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Approximate Determination

The Experts below are selected from a list of 156 Experts worldwide ranked by ideXlab platform

Makoto Yasuda – 1st expert on this subject based on the ideXlab platform

  • Approximate Determination of q-Parameter for FCM with Tsallis Entropy Maximization
    Journal of Advanced Computational Intelligence and Intelligent Informatics, 2017
    Co-Authors: Makoto Yasuda

    Abstract:

    This paper considers a fuzzyc-means (FCM) clustering algorithm in combination with deterministic annealing and the Tsallis entropy maximization. The Tsallis entropy is aq-parameter extension of the Shannon entropy. By maximizing the Tsallis entropy within the framework of FCM, statistical mechanical membership functions can be derived. One of the major considerations when using this method is how to determine appropriate values forqand the highest annealing temperature,Thigh, for a given data set. Accordingly, in this paper, a method for determining these values simultaneously without introducing any additional parameters is presented, where the membership function is Approximated using a series expansion method. The results of experiments indicate that the proposed method is effective, and bothqandThighcan be determined automatically and algebraically from a given data set.

  • SCIS&ISIS – Approximate Determination of q-Parameter for FCM with Tsallis Entropy Maximization
    2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Syst, 2016
    Co-Authors: Makoto Yasuda

    Abstract:

    This article is dealing with the fuzzy clustering algorithm combined with deterministic annealing and Tsallis entropy maximization. In this article, a method to determine a q-parameter and an initial annealing temperature Thigh for the algorithm is presented. Tsallis entropy is the q-parameter extension of Shannon entropy. By maximizing Tsallis entropy within the framework of fuzzy c-means, a membership function similar to the statistical mechanical distribution functions is obtained. One of the major issue of this method is that how to determine appropriate q and Thigh for a data distribution is not clear. For the purpose of this article, an approximation method of the membership function is examined. Experiments are performed and the results indicate that the proposed method works properly and both q and Thigh can be determined automatically and algebraically from a data distribution.

  • Approximate Determination of q-Parameter for FCM with Tsallis Entropy Maximization
    2016 Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) and 17th International Symposium on Advanced Intelligent Syst, 2016
    Co-Authors: Makoto Yasuda

    Abstract:

    This article is dealing with the fuzzy clustering algorithm combined with deterministic annealing and Tsallis entropy maximization. In this article, a method to determine a q-parameter and an initial annealing temperature Thigh for the algorithm is presented. Tsallis entropy is the q-parameter extension of Shannon entropy. By maximizing Tsallis entropy within the framework of fuzzy c-means, a membership function similar to the statistical mechanical distribution functions is obtained. One of the major issue of this method is that how to determine appropriate q and Thigh for a data distribution is not clear. For the purpose of this article, an approximation method of the membership function is examined. Experiments are performed and the results indicate that the proposed method works properly and both q and Thigh can be determined automatically and algebraically from a data distribution.

Emmanuel E. Gdoutos – 2nd expert on this subject based on the ideXlab platform

  • Approximate Determination of the Crack Tip Plastic Zone for Mixed-Mode Loading
    Problems of Fracture Mechanics and Fatigue, 2020
    Co-Authors: Emmanuel E. Gdoutos

    Abstract:

    Determine the radius of the plastic zone accompanying the crack tip for mixed-mode (opening-mode and sliding-mode) loading under plane strain conditions according to the Mises Yield criterion. Plot the resulting elastic-plastic boundary for a crack of length 2a in an infinite plate subtending an angle β = 30° with the direction of applied uniaxial stress at infinity. v = 0.3.

  • Approximate Determination of the Crack Tip Plastic Zone for Mode-I and Mode-II Loading
    Problems of Fracture Mechanics and Fatigue, 2020
    Co-Authors: Emmanuel E. Gdoutos

    Abstract:

    Determine the crack tip plastic zone for mode-I and mode-II loading according to the Mises yield criterion.

R M Holt – 3rd expert on this subject based on the ideXlab platform

  • Approximate Determination of surface conductivity in porous media
    Journal of Physics D, 1995
    Co-Authors: B Nettelblad, B Ahlen, Gunnar A Niklasson, R M Holt

    Abstract:

    We have studied the fluid permeability and the electrical conduction in artificially made impregnated sandstones in order to determine the surface conductivity Approximately. The electrical conductivity of the impregnated porous medium is not proportional to the conductivity of the impregnation liquid, but a linear dependence is found which permits us to calculate an electrical formation factor, F, and an intercept with the ordinate axis. We propose that ‘Archie’s law’ for the formation factor’s porosity-dependence is composed of two factors: a factor inversely proportional to the porosity and a tortuosity factor. The tortuosity factor is dependent on the grain size distribution of the sandstone. The formation factor has been shown to relate to the permeability, k, in two ways: either as k alpha F-1 or as k alpha F-2, where the proportionality factors are different geometrical properties of the porous medium. We also show that it is possible to calculate the surface conductivity from a theoretical relation between the conductivity intercept and the permeability.