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Search Results: 1 - 10 of 32265 matches for " Yao Xin "
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General Simulated Annealing
Yao Xin,Li Guojie
计算机科学技术学报 , 1991,
Abstract: Simulated annealing is a new kind of random search methods developed in recent years.It can also be considered as an extension to the classical hill-climbing method in AI--probabilistic hill-cimbing.One of its most important features is its global convergence.The convergence of simulated annealing algorithm is determined by state generating probability,state accepting probability,and temperature decreasing rate,This paper gives a generalized simulated annealing algorithm with dynamic generating and accepting probabilities.The paper also shows that the generating and accepting probabilities can adopt many different kinds of distributions while the global convergence is guaranteed.
Simulated annealing and joint manufacturing batch-sizing
Sarker Ruhul,Yao Xin
Yugoslav Journal of Operations Research , 2003, DOI: 10.2298/yjor0302245s
Abstract: We address an important problem of a manufacturing system. The system procures raw materials from outside suppliers in a lot and processes them to produce finished goods. It proposes an ordering policy for raw materials to meet the requirements of a production facility. In return, this facility has to deliver finished products demanded by external buyers at fixed time intervals. First, a general cost model is developed considering both raw materials and finished products. Then this model is used to develop a simulated annealing approach to determining an optimal ordering policy for procurement of raw materials and also for the manufacturing batch size to minimize the total cost for meeting customer demands in time. The solutions obtained were compared with those of traditional approaches. Numerical examples are presented. .
A Matlab/Simulink Development and Verification Platform for a Frequency Estimation System  [PDF]
Yingtai Li, Lisheng Yang, Xin Lei, Rui Ma, Luncai Liu, Fan Liu, Yao Yao
Journal of Computer and Communications (JCC) , 2018, DOI: 10.4236/jcc.2018.611010
The precise estimation of the frequency of the signal is of great significance in the Radar system, the electronic warfare system and many other systems. In this paper, we propose a development and verification platform for the frequency estimation system in the Matlab and Simulink environment. Its open-extensibility architecture enables the performance evaluation of different frequency estimation algorithms and its graphic interface can greatly promote the system design, simulation and verification efficiency.
Recent Advances in Evolutionary Computation
Xin Yao,Yong Xu,

计算机科学技术学报 , 2006,
Abstract: Evolutionary computation has experienced a tremendous growth in the last decade in both theoretical analyses and industrial applications. Its scope has evolved beyond its original meaning of "biological evolution" toward a wide variety of nature inspired computational algorithms and techniques, including evolutionary, neural, ecological, social and economical computation, etc., in a unified frarnework. Many research topics in evolutionary computation nowadays are not necessarily "evolutionary". This paper provides an overview of some recent advances in evolutionary computation that have been made in CERCIA at the University of Birmingham, UK. It covers a wide range of topics in optimization, learning and design using evolutionary approaches and techniques, and theoretical results in the computational time complexity of evolutionary algorithms. Some issues related to future development of evolutionary computation are also discussed.
On the Impact of Mutation-Selection Balance on the Runtime of Evolutionary Algorithms
Per Kristian Lehre,Xin Yao
Physics , 2010,
Abstract: The interplay between mutation and selection plays a fundamental role in the behaviour of evolutionary algorithms (EAs). However, this interplay is still not completely understood. This paper presents a rigorous runtime analysis of a non-elitist population-based EA that uses the linear ranking selection mechanism. The analysis focuses on how the balance between parameter $\eta$, controlling the selection pressure in linear ranking, and parameter $\chi$ controlling the bit-wise mutation rate, impacts the runtime of the algorithm. The results point out situations where a correct balance between selection pressure and mutation rate is essential for finding the optimal solution in polynomial time. In particular, it is shown that there exist fitness functions which can only be solved in polynomial time if the ratio between parameters $\eta$ and $\chi$ is within a narrow critical interval, and where a small change in this ratio can increase the runtime exponentially. Furthermore, it is shown quantitatively how the appropriate parameter choice depends on the characteristics of the fitness function. In addition to the original results on the runtime of EAs, this paper also introduces a very useful analytical tool, i.e., multi-type branching processes, to the runtime analysis of non-elitist population-based EAs.
Gene selection algorithms for microarray data based on least squares support vector machine
E Ke Tang, PN Suganthan, Xin Yao
BMC Bioinformatics , 2006, DOI: 10.1186/1471-2105-7-95
Abstract: A gene selection method searches for an optimal or near optimal subset of genes with respect to a given evaluation criterion. In this paper, we propose a new evaluation criterion, named the leave-one-out calculation (LOOC, A list of abbreviations appears just above the list of references) measure. A gene selection method, named leave-one-out calculation sequential forward selection (LOOCSFS) algorithm, is then presented by combining the LOOC measure with the sequential forward selection scheme. Further, a novel gene selection algorithm, the gradient-based leave-one-out gene selection (GLGS) algorithm, is also proposed. Both of the gene selection algorithms originate from an efficient and exact calculation of the leave-one-out cross-validation error of the least squares support vector machine (LS-SVM). The proposed approaches are applied to two microarray datasets and compared to other well-known gene selection methods using codes available from the second author.The proposed gene selection approaches can provide gene subsets leading to more accurate classification results, while their computational complexity is comparable to the existing methods. The GLGS algorithm can also better scale to datasets with a very large number of genes.Recently, discriminant analysis of microarray data has been widely used to assist diagnosis [1-3]. Given some microarray data characterized by a large number of genes' expressions, a typical discriminant analysis constructs a classifier based on the given data to distinguish between different disease types. In practice, a gene selection procedure to select the most informative genes from the whole gene set is usually employed. There are several reasons for performing gene selection. First, the cost of clinical diagnosis can be reduced with gene selection since it is much cheaper to focus on only the expressions of a few genes for diagnosis instead of the whole gene set. Second, many of the genes in the whole gene set are redundant. Altho
分离酶的作用及其调节Activity of Separase and Its Regulation
遗传 , 2004,
Abstract: 姐妹染色单体的分离是一精确时空调控事件,分离的紊乱会造成遗传物质传递的不稳定,从而可能引起严重的后果—细胞或个体的死亡或病态。在真核生物细胞中,一种比较保守的机制调控着姐妹染色单体的分离:随DNA复制过程建立由黏合素维持的姐妹染色单体的结合,在有丝分裂中期向后期转变过程中,随保全素的降解,分离酶发挥活性,裂解黏合素一个亚单位,促成黏合素蛋白质复合体的解离和姐妹染色单体的分离。Abstract: Sister chromatids separation is under precise regulation during cell cycle. Any turbulence happened in the separation process can cause instability in the transmission of inherited material ,and may cause: death or disease of cell or even individual. In eukaryotic cells, one conserved mechanism governs the separation of sister chromatids. Cohesion between sister chromatids is established during DNA replication and depends on a multiprotein complex called cohesin. At the metaphase to anaphase transition, separase is activated by proteolysis of securin. Separase can cleave one of cohesin's subunits, and then promote cohesin dissociation and sister chromatids separation.
Time Complexity Analysis of an Evolutionary Algorithm for Finding Nearly Maximum Cardinality Matching
Jun HE,Xin YAO,

计算机科学技术学报 , 2004,
Abstract: Most of works on the time complexity analysis of evolutionary algorithms have always focused on some artificial binary problems The time complexity of the algorithms for combinatorial optimisation has not been well understood. This paper considers the time complexity of an evolutionary algorithm for a classical combinatorial optimisation problem, to find the maximum cardinality matching in a graph. It is shown that the evolutionary algorithm can produce, a matching with nearly maximum cardinality in average polynomial time. The work is partially supported by Engineering and Physical Sciences Research Council (GR/R52541/01) and State Key Lab of Software Engineering at Wuhan University. The work was reported at UK 2002 Workshop on Computational Intelligence. Jun He received his M.Sc. degree in mathematics and Ph.D. degree in computer science from Wuhan University, China, in 1992 and 1995 respectively. He is currently a research fellow at University of Birmingham, England. His research interests include evolutionary computation, network security and parallel algorithms. Xin Yao received the Ph.D. degree in computer science from the Univ. Sci. Tech. China in 1990. He is currently a professor of computer science at the University of Birmingham, England. He is a fellow of IEEE. His major research interests include evolutionary computation, neural network ensembles, co-evolution, evolvable hardware, time complexity of evolutionary algorithms, and data mining. He published extensively in these areas.
Influencing Factors Analysis of Co-Branding Fit Degree Based on Niche Trend Theory
Huili YAO,Xin WANG,Juan CHU
International Business and Management , 2012, DOI: 10.3968/j.ibm.1923842820120502.1035
Abstract: On the basis of related research results, the paper defines Co-Branding Fit Degree as the consistent degree in brand image, target market and market position among partner brands. According to Niche Trend Theory, three dimensions of Co-Branding Fit Degree, i.e. brand image, target market and market position, each one can be seen as a comprehensiveness of state and potential. So the paper analyzes the influencing factors of brand image, target market and market position from “state” and “potential” based on Niche Trend Theory, establishes relationship model of Co-Branding Fit Degree’s influencing factors and does a detailed analysis of influencing factors. These studies can provide reference to the enterprises which implement co-branding strategy. They can help enterprises to understand the connotation and influencing factors of Co-Branding Fit Degree. Enterprises may evaluate Co-Branding Fit Degree based on these factors. The research provides prerequisite for successful implementation of Co-Branding strategy. Key words: Co-Branding; Co-Branding Fit Degree; Niche Trend Theory; Influencing factors; Brand partnership
Limited Hydrolysis of Two Soybean Protein Products with Trypsin or Neutrase and the Impacts on their Solubility, Gelation and Fat Absorption Capacity
Yao Hou,Xin-Huai Zhao
Biotechnology , 2011,
Abstract: Soybean Protein Concentrates (SPC) and Soybean Protein Isolates (SPI) were hydrolyzed with trypsin or neutrase to a degree of hydrolysis of 1 and 2%, respectively, to reveal the impacts of limited hydrolysis on their functional properties. Sodium dodecylsulfate-polyacrylamide gel electrophoresis analysis showed that the hydrolysates prepared were hydrolyzed proteins but with different peptide profiles. The evaluation results indicated that the hydrolysates had an increased solubility in pH range of 3-7 over the original SPC or SPI, especially at pH of 4.5. When the hydrolysates were used to prepare heat-induced gels, limited hydrolysis of SPC or SPI led to a decreased or an enhanced hardness of the gels prepared. The SPC hydrolysates had an increased fat absorption capacity about 17-29% while the SPI hydrolysates had a decreased fat absorption capacity about 17-23%. The present study showed that limited hydrolysis of SPC and SPI by neutrase or trypsin could be applied to improve some functional properties of them intended.
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