基于智能全间隔自适应模糊支持向量机的水质分类

提出了一种新型具有良好特性的支持向量机——全间隔自适应模糊支持向量机(TAFSVM)。运用实值遗传算法(RGA)对其进行参数优选,得到一种新的智能模型——实值遗传算法优化的全间隔自适应模糊支持向量机(RGATAFSVM)模型,并且应用于四种不同的水质数据分类。实验结果表明,提出的模型相对标准支持向量机、BP神经网络和单因子分类方法具有较高的分类精度和较高的稳定性,是一种有效的水质分类方法。

多特征主成分分析与声图相结合的海底底质分类

通过提取多种回声特征构造全特征向量,并对全特征向量进行主成分分析,计算出对底质分类贡献率最大的特征组,实现海底底质的分类.采用两种分类方法对胶州湾实测数据进行比较,可得出下列结论:应用多特征主成分分析与声图相结合的分类结果优于单纯使用声纳图像的分类结果.

二次曲线方程的化简

本文引入平移式半向量，旋转式半向量，全向量、定位方程组，利用它们来进行二次曲线方程的化简，改变传统上分为有心和无心的做法．

基于ETAFSVM的高光谱遥感图像自动波段选择和分类

提出了一种新型的具有良好特性的支持向量机——全间隔自适应模糊支持向量机(TAFSVM),并提出一种新的遗传算法——智能遗传算法(IGA)来设计一个TAFSVM分类器,称为ETAFSVM,同时优化高光谱遥感图像自动波段选择和TAFSVM参数集,并且结合5-fold交叉验证来确定其泛化能力,最后将ETAFSVM应用于高光谱遥感图像数据。通过先进行自适应波段选择后再用径向基神经网络分类器、K-最近邻分类器和标准支持向量机等3种方法进行全部分类精度比较,以及与这3种方法直接进行类别分类精度和平均分类精度比较,其结果表明运用ETAFS-VM不仅可以自动进行波段选择,而且分类精度较高,对Hughes现象敏感性较低,是进行高光谱遥感图像分类的一种有效方法。

The Submanifolds with Parallel Mean Curvature Vector in a Locally Symmetric and Conformally Flat Riemannian Manifold

In the present paper we obtain the following result: Theorem Let M^R be a compact submanifold with parallel mean curvature vector in a locally symmetric and conformally flat Riemannian manifold N^(n+p)(p>1). If then M^n lies in a totally geodesic submanifold N^(n+1).

Research on highly nonlinear photonic bandgap fibers

A new type of highly nonlinear photonic bandgap fiber with modified honeycomb lattice is brought forward. Based on full-vector plane-wave method, the structure of bandgaps and the distributions of fundamental mode field are analyzed. Then its nonlinear coefficient is calculated, and the effect of each structural pa- rameter on the nonlinear coefficient is discussed. At last, considering many factors synthetically, we make some optimization design of the structural parameters. It can be concluded that this new type of photonic bandgap fiber can gain the nonlinear coefficient of 30 W^-1 km^-1.

基于ITAFSVM的微阵列数据特征选择和分类

支持向量机已经被成功应用于基因表达谱数据分析。但是,仍有开放问题需要解决:①支持向量机不能自动进行基因表达谱数据的特征选择;②支持向量机的参数优选没有简单有效的办法。一种新型具有良好特性的支持向量机——全间隔自适应模糊支持向量机(TAFSVM)被提出。并且提出一种新的遗传算法——智能遗传算法(IGA)来设计一个TAFSVM分类器,称为ITAFSVM,同时优化TAFSVM参数集和特征选择,并且结合10-fold交叉验证来确定其泛化能力。最后将ITAFSVM应用于四种基因表达谱数据集。通过与进化支持向量机(ESVM)方法、粗糙集与径向基神经网络组合(RBF-RBFNN)方法进行了比较,实验结果表明运用ITAFSVM不仅可以自动进行基因表达谱数据特征选择,而且分类精度和稳定性都较高,速度更快。

基于实值遗传算法与TAFSVM的遥感图像分类

支持向量机已经被成功应用于遥感图像分类。一种新型具有良好特性的支持向量机--全间隔自适应模糊支持向量机被提出。这种新型的支持向量机具有通过训练集的模糊性来增强泛化能力;对不平衡训练集具有自适应性,对正负数据采用不同的损失算法,可以提高正确分类率;通过引进全间隔算法来代替软间隔算法,可以得到更低的泛化误差等优良特性,符合遥感图像数据的内在规律。并且运用实值遗传算法对其进行参数优选,得到一种新的分类器——AGATAFSVM。最后将该分类器应用于遥感图像分类。实验结果表明,该分类器非常适用于遥感图像分类,分类精度和稳定性明显高于径向基神经网络分类器、最近邻分类器和标准支持向量机。

Signal classification system using global-local feature extraction algorithm

A continuous wavelet transform(CWT)and globallocal feature(GLF)extraction-based signal classificationalgorithm is proposed to improve the signal classification accuracy.First,the CWT is utilized to generate the timefrequency scalogram.Then,the GLF extraction method is proposed to extract features from the time-frequency scalogram.Finally,a classification method based on the support vector machine(SVM)is proposed to classify the extracted features.Experimental results show that the extended binary phase shift keying(EBPSK)bit error rate(BER)of the proposed classification algorithm is1.3x10_5under the environment of additional white Gaussian noise with the signal-to-noise ratio of-3dB,which is24times lower than that of the SVM-based signal classification method.Meanwhile,the BER using the GLF extraction method is13times lower than the one using the global feature extraction method and24times lower than the one using the local feature extraction method.

Quantitative assessment of flight safety under atmospheric icing conditions

A quantitative assessment method is proposed to sense the specific effects of atmospheric icing conditions on flight safety. A six degree-of-freedom computational flight dynamics model is used to study the effects of ice accretion on aircraft dynamics, and a pilot model is also involved. In order to investigate icing severity under different icing conditions, support vector regression is applied in establishing relationship between aircraft icing parameter and weather conditions. Considering the characteristics of aircraft icing accidents, a risk probability assessment model optimized by the particle swarm method is developed to measure the safety level. In particular, angle of attack is chosen as a critical parameter in this method. Results presented in the paper for a series of simulation show that this method captures the basic effects of atmospheric icing conditions on flight safety, which may provide an important theoretical reference for icing accidents avoidance.

The Dual Pair with the Signed-weak Gliding Hump Property

In this paper, we introduce the signed weak gliding hump property in a dual pair with the structure of a system of sections and show that if a dual pair [E, F] has the signed weak gliding hump property, then the β-dual space of E is a weak sequentially complete space if and only if for every n ∈N,(F[n] ,σ(F[n] ,E[n] )) is sequentially complete. Furthermore, we also prove that if [E,F] has the signed weak gliding hump property, then (E,τ(E,E<β> )) is an AK- space.

Sasakian Submanifolds of Kaehlerian Manifolds(Ⅱ)

In this paper,it is proved that the Sasakian anti-holomorphic submanifolds of a Kaehlerian manifold is characterized by D-totally umbilical,and some curvature properties of the CR-submanifolds are ohtained.

Key Exchange Protocol Based on Tensor Decomposition Problem

The hardness of tensor decomposition problem has many achievements, but limited applications in cryptography, and the tensor decomposition problem has been considered to have the potential to resist quantum computing. In this paper, we firstly proposed a new variant of tensor decomposition problem, then two one-way functions are proposed based on the hard problem. Secondly we propose a key exchange protocol based on the one-way functions, then the security analysis, efficiency, recommended parameters and etc. are also given. The analyses show that our scheme has the following characteristics: easy to implement in software and hardware, security can be reduced to hard problems, and it has the potential to resist quantum computing.Besides the new key exchange can be as an alternative comparing with other classical key protocols.

GA-SVC model and application of comprehensive evaluation of coal mine essential safety management

In order to evaluate the level of the coal mine essential safety management, the comprehensive index system was designed base on the connotation principle of the mine essential safety management. Due to the disadvantage of index weight setting by subjective idea in the former method, support vector classification algorithm was used to assess the level of coal mine essential safety management. According to the advantages of the global search capability of the genetic algorithm, support vector classification parameters optimization method was proposed based on genetic algorithm, and genetic algorithm-support vector classification model of coal mine essential safety management assessment was established. Learning samples were constructed on the basis of former data of mine essential safety management evaluation. The test results show that the genetic algorithm-support vector classification model has higher evaluation accuracy and good generalization ability, and the advantage of no need for artificial setting of index weight and absence of the subjective factors influence to evaluation results.

Effect of Solving Models on Euler Vectors

In the process of solving Euler vectors based on GNSS horizontal movement field,the number of estimated parameters can affect Euler vector results. This issue is analyzed through theoretical deduction and practical example in this paper. Firstly,the difference between the results of Euler vectors in different solving models is deduced. Meanwhile, based on GNSS horizontal movement field in the Chinese mainland from 2004 to 2007,two common models( RRM and REHSM) are used to discuss the impact of solving models on Euler vectors and the follow-up study. The result shows that the maximum value of the difference in a block's entire rotation can reach 2. 6mm /a,and should not be ignored. Therefore,the results of horizontal movement are different using different kinematic block models,and this should be paid more attention in the analysis of crustal horizontal movement.

C-Totally Real Submanifolds with Parallel Mean Curvature Vector of Sasakian Space Form

We have discussed the C-totally real subrnanifolds with parallel mean curvature vector of Sasakian space form, obtained a formula of J.Simons type, and improved one result of S.Yamaguchi.

A geometric heat flow for vector fields

We introduce and study a geometric heat flow to find Killing vector fields on closed Riemannian manifolds with positive sectional curvature. We study its various properties, prove the global existence of the solution to this flow, discuss its convergence and possible applications, and its relation to the Navier-Stokes equations on manifolds and Kazdan-Warner-Bourguignon-Ezin identity for conformal Killing vector fields. We also provide two new criterions on the existence of Killing vector fields. A similar flow to finding holomorphic vector fields on K¨ahler manifolds will be studied by Li and Liu(2014).

Discrete-Time Chaotic Systems Synchronization Based on Vector Norms Approach

Suitable stabilization conditions obtained for continuous chaotic systems are generalized to discrete-time chaotic systems. The proposed approach, leading to these conditions for complete synchronization is based on the use of state feedback and aggregation techniques for stability studies associated with the arrow form matrix for system description. The results are successfully applied for two identical discrete-time hyper chaotic Henon maps with different orders and also for non-identical discrete-time chaotic systems with same order namely the Lozi and the Ushio maps.

On the lower bounds of the curvatures in a bounded domain

Let KD（z, z） be the Bergman kernel of a bounded domain 7P in Cn and Sect （z, ） and Ricci （z, ） be the holomorphic sectional curvature and Ricci curvature of the Bergman metric ds2 = T T：）（z,N）dzCdz respectively at the point z E T with tangent vector . It is proved by constructing suitable minimal functions that where z ∈D1 D D2, D1 is a ball contained in D and D2 is a ball containing D.

Laplacian on Complex Finsler Manifolds

In this paper, the Laplacian on the holomorphic tangent bundle T 1,0 M of a complex manifold M endowed with a strongly pseudoconvex complex Finsler metric is defined and its explicit expression is obtained by using the Chern Finsler connection associated with (M, F ). Utilizing the initiated "Bochner technique", a vanishing theorem for vector fields on the holomorphic tangent bundle T 1,0 M is obtained.