Cancer classification and identification are major areas in medical research. DNA microarrays could provide useful information for cancer classification at the gene expression level. The number of genes in a microarra...
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Cancer classification and identification are major areas in medical research. DNA microarrays could provide useful information for cancer classification at the gene expression level. The number of genes in a microarray is always several thousands while the number of training samples always several dozens. In such case most of the machine learning models suffer from the overfitting and it is necessary to select a handful of most informative genes. An adaptive and iterative gene selection algorithm based on least squares support vector machines is proposed in this paper. The algorithm adopts sequential forward selection search scheme. The number of selected genes can be determined adaptively. The total number of genes processed by the proposed algorithm is smaller than that processed by other algorithms using support vector machines. Results of numerical experiments show that the proposed algorithm trains fast and achieves comparable performance on two well-known benchmark problems.
The constraint problem can be transformed to an optimization problem. Particle swarm optimization (PSO) is a new evolutionary computation technique. Even PSO has many attractive properties, but it lacks global search ...
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The constraint problem can be transformed to an optimization problem. Particle swarm optimization (PSO) is a new evolutionary computation technique. Even PSO has many attractive properties, but it lacks global search ability at the end of the run. This paper introduce a hybrid approach called the TPSO that simultaneously applies particle swarm optimization (PSO), and tabu search (TS) to create a generally well-performing search heuristics, and combat the problem of premature convergence. The new algorithm considers candidate solutions and their fitness as individuals, which are based on their recent search progress. The tabu search makes each particle to reset its record of its best position, to avoid making direction and velocity decisions on the basis of outdated information. The feasibility of the proposed method is demonstrated on Solving Geometric Constraint Problems.
The escape time algorithm cannot render the convergence region of mapping, so there are some black regions in escape time fractal. In this paper, a novel method is presented to construct fractal image, which is named ...
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The escape time algorithm cannot render the convergence region of mapping, so there are some black regions in escape time fractal. In this paper, a novel method is presented to construct fractal image, which is named the distance ratio iteration method. This method performs iteration on two points and render fractal image by using their distance ratio convergence times. Taking complex mapping z←zα+c as example, the generalized Mandelbrot and Julia sets are constructed based on distance ratio and their visual properties are analyzed. The result fractal image has complex and self-similarity structure in inner convergence region. It is proved that the boundary of distance ratio fractal is the same as M-J set when α>0, and some visual structure of it with various exponent α are discussed. When α<0, the generalized Mandelbrot and Julia set based on distance ratio have some complex structures which M-J set does not have.
Modal logics are good candidates for a formal theory of agents. The efficiency of reasoning method in modal logics is very important, because it determines whether or not the reasoning method can be widely used in sys...
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Modal logics are good candidates for a formal theory of agents. The efficiency of reasoning method in modal logics is very important, because it determines whether or not the reasoning method can be widely used in systems based on agent. In this paper, we modify the extension rule theorem proving method we presented before, and then apply it to P-logic that is translated from modal logic by functional transformation. At last, we give the proof of its soundness and completeness.
Ontology evolution in the Model Driven Semantic Web can be looked as a process of model transformations. A model-transformation based conceptual framework for ontology evolution is presented in the paper. Applications...
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ISBN:
(纸本)3885793989
Ontology evolution in the Model Driven Semantic Web can be looked as a process of model transformations. A model-transformation based conceptual framework for ontology evolution is presented in the paper. Applications of model transformations in every phase of ontology evolution process are described. The framework combines technologies of ontology evolution, Ontology Definition Metamodel and model transformations, and it can be looked as a method for ontology evolution in the Model Driven Semantic Web.
The traditional RBAC model already cannot express the complicated secure access control constraint of the workflow. Based on the traditional RBAC model, a new conditioned RBAC model named as CMWRBSAC is proposed on th...
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The configuration problem in manufacture is more complicated than most other fields. Therefore, the design of modeling and reasoning module for product configuration manager in manufacture is very important and comple...
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The workflow model is the abstract expression of the workflow or the business process. Following the WfMC reference model, a PKI-based lightweight workflow model named as PBLW is put forward in this paper. The framewo...
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It is well recognized that sequential pattern mining plays an essential role in many scientific and business domains. In this paper, a new extension of sequential pattern, attributes' sequential pattern, is propos...
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This paper presents two parallel semantics of constraint logic programs: multiset answer constraint semantics and game semantics, which differ entirely from the traditional semantics. When giving the first semantics, ...
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