基于混合二阶隐马尔可夫模型的基因结构预测

在基因预测时,待研究的生物序列中的残基(氨基酸或核甘酸)具有高度的相关性,因此,观测噪声和马尔可夫链不相互独立的条件下的混合隐马尔可夫模型比普通隐马尔可夫模型更适用于基因预测功能.介绍了一种基于混合二阶隐马尔可夫模型(HMM2)的基因识别系统,该系统的预测精度在在核苷酸和外显子水平上均与国外同类研究水平相当.     

应用阶数自学习自回归隐马尔可夫模型对控制过程异常数据的在线检测

针对过程工业中强噪声环境下实时采集的控制过程海量数据难以在线精确检测的问题,提出了基于阶数自学习自回归隐马尔可夫模型(ARHMM)的工业控制过程异常数据在线检测方法.该算法采用自同归(AR)模型对时间序列进行拟合,利用隐马尔科夫模型(HMM)作为数据检测的工具,避免了传统检测方法中需要预先设定检测阈值的问题,并将传统的...     

基于加权观测的隐马尔可夫模型

针对隐马尔可夫模型无法融合分类结果权值的问题,文中提出加权观测隐马尔可夫模型(WOHMM),并给出模型中概率计算、参数学习、序列标注三个基本问题的解决算法.使用公开数据集对参数学习和序列标注问题进行仿真实验,结果表明,WOHMM的参数学习算法能得到更接近真实值的模型参数,序列标注算法的效果较优.     

一种基于RBF-HMM的网络入侵检测方法研究

本文提出了基于RBF-HMM模型的网络入侵检测方法,给出了该模掣的训练和识别方法.因为HMM模型的分类决策能力和对不确定信息的描述能力不理想,而人工神经网络对动志时间序列的建模能力尚不尽如人意,所以将RBF神经网络集成到HMM框架中,用RBF神经网络为HMM提供状态概牢输出.通过RBF神经网络的粗分类,克服了HMM的缺...     

模糊深隐马尔可夫模型研究

针对经典马尔可夫模型没有考虑模型应用中状态、观测量间的上下文相关性以及状态转移概率动态性、可变性,提出一种模糊深隐马尔可夫模型.该模型通过增加观测值间的相关性、解决概率转移问题中的不确定性和改进参数优化算法,使之能够较好地应用于强噪声、训练数据缺损等情形的模式识别中.理论证明,显式模糊深隐马尔可夫模型在同等模型复杂度下具有模型优化程度高、区分度好、误识率低、鲁棒性高的特性.     

基于隐马尔可夫模型在股票择时上的应用与研究

隐马尔可夫模型(HMM)是由马尔可夫过程衍生出的概率图模型,常被用于语音模式识别、生物基因序列标记、金融时间序列预测等.主要是验证隐马尔可夫模型在量化金融领域的应用可行性.选取上证指数(上海证券交易所全部上市股票,包括A股和B股,反映了上海证券交易所上市股票价格的变动情况),指数在2000年到2004年这个时间段的数据并进行特征选取,通过实验对隐马尔可夫模型的预测结果与实际结果进行对比,发现隐马尔可夫模型能够更好地识别金融市场的状态,预测金融市场的走向,从而验证其在我国金融市场的应用可行性.     

基于拉普拉斯脸和隐马尔可夫的视频人脸识别

提出了一种基于拉普拉斯脸和隐马尔可夫模型的视频人脸识别方法。在训练过程中，采用拉普拉斯脸方法将每一视频序列中的人脸图像映射到拉普拉斯空间，将降维后的特征作为观测值，通过隐马尔可夫模型得到每一训练视频的统计特性和时间动态特性。在识别过程中，用每一个训练视频的隐马尔可夫模型来分析测试视频的时间动态特性，计算出每一训练模型产生该序列的概率，概率最大值所对应的模型就是待识别序列所属的类别。实验结果表明，该方法能够很好地进行视频人脸识别。     

基于RBF神经网络的混沌时间序列预测

本文提出将径向基函数(RBF)神经网络应用于混沌时间序列的预测,设计了一个三层RBF网络结构.对于三个典型的混沌系统,在不同的噪声水平下,采用RBF网络模型分别进行了预测研究.仿真结果表明,采用RBF网络进行混沌时间序列的预测能够取得比现有其它方法更好的效果.     

用于非线性时间序列预测的POD-RBF神经网络

基于正规正交分解(Proper Orthogonal Decomposition,POD)提出一种适用于非线性时间序列预测的径向基函数(Radial Basis Function,RBF)神经网络模型-POD-RBF神经网络模型.该模型在选取中心时考虑了时间序列数据之间的时序关系,并且使得中心的选取具有并行性.股票价格预测问题的模拟结果表明,POD-RBF神经网络可以有效地用于非线性时间序列预测问题.与基于硬C均值(Hard C-means,HCM)聚类的RBF神经网络(HCM-RBF)和基于正交最小二乘(Orthogonal LestSquare,OLS)的RBF神经网络(OLS-PBF)相比,POD-RBF神经网络不仅具有更好的训练、预测精度,而且具有更好的收敛稳定性、更好的泛化能力和抵抗噪声干扰的能力.     

一种基于非参数贝叶斯估计的PHMM模型

传统时间序列模型很少从时间序列系统本身角度分析时间序列数据.目前,一种基于模式的隐马尔科夫模型(PHMM)实现了对时序数据系统的内部状态转换机制的建模,从而在时间序列的多步预测和相关性检测上提供了一种高效途径.然而,PHM M模型在考虑隐状态内部观测数据分布时,直接采用高斯分布进行估计的方法受训练数据影响较大.因此,提出一种利用非参数贝叶斯估计来计算模型隐状态内分布的方法.考虑到与固定状态集的隐马科夫模型不同,PHMM模型是一种无限状态隐马尔科夫模型,通过引入非参数HDP过程实现对PHMM模型两层随机过程的解释.实验结果证明,引入非参数估计后模型的预测效率显著提升.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

Enhancing a leaf radiative transfer model to estimate concentrations and in vivo specific absorption coefficients of total carotenoids and chlorophylls a and b from single-needle reflectance and transmittance

The relative concentrations of different pigments within a leaf have significant physiological and spectral consequences. Photosynthesis, light use efficiency, mass and energy exchange, and stress response are dependent on relationships among an ensemble of pigments. This ensemble also determines the visible characteristics of a leaf, which can be measured remotely and used to quantify leaf biochemistry and structure. But current remote sensing approaches are limited in their ability to resolve individual pigments. This paper focuses on the incorporation of three pigments—chlorophyll a, chlorophyll b, and total carotenoids—into the LIBERTY leaf radiative transfer model to better understand relationships between leaf biochemical, biophysical, and spectral properties.Pinus ponderosa and Pinus jeffreyi needles were collected from three sites in the California Sierra Nevada. Hemispheric single-leaf visible reflectance and transmittance and concentrations of chlorophylls a and b and total carotenoids of fresh needles were measured. These data were input to the enhanced LIBERTY model to estimate optical and biochemical properties of pine needles. The enhanced model successfully estimated reflectance (RMSE = 0.0255, BIAS = 0.00477, RMS%E = 16.7%), had variable success estimating transmittance (RMSE = 0.0442, BIAS = 0.0294, RMS%E = 181%), and generated very good estimates of carotenoid concentrations (RMSE = 2.48 µg/cm², BIAS = 0.143 µg/cm², RMS%E = 20.4%), good estimates of chlorophyll a concentrations (RMSE = 10.7 µg/cm², BIAS = − 0.992 µg/cm², RMS%E = 21.1%), and fair estimates of chlorophyll b concentrations (RMSE = 7.49 µg/cm², BIAS = − 2.12 µg/cm², RMS%E = 43.7%). Overall root mean squared errors of reflectance, transmittance, and pigment concentration estimates were lower for the three-pigment model than for the single-pigment model. The algorithm to estimate three in vivo specific absorption coefficients is robust, although estimated values are distorted by inconsistencies in model biophysics. The capacity to invert the model from single-leaf reflectance and transmittance was added to the model so it could be coupled with vegetation canopy models to estimate canopy biochemistry from remotely sensed data.     

Mr. Twinn’s bombes

This article discusses the history and design of the special versions of the bombe key-finding machines used by Britain’s Government Code & Cypher School (GC&CS) during World War II to attack the Enigma traffic of the Abwehr (the German military intelligence service). These special bombes were based on the design of their more numerous counterparts used against the traffic of the German armed services, but differed from them in important ways that highlight the adaptability of the British bombe design, and the power and flexibility of the diagonal board. Also discussed are the changes in the Abwehr indicating system that drove the development of these machines, the ingenious ways in which they were used, and some related developments involving the bombes used by the U.S. Navy’s cryptanalytic unit (OP-20-G).