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Parallel Genetic Algorithm Based on the MPI Environment
Jing-Jun Zhang,Wen-Juan Liu,Guang-Yuan Liu
TELKOMNIKA : Indonesian Journal of Electrical Engineering , 2012, DOI: 10.11591/telkomnika.v10i7.1566
Abstract: Current genetic algorithm require both management of huge amounts of data and heavy computation, fulfilling these requirements calls for simple ways to implement parallel computing. In this paper, serial genetic algorithm was designed to parallel GA; this technology appears to be particularly well adapted to this task. Here we introduce two related mechanism: elite reserve strategy and MPI. The first can increase the possible to get the optimal solution of the population, while the message passing interface MPI support is adding to form a new coarse-grain model of distributed parallel genetic algorithm. This new algorithm is tested by the classical and effective Knapsack problem, analysis shows that, the introduction of the parallel strategies can reduce the communication between different machines and the scheduling time of the heterogeneous system, thereby accelerate the traditional genetic algorithm search process, ultimately concluded that the parallel genetic algorithm is very promising and this framework could have a wide range of applications while maintaining good computational efficiency, scalability and ease of maintenance.
Phylogeny of the Genus Chrysanthemum L.: Evidence from Single-Copy Nuclear Gene and Chloroplast DNA Sequences
Ping-Li Liu, Qian Wan, Yan-Ping Guo, Ji Yang, Guang-Yuan Rao
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0048970
Abstract: Chrysanthemum L. (Asteraceae-Anthemideae) is a genus with rapid speciation. It comprises about 40 species, most of which are distributed in East Asia. Many of these are narrowly distributed and habitat-specific. Considerable variations in morphology and ploidy are found in this genus. Some species have been the subjects of many studies, but the relationships between Chrysanthemum and its allies and the phylogeny of this genus remain poorly understood. In the present study, 32 species/varieties from Chrysanthemum and 11 from the allied genera were analyzed using DNA sequences of the single-copy nuclear CDS gene and seven cpDNA loci (psbA-trnH, trnC-ycf6, ycf6-psbM, trnY-rpoB, rpS4-trnT, trnL-F, and rpL16). The cpDNA and nuclear CDS gene trees both suggest that 1) Chrysanthemum is not a monophyletic taxon, and the affinity between Chrysanthemum and Ajania is so close that these two genera should be incorporated taxonomically; 2) Phaeostigma is more closely related to the Chrysanthemum+Ajania than other generic allies. According to pollen morphology and to the present cpDNA and CDS data, Ajania purpurea is a member of Phaeostigma. Species differentiation in Chrysanthemum appears to be correlated with geographic and environmental conditions. The Chinese Chrysanthemum species can be divided into two groups, the C. zawadskii group and the C. indicum group. The former is distributed in northern China and the latter in southern China. Many polyploid species, such as C. argyrophyllum, may have originated from allopolyploidization involving divergent progenitors. Considering all the evidence from present and previous studies, we conclude that geographic and ecological factors as well as hybridization and polyploidy play important roles in the divergence and speciation of the genus Chrysanthemum.
Adjacency Effect of Satellite Remote Sensing on Land Surface Studies
卫星对地遥感应用中的邻近效应研究

LIU Guang-Yuan,QIU Jin-Huan,
刘广员
,邱金桓

大气科学 , 2004,
Abstract: Sensitivities of satellite apparent reflectance to parameters of surface, atmosphere and satellite measurements are simulated with a 3-dimensional Monte-Carlo model. Researches are mainly focused on three aspects: Sensitivities of satellite apparent reflectance to non-uniform reflection surface;to the effective surface range;and relations between adjacency effect and satellite altitude. Based on the sensitivity, the main adjacency effect factors and mechanism are uncovered. Some notable results are given as follows: Adjacency effect caused by surface's non-uniformity is of high importance. On the kind of oasis surface adjacency effect is especially distinct. The bigger the aerosol optical depth and the more symmetric the scattering phase function, the stronger the sensitivity is. Within a fair large horizontal range the adjacency surface has effect on satellite apparent reflectance, and the more symmetric (for example, molecular) the phase function is, the bigger the effective surface range is. For a certain surface target, the higher the satellite altitude is, the bigger the adjacency effect is.
A Three-Dimensional Monte-Carlo Model of Surface-Atmosphere Coupled Radiation
一个三维Monte-Carlo地气耦合辐射传输模式

LIU Guang-Yuan,QIU Jin-Huan,
刘广员
,邱金桓

大气科学 , 2004,
Abstract: A reliable 3D Monte-Carlo model(3DMC) of surface-atmosphere coupled radiation is developed with higher computing efficiency. Its characteristics is showed in six aspects of release and finding the location of photons, receiving fashion of sensor, coupling of surface and atmosphere, computing radiance in high resolution with high accuracy and computing efficiency, respectively.
A Synergetic Algorithm for Static Face Recognition
静态人脸识别的一种协同学方法

WEN Wan-Hui,LIU Guang-Yuan,
温万惠
,刘光远

计算机科学 , 2006,
Abstract: A practicable algorithm for static face recognition is designed in this paper.Unlike the conventional meth- ods,this algorithm doesn't depend on the accurate location of face features.While new patterns are added into the sys- tem,the algorithm can form the new original vectors and their adjoint vectors rapidly.In the simulation,two choices for attention parameters got good results.
Emotion Recognition Using Four Physiological Signals Based on BPSO
基于BPSO的四种生理信号的情感状态识别

YANG Rui-Qing,LIU Guang-Yuan,
杨瑞请
,刘光远

计算机科学 , 2008,
Abstract: 通过生理信号来识别人的情感状态越来越引起人们的关注.如何提取有效的生理信号特征进行情感状态的分类,是情感识别的关键.本文采用离散二进制粒子群优化算法(BPS0)进行特征选择,以提高情感状态分类的效果.通过四种生理信号来识别四种情感状态,用最近邻法进行分类,总体识别率达到85%.仿真实验结果表明,将BPSO方法用于生理信号的特征选择是可行的.
A Novel Image Filtering Method Based on Iterative Fuzzy Control
一种新的基于迭代模糊控制的图像滤波方法

LU Rui-Hua,LIU Guang-Yuan,
鲁瑞华
,刘光远

计算机科学 , 2005,
Abstract: A novel iterative fuzzy control-based method of image filtering is proposed in this paper.The method has distinguishing properties of removing impulsive noise and smoothing out Gaussian noise while preserving edges and im- age details effectively.The proposed filtering approach is mainly based on the idea of not letting each point in the area of concern being uniformly fired by each of the basic fuzzy rules.Different modifications of the proposed filtering meth- od improve its performance greatly.
Emotion recognition from surface EMG signal using wavelet transform and neural network
基于小波变换与神经网络的表面肌电信号的情感识别

CHENG Bo,LIU Guang-yuan,
程波
,刘光远

计算机应用 , 2008,
Abstract: Emotion recognition is critical in affective computing. This paper adopted the wavelet transform to analyse the surface EMG signal instability feature. Surface EMG signal was decomposed by discrete wavelet transform (DWT) and maximum and minimum of the wavelet coefficients in every level were extracted. The extracted maximum and minimum of the wavelet coefficients were input to identify emotion by the BP neural network improved by Levenberg-Marquardt algorithm. Experimental result shows that the identification of four emotional signals (joy, anger, sadness and pleasure) is effective and it has great potential in practical application of emotion recognition.
Study on Successive Learning Chaotic Neural Network
连续学习混沌神经网络的研究

DUAN Shu-Kai LIU Guang-Yuan,
段书凯
,刘光远

计算机科学 , 2004,
Abstract: The applications of chaotic neural network in the field of message treatment especially in associative memories have drawn a lot of attention in recent years. In this paper, we propose a modified successive learning chaotic neural network (MSLCNN)model. It has two important features: (l)It can distinguish unknown patterns from the known patterns according to different response of the neural network when different input applied. C2)It can learn unknown pattern successively. When a stored pattern is given to the network, the network searches around the input pattern. However, while an unknown pattern is given, a chaotic itinerancy appears. The MSLCNN makes use of these features to distinguish unknown patterns from the known patterns and learn the unknown patterns successively. A series of computer simulations are done to demonstrate the potentiality of the proposed model.
A Chaotic Neural Network and its Applications in Separation of Superimposed Pattern and Many-to-Many Associative Memory
混沌神经网络在分离叠加模式和多对多联想记忆中的应用

LIU Guang-Yuan DUAN Shu-Kai,
刘光远
,段书凯

计算机科学 , 2003,
Abstract: In this paper, we propose a modified chaotic associative memory neural network(MCAM). It has two important features: it can recall stored patterns from superimposed input; (2)it can deal with many-to-many associative memory. The computer simulations show the effectiveness of the proposed model.
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