Applied Mechanics and Materials Vols. 687-691

Abstract: By means of Riemann-Stieltjes stochastic process, moment-generating functions and operator-Valued mathematical expectation,the problem of probabilistic approximation for bi-continuous semigroups was studied and the saturation theorem of probabilistic representations of semigroups are obtained .

Abstract: In terms of cogenerator and rsolvent of cosine functions,the contractivity and boundedness of cosine functions were characterized.

Abstract: System simulation software MATLAB is developed by the United States Mays Walker Corporation (Mathwork) for the study of engineering analysis and design process. On the basis of discussion on MATLAB simulation software, this paper introduces the evolutionary game model, and take the evolutionary game model between logistics enterprises and SMEs as an example , Showing the application of MATLAB simulation technology on evolutionary game.

Abstract: Considering the inheritance and hereditary of product structure life cycle assessment, full life cycle assessment properties of structure is introduced into expression of design scheme. Scheme evolution design is presented based on gene model of full life cycle assessment properties of structure. The gene model of life cycle assessment properties of structure is established. The variable length coding is converted to equal length coding to realize the quantitative representation of structure information. The fitness function is established for life cycle assessment of structure by Analytic Hierarchy Process. The genetic operators are designed. Scheme evolution design is realized based on gene model of life cycle assessment of structure, reflecting life cycle assessment properties of design schemes, improving the efficiency of product design generation. The evolution design example of multi-rope diamond wire saw verifies the feasibility of the imposed method.

Abstract: Incremental Neural Network (IncNet) structure is controlled by the growth and pruning, and the complexity of the match and training data. Dual radial transfer function is more flexible than other commonly transfer function used in artificial neural network. Recent improvements in the multi-dimensional space (having the N-1 parameters) to increase the rotation of the transfer function of the constant value. Based on the results of the benchmark approach and psychological classification analysis clearly shows than any other classification network model has a stronger generalization.

Abstract: Research and analysis of RBF neural network structure and characteristics. Find out its shortcomings and propose an improved method for the deficiencies, then created a neural network model for using entropy-based clustering and competitive learning algorithm. Using MATLAB simulation tools for model simulation, confirmed the entropy clustering and competitive learning algorithm of FBF prediction neural network have high precision and generalization ability of stronger character.

Abstract: With the Development of web service technology, a single web service cannot fulfill different users’ diverse requirements. Adding semantic information to the input-output message of web services provides us a method to implement web service composition automatically. After researching on existing algorithms for web service composition, this article proposed a QoS-oriented web service composition algorithm based on graph search with semantic information.

Abstract: Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) are important methods in model prediction. In this paper, a case concerning in how to estimate the serial criminal’s next possible crime location is researched. Two models are devised to determine the “geographical profile” of a suspected serial criminal. Model 1 is proposed that we use the AHP and consider many factors which may influence a criminal to choose his next crime location. Model 2 is an improvement of Model 1. It is a combination of the FAHP and the Fuzzy Comprehensive Evaluation Theory (FCET). And it overcomes the difficulty of dealing with uncertain factors, which model 1 cannot work. In the end, performances of the above models are analyzed.

Abstract: In the process of cloud computing, the dynamic hierarchical resource index is researched, and the independent confusion cloud computing is studied. This problem has become the focus of data processing. Therefore, it needs to establish improved dynamic layered resource index independent confuse cloud computing model. According to the theory of support vector machine, all of the resources are taken with dynamical layered processing, different levels of resources are taken with the independent confusion cloud computing. The experiment results show that, this algorithm is taken for the dynamic layered resource cloud computing, calculation efficiency can be improved, computational complexity and redundancy are reduced, meet the practical demands of dynamic hierarchical resource index independent confused cloud computing. It has good application value in the cloud computing application.

Abstract: We collected fatigue stress concentration factor and used Support Vector Machines (SVM) by linear kernel to reduce dimension processing. In order to research the way of dimensionality reduction for data, we also processed the sample of stress fatigue concentration factor to compare with Principal Component Analysis(PCA). The results showed that the sample is processed by linear kernel could improve efficiency to train by SVM again.