The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel ex-tension principle is also introduced for the increasing function σ:R→R. Thus it is convenient to con-struct a fuzzy neural networ...The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel ex-tension principle is also introduced for the increasing function σ:R→R. Thus it is convenient to con-struct a fuzzy neural network model with succinct learning algorithms. Such a system possesses some universal approximation capabilities, that is, the corresponding three layer feedforward fuzzy neural networks can be universal approximators to the continuously increasing fuzzy functions.展开更多
The key component of finite element analysis of structures with fuzzy parameters, which is associated with handling of some fuzzy information and arithmetic relation of fuzzy variables, was the solving of the governin...The key component of finite element analysis of structures with fuzzy parameters, which is associated with handling of some fuzzy information and arithmetic relation of fuzzy variables, was the solving of the governing equations of fuzzy finite element method. Based on a given interval representation of fuzzy numbers, some arithmetic rules of fuzzy numbers and fuzzy variables were developed in terms of the properties of interval arithmetic. According to the rules and by the theory of interval finite element method, procedures for solving the static governing equations of fuzzy finite element method of structures were presented. By the proposed procedure, the possibility distributions of responses of fuzzy structures can be generated in terms of the membership functions of the input fuzzy numbers. It is shown by a numerical example that the computational burden of the presented procedures is low and easy to implement. The effectiveness and usefulness of the presented procedures are also illustrated.展开更多
Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the fuzzy primal simpl...Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the fuzzy primal simplex method proposed by Ganesan and Veeramani [1] and the fuzzy dual simplex method proposed by Ebrahimnejad and Nasseri [2]. The former method is not applicable when a primal basic feasible solution is not easily at hand and the later method needs to an initial dual basic feasible solution. In this paper, we develop a novel approach namely the primal-dual simplex algorithm to overcome mentioned shortcomings. A numerical example is given to illustrate the proposed approach.展开更多
The numerical solutions for uncertain viscoelastic problems have important theo- retical and practical significance. The paper develops a new approach by combining the scaled boundary finite element method （SBFEM） a...The numerical solutions for uncertain viscoelastic problems have important theo- retical and practical significance. The paper develops a new approach by combining the scaled boundary finite element method （SBFEM） and fuzzy arithmetic. For the viscoelastic problems with zero uncertainty, the SBFEM and the temporally piecewise adaptive algorithm is employed in the space domain and the time domain, respectively, in order to provide an accurate semi- analytical boundary-based approach and to ensure the accuracy of discretization in the time domain with different sizes of time step at the same time. The fuzzy arithmetic is used to address the uncertainty analysis of viscoelastic material parameters, and the transformation method is used for computation with the advantages of effectively avoiding overestimation and reducing the computational costs. Numerical examples are provided to test the performance of the proposed method. By comparing with the analytical solutions and the Monte Carlo method, satisfactory results are achieved.展开更多
基金The author would like to thank Professor H. Wang for helpful suggestions This work was supported by the National Natural Science Foundation of China( Grants Nos. 69974006 and 69974041) .
文摘The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel ex-tension principle is also introduced for the increasing function σ:R→R. Thus it is convenient to con-struct a fuzzy neural network model with succinct learning algorithms. Such a system possesses some universal approximation capabilities, that is, the corresponding three layer feedforward fuzzy neural networks can be universal approximators to the continuously increasing fuzzy functions.
基金Foundation items:the National Natural Science Foundation of China(59575040,59575032)the Areonautics Science Foundation of China(00B53010)
文摘The key component of finite element analysis of structures with fuzzy parameters, which is associated with handling of some fuzzy information and arithmetic relation of fuzzy variables, was the solving of the governing equations of fuzzy finite element method. Based on a given interval representation of fuzzy numbers, some arithmetic rules of fuzzy numbers and fuzzy variables were developed in terms of the properties of interval arithmetic. According to the rules and by the theory of interval finite element method, procedures for solving the static governing equations of fuzzy finite element method of structures were presented. By the proposed procedure, the possibility distributions of responses of fuzzy structures can be generated in terms of the membership functions of the input fuzzy numbers. It is shown by a numerical example that the computational burden of the presented procedures is low and easy to implement. The effectiveness and usefulness of the presented procedures are also illustrated.
文摘Two existing methods for solving a class of fuzzy linear programming (FLP) problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the fuzzy primal simplex method proposed by Ganesan and Veeramani [1] and the fuzzy dual simplex method proposed by Ebrahimnejad and Nasseri [2]. The former method is not applicable when a primal basic feasible solution is not easily at hand and the later method needs to an initial dual basic feasible solution. In this paper, we develop a novel approach namely the primal-dual simplex algorithm to overcome mentioned shortcomings. A numerical example is given to illustrate the proposed approach.
文摘The numerical solutions for uncertain viscoelastic problems have important theo- retical and practical significance. The paper develops a new approach by combining the scaled boundary finite element method （SBFEM） and fuzzy arithmetic. For the viscoelastic problems with zero uncertainty, the SBFEM and the temporally piecewise adaptive algorithm is employed in the space domain and the time domain, respectively, in order to provide an accurate semi- analytical boundary-based approach and to ensure the accuracy of discretization in the time domain with different sizes of time step at the same time. The fuzzy arithmetic is used to address the uncertainty analysis of viscoelastic material parameters, and the transformation method is used for computation with the advantages of effectively avoiding overestimation and reducing the computational costs. Numerical examples are provided to test the performance of the proposed method. By comparing with the analytical solutions and the Monte Carlo method, satisfactory results are achieved.
