种基因序列探讨中国东南沿海青蟹的种类归属与青蟹属的系统进化;(2)利用线粒体COI基因标记分析中国东南沿海拟穴青蟹的群体遗传结构。序列特征、遗传距离和系统进化分析结果都表明本文研究的青蟹均为S. paramamosain。NJ、BAYES和ML系统进化树显示S. paramamosain与S. tranquebarica互为姐妹种,S. olivecea应该是4种青蟹中最早分化出来的种类。10个地理群体130只拟穴青蟹的线粒体DNA(mitochondrial DNA,mtDNA)细胞色素氧化酶亚基I(COI)基因序列Mantel检验结果显示群体间的遗传分化程度与地理距离没有显著的相关性。分子进化中性检验结果表明自然选择在分子进化过程中起了重要作用,并暗示该物种在最近经历了一个快速的群体爆发及扩张事件。
Resumo:
首先提出了一种新的基于卡尔曼滤波及牛顿预测的角加速度估计方法,在已知电机驱动系统位置信息的情况下,利用卡尔曼滤波实时估计系统的角加速度;同时采用牛顿预测方法解决估计算法的滞后问题,进一步提高了估计加速度的响应频带.以此为基础,本文进一步分析了利用估计加速度进行反馈控制以增强系统对外扰动的鲁棒性问题,提出了加速度反馈控制策略的设计准则并分析了稳定性.在一个直接驱动机器人关节上针对上述加速度估计及控制方法进行了实验研究:将估计加速度的实验结果与实测加速度(利用加速度计)的实验结果进行了比较分析,从而定量地揭示出估计加速度及其反馈控制在实际系统中的可行性及有效性.
Resumo:
根据主UUV观测系统测量的从UUV方位信息精度高、距离信息精度低的特点,将遗忘因子和位置权值构成的综合权值融入递推最小二乘算法(RLS)用于从UUV航行参数分析,避免采用EKF算法对观测噪声要求高的缺陷,克服数据饱和现象。同时对从UUV方位信息进行预处理以提高航行参数估计的收敛速度。仿真实验证明了方法的有效性。
Resumo:
This thesis bases on horizontal research project “The research about the fine structure and mechanical parameters of abutment jointed rock mass of high arch dam on Jinping Ⅰ Hydropower Station, Yalong River” and “The research about the fine structure and mechanical parameters of the columnar basalt rock mass on Baihetan Hydropower Station, Jinsha River”. A rounded system about the fine structure description and rock mass classification is established. This research mainly contains six aspects as follow: (1) Methods about fine structure description of the window rock mass; (2) The window rock mass classification about the fine structure; (3) Model test study of intermittent joints; (4) Window rock mass strength theory; (5) Numerical experimentations about window rock mass; (6) The multi-source fusion of mechanical parameters based on Bayes principle. Variation of intact rock strength and joint conditions with the weathering and relaxation degree is studied through the description of window rock mass. And four principal parameters: intact rock point load strength, integration degree of window rock mass, joint conditions, and groundwater condition is selected to assess the window rock mass. Window rock mass is classified into three types using the results of window rock mass fine structure description combined with joints develop model. Scores about intact rock strength, integrality condition, divisional plane condition and groundwater conditions are given based on window rock mass fine structure description. Then quality evaluation about two different types of rock mass: general joint structure and columnar jointing structure are carried out to use this window rock mass classification system. Application results show that the window rock mass classification system is effective and applicable. Aimed at structural features of window structure of “the rock mass damaged by recessive fracture”, model tests and numerical models are designed about intermittent joints. By conducting model tests we get shear strength under different normal stress in integrated samples, through samples and intermittent joints samples. Also, the changing trends of shear strength in various connectivity rates are analyzed. We numerically simulate the entire process of direct shear tests by using PFC2D. In order to tally the stress-strain curve of numerical simulation with experimental tests about both integrated samples and through samples, we adjust mechanical factors between particles. Through adopting the same particle geometric parameter, the numerical sample of intermittent joints in different connective condition is re-built. At the same time, we endow the rock bridges and joints in testing samples with the fixed particle contacting parameters, and conduct a series of direct shear tests. Then the destructive process and mechanical parameters in both micro-prospective and macro-prospective are obtained. By synthesizing the results of numerical and sample tests and analyzing the evolutionary changes of stress and strain on intermittent joints plane, we conclude that the centralization of compressive stress on rock bridges increase the shear strength of it. We discuss the destructive mechanics of intermittent joints rock under direct shear condition, meanwhile, divide the whole shear process into five phases, which are elasticity phase, fracture initiation phase, peak value phase, after-peak phase and residual phase. In development of strength theory, the shear strength mechanisms of joint and rock bridge are analyzed respectively. In order to apply the deducted formulation conveniently in the real projects, a relationship between these formulations and Mohr-Coulomb hypothesis is built up. Some sets of numerical simulation methods, i.e. the distinct element method (UDEC) based on in-situ geology mapping are developed and introduced. The working methods about determining mechanical parameters of intact rock and joints in numerical model are studied. The operation process and analysis results are demonstrated detailed from the research on parameters of rock mass based on numerical test in the Jinping Ⅰ Hydropower Station and Baihetan Hydropower Station. By comparison,the advantages and disadvantages are discussed. Results about numerical simulation study show that we can get the shear strength mechanical parameters by changing the load conditions. The multi-source rock mass mechanical parameters can be fused by the Bayes theory, which are test value, empirical value and theoretical value. Then the value range and its confidence probability of different rock mass grade are induced and these data supports the reliability design.
Resumo:
Impedance inversion is very important in seismic technology. It is based on seismic profile. Good inversion result is derived from high quality seismic profile, which is formed using high resolution imaging resolution. High-resolution process demands that signal/noise ratio is high. It is very important for seismic inversion to improve signal/noise ratio. the main idea is that the physical parameter (wave impedance), which describes the stratigraphy directly, is achieved from seismic data expressing structural style indirectly. The solution of impedance inversion technology, which is based on convolution model, is arbitrary. It is a good way to apply the priori information as the restricted condition in inversion. An updated impedance inversion technology is presented which overcome the flaw of traditional model and highlight the influence of structure. Considering impedance inversion restricted by sedimentary model, layer filling style and congruence relation, the impedance model is built. So the impedance inversion restricted by geological rule could be realized. there are some innovations in this dissertation: 1. The best migration aperture is achieved from the included angle of time surface of diffracted wave and reflected wave. Restricted by structural model, the dip of time surface of reflected wave and diffracted wave is given. 2. The conventional method of FXY forcasting noise is updated, and the signal/noise ratio is improved. 3. Considering the characteristic of probability distribution of seismic data and geological events fully, an object function is constructed using the theory of Bayes estimation as the criterion. The mathematics is used here to describe the content of practice theory. 4. Considering the influence of structure, the seismic profile is interpreted to build the model of structure. A series of structure model is built. So as the impedance model. The high frequency of inversion is controlled by the geological rule. 5. Conjugate gradient method is selected to improve resolving process for it fit the demands of geophysics, and the efficiency of algorithm is enhanced. As the geological information is used fully, the result of impedance inversion is reasonable and complex reservoir could be forecasted further perfectly.
Resumo:
Formation resistivity is one of the most important parameters to be evaluated in the evaluation of reservoir. In order to acquire the true value of virginal formation, various types of resistivity logging tools have been developed. However, with the increment of the proved reserves, the thickness of interest pay zone is becoming thinner and thinner, especially in the terrestrial deposit oilfield, so that electrical logging tools, limited by the contradictory requirements of resolution and investigation depth of this kinds of tools, can not provide the true value of the formation resistivity. Therefore, resitivity inversion techniques have been popular in the determination of true formation resistivity based on the improving logging data from new tools. In geophysical inverse problems, non-unique solution is inevitable due to the noisy data and deficient measurement information. I address this problem in my dissertation from three aspects, data acquisition, data processing/inversion and applications of the results/ uncertainty evaluation of the non-unique solution. Some other problems in the traditional inversion methods such as slowness speed of the convergence and the initial-correlation results. Firstly, I deal with the uncertainties in the data to be processed. The combination of micro-spherically focused log (MSFL) and dual laterolog(DLL) is the standard program to determine formation resistivity. During the inversion, the readings of MSFL are regarded as the resistivity of invasion zone of the formation after being corrected. However, the errors can be as large as 30 percent due to mud cake influence even if the rugose borehole effects on the readings of MSFL can be ignored. Furthermore, there still are argues about whether the two logs can be quantitatively used to determine formation resisitivities due to the different measurement principles. Thus, anew type of laterolog tool is designed theoretically. The new tool can provide three curves with different investigation depths and the nearly same resolution. The resolution is about 0.4meter. Secondly, because the popular iterative inversion method based on the least-square estimation can not solve problems more than two parameters simultaneously and the new laterolog logging tool is not applied to practice, my work is focused on two parameters inversion (radius of the invasion and the resistivty of virgin information ) of traditional dual laterolog logging data. An unequal weighted damp factors- revised method is developed to instead of the parameter-revised techniques used in the traditional inversion method. In this new method, the parameter is revised not only dependency on the damp its self but also dependency on the difference between the measurement data and the fitting data in different layers. At least 2 iterative numbers are reduced than the older method, the computation cost of inversion is reduced. The damp least-squares inversion method is the realization of Tikhonov's tradeoff theory on the smooth solution and stability of inversion process. This method is realized through linearity of non-linear inversion problem which must lead to the dependency of solution on the initial value of parameters. Thus, severe debates on efficiency of this kinds of methods are getting popular with the developments of non-linear processing methods. The artificial neural net method is proposed in this dissertation. The database of tool's response to formation parameters is built through the modeling of the laterolog tool and then is used to training the neural nets. A unit model is put forward to simplify the dada space and an additional physical limitation is applied to optimize the net after the cross-validation method is done. Results show that the neural net inversion method could replace the traditional inversion method in a single formation and can be used a method to determine the initial value of the traditional method. No matter what method is developed, the non-uniqueness and uncertainties of the solution could be inevitable. Thus, it is wise to evaluate the non-uniqueness and uncertainties of the solution in the application of inversion results. Bayes theorem provides a way to solve such problems. This method is illustrately discussed in a single formation and achieve plausible results. In the end, the traditional least squares inversion method is used to process raw logging data, the calculated oil saturation increased 20 percent than that not be proceed compared to core analysis.
Resumo:
It is a weighting process to justify the importance of different items. This paper is about how the estimator distributes profiling the weights to different items. This paper is about using design of psychological experiment to figure out the profiles of the weights of different ranked items in three weighting methods, and in the experiment we use five topics as experimental materials. At the same time, we controlled the factors such as the familiarity about the topic and the number of items. Then we use the curve estimation to figure out the exact profiles and use ANOVA to test the topic effects. Curve estimation result shows that there is difference between the profiles of the weights of different ranking items in three weighting methods. To PA, the weighting profile is logarithmic curving style, and to DR, the weighting profile is linear style. ANOVA result shows that there are topic effects to different weighting profiles. But to go ahead, when we use point allocation (PA) to the more important items, the topics seems to have little effects. The methods have relatively more effect than the topics. The result also indicates that to PA methods, there is no significant difference the weight profiles between the fix-sum and the open-sum. This result has a contribution to the basic research to the management science and social science.