The Experts below are selected from a list of 1554 Experts worldwide ranked by ideXlab platform

Saeed Jafarzadeh - One of the best experts on this subject based on the ideXlab platform.

  • An analytical approach for solving type-1 and type-2 fully fuzzy linear systems of equations
    2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
    Co-Authors: Sheriff Sadiqbatcha, Saeed Jafarzadeh
    Abstract:

    A general analytical method for solving fully fuzzy linear system (FFLSE) of equations using interval analysis and LU decomposition is proposed in this study. Both type-1 and interval type-2 fuzzy coefficients are discussed. Alpha level sets (alpha cuts) are used to reduce a FFLSE into a number of interval systems, which are then solved systematically using LU decomposition and forward-Backward Substitution. To carry out forward-Backward Substitution on interval equations, conditions for the existence and uniqueness of interval solutions are derived and approximations are used for cases when an interval solution does not exist. The proposed method is then extended to solve interval type-2 fuzzy system of equations.

  • FUZZ-IEEE - An analytical approach for solving type-1 and type-2 fully fuzzy linear systems of equations
    2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
    Co-Authors: Sadiqbatcha, Saeed Jafarzadeh
    Abstract:

    A general analytical method for solving fully fuzzy linear system (FFLSE) of equations using interval analysis and LU decomposition is proposed in this study. Both type-1 and interval type-2 fuzzy coefficients are discussed. Alpha level sets (alpha cuts) are used to reduce a FFLSE into a number of interval systems, which are then solved systematically using LU decomposition and forward-Backward Substitution. To carry out forward-Backward Substitution on interval equations, conditions for the existence and uniqueness of interval solutions are derived and approximations are used for cases when an interval solution does not exist. The proposed method is then extended to solve interval type-2 fuzzy system of equations.

Sheriff Sadiqbatcha - One of the best experts on this subject based on the ideXlab platform.

  • An analytical approach for solving type-1 and type-2 fully fuzzy linear systems of equations
    2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
    Co-Authors: Sheriff Sadiqbatcha, Saeed Jafarzadeh
    Abstract:

    A general analytical method for solving fully fuzzy linear system (FFLSE) of equations using interval analysis and LU decomposition is proposed in this study. Both type-1 and interval type-2 fuzzy coefficients are discussed. Alpha level sets (alpha cuts) are used to reduce a FFLSE into a number of interval systems, which are then solved systematically using LU decomposition and forward-Backward Substitution. To carry out forward-Backward Substitution on interval equations, conditions for the existence and uniqueness of interval solutions are derived and approximations are used for cases when an interval solution does not exist. The proposed method is then extended to solve interval type-2 fuzzy system of equations.

Jiayi Du - One of the best experts on this subject based on the ideXlab platform.

  • A Hybrid Parallel Tridiagonal Solver on Multi-core Architectures
    2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014
    Co-Authors: Guangping Tang, Kenli Li, Keqin Li, Hang Chen, Jiayi Du
    Abstract:

    An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated Backward Substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. This hybrid algorithm has simple Backward Substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi-threading implementation achieves better efficiency than the other parallel methods, i.e., the cyclic reduction and the partition methods. Among them, the cyclic reduction method is previously found to be the fastest algorithm in many ways for solutions. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on multi-core computer when the size of an equation is large enough. The hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 30% and 20% respectively.

  • IPDPS Workshops - A Hybrid Parallel Tridiagonal Solver on Multi-core Architectures
    2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014
    Co-Authors: Guangping Tang, Kenli Li, Keqin Li, Hang Chen, Jiayi Du
    Abstract:

    An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated Backward Substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. This hybrid algorithm has simple Backward Substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi-threading implementation achieves better efficiency than the other parallel methods, i.e., the cyclic reduction and the partition methods. Among them, the cyclic reduction method is previously found to be the fastest algorithm in many ways for solutions. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on multi-core computer when the size of an equation is large enough. The hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 30% and 20% respectively.

Guangping Tang - One of the best experts on this subject based on the ideXlab platform.

  • An iteration-based hybrid parallel algorithm for tridiagonal systems of equations on multi-core architectures
    Concurrency and Computation: Practice and Experience, 2015
    Co-Authors: Guangping Tang, Kenli Li, Wangdong Yang, Yu Ye, Guoqing Xiao, Keqin Li
    Abstract:

    An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated Backward Substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. This hybrid algorithm has simple Backward Substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi-threading implementation achieves better efficiency than the other parallel methods, that is, the cyclic reduction and the partition methods. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on a multi-core computer when the size of equations meets some dimension threshold. The hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 19.2% and 13.2%, respectively. In addition, by comparing the single-iteration and multi-iteration hybrid parallel algorithms, it is found that increasing iteration steps of the cyclic reduction method does not affect the performance of the hybrid parallel algorithm very much. Copyright © 2015 John Wiley & Sons, Ltd.

  • A Hybrid Parallel Tridiagonal Solver on Multi-core Architectures
    2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014
    Co-Authors: Guangping Tang, Kenli Li, Keqin Li, Hang Chen, Jiayi Du
    Abstract:

    An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated Backward Substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. This hybrid algorithm has simple Backward Substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi-threading implementation achieves better efficiency than the other parallel methods, i.e., the cyclic reduction and the partition methods. Among them, the cyclic reduction method is previously found to be the fastest algorithm in many ways for solutions. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on multi-core computer when the size of an equation is large enough. The hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 30% and 20% respectively.

  • IPDPS Workshops - A Hybrid Parallel Tridiagonal Solver on Multi-core Architectures
    2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014
    Co-Authors: Guangping Tang, Kenli Li, Keqin Li, Hang Chen, Jiayi Du
    Abstract:

    An optimized parallel algorithm is proposed to solve the problem occurred in the process of complicated Backward Substitution of cyclic reduction during solving tridiagonal linear systems. Adopting a hybrid parallel model, this algorithm combines the cyclic reduction method and the partition method. This hybrid algorithm has simple Backward Substitution on parallel computers comparing with the cyclic reduction method. In this paper, the operation count and execution time are obtained to evaluate and make comparison for these methods. On the basis of results of these measured parameters, the hybrid algorithm using the hybrid approach with a multi-threading implementation achieves better efficiency than the other parallel methods, i.e., the cyclic reduction and the partition methods. Among them, the cyclic reduction method is previously found to be the fastest algorithm in many ways for solutions. In particular, the approach involved in this paper has the least scalar operation count and the shortest execution time on multi-core computer when the size of an equation is large enough. The hybrid parallel algorithm improves the performance of the cyclic reduction and partition methods by 30% and 20% respectively.

W.f. Tinney - One of the best experts on this subject based on the ideXlab platform.

  • Approximate sparse vector techniques for power network solutions
    IEEE Transactions on Power Systems, 1991
    Co-Authors: R. Bacher, G.c. Ejebe, W.f. Tinney
    Abstract:

    Approximate sparse vector techniques can be used to enhance solution speeds of sparsity-oriented power network algorithms. They are especially applicable to large problems in which rapid solutions are particularly important and where it may be advantageous to trade a certain amount of accuracy to gain speed. Speed is gained with approximate sparse vector techniques by skipping operations with relatively small effects in the forward/Backward Substitution when solving a sparse linear system of equations and when updating factors to reflect matrix changes. Four such techniques are described and discussed. Numerical examples showing the effectiveness of approximate sparse vector techniques for selected applications are also presented.