• Title/Summary/Keyword: fuzzy arithmetic

Search Result 64, Processing Time 0.025 seconds

On the Implementation of Fuzzy Arithmetic for Prediction Model Equation of Corrosion Initiation

  • Do Jeong-Yun;Song Hun;Soh Yang-Seob
    • Journal of the Korea Concrete Institute
    • /
    • v.17 no.6 s.90
    • /
    • pp.1045-1051
    • /
    • 2005
  • For critical structures and application, where a given reliability must be met, it is necessary to account for uncertainties and variability in material properties, structural parameters affecting the corrosion process, in addition to the statistical and decision uncertainties. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters and the fuzziness of the corrosion time is determined by the fuzzy arithmetic of interval arithmetic and extension principle

Fuzzy arithmetic (퍼지연산)

  • Chung, Se-Hwa
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2000.05a
    • /
    • pp.5-8
    • /
    • 2000
  • Using the concept of a piecewise linear function, we present new operations for fuzzy arithmetic and then compare the operation based by the extension principle with the new operation.

  • PDF

Cpk Index Estimation under Tw (the weakest t-norm)-based Fuzzy Arithmetic Operations

  • Hong, Dug-Hun
    • International Journal of Fuzzy Logic and Intelligent Systems
    • /
    • v.8 no.3
    • /
    • pp.170-174
    • /
    • 2008
  • The measurement of performance of a process considering both the location and the dispersion of information about the process is referred to as the process capacity indices (PCIs) of interest, $C_{pk}$. This information is presented by the mean and standard deviation of the producing process. Linguistic variables are used to express the evaluation of the quality of a product. Consequently, $C_{pk}$ is defined with fuzzy numbers. Lee [Eur. J. Oper. Res. 129(2001) 683-688] constructed the definition of the $C_{pk}$ index estimation presented by fuzzy numbers and approximated its membership function using the "min" - norm based Zadeh's extension principle of fuzzy sets. However, Lee's result was shown to be invalid by Hong [Eur. J. Oper. Res. 158(2004) 529-532]. It is well known that $T_w$ (the weakest t-norm)-based addition and multiplication preserve the shape of L-R fuzzy numbers. In this paper, we allow that the fuzzy numbers are of L-R type. The object of the present study is to propose a new method to calculate the $C_{pk}$ index under $T_w-based$ fuzzy arithmetic operations.

A DATA COMPRESSION METHOD USING ADAPTIVE BINARY ARITHMETIC CODING AND FUZZY LOGIC

  • Jou, Jer-Min;Chen, Pei-Yin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 1998.06a
    • /
    • pp.756-761
    • /
    • 1998
  • This paper describes an in-line lossless data compression method using adaptive binary arithmetic coding. To achieve better compression efficiency , we employ an adaptive fuzzy -tuning modeler, which uses fuzzy inference to deal with the problem of conditional probability estimation. The design is simple, fast and suitable for VLSI implementation because we adopt the table -look-up approach. As compared with the out-comes of other lossless coding schemes, our results are good and satisfactory for various types of source data.

  • PDF

Fuzzy methodology application for modeling uncertainties in chloride ingress models of RC building structure

  • Do, Jeongyun;Song, Hun;So, Seungyoung;Soh, Yangseob
    • Computers and Concrete
    • /
    • v.2 no.4
    • /
    • pp.325-343
    • /
    • 2005
  • Chloride ingress is a common cause of deterioration of reinforced concrete located in coastal zone. Modeling the chloride ingress is an important basis for designing reinforced concrete structures and for assessing the reliability of an existing structure. The modeling is also needed for predicting the deterioration of a reinforced structure. The existing deterministic solution for prediction model of corrosion initiation cannot reflect uncertainties which input variables have. This paper presents an approach to the fuzzy arithmetic based modeling of the chloride-induced corrosion of reinforcement in concrete structures that takes into account the uncertainties in the physical models of chloride penetration into concrete and corrosion of steel reinforcement, as well as the uncertainties in the governing parameters, including concrete diffusivity, concrete cover depth, surface chloride concentration and critical chloride level for corrosion initiation. There are a lot of prediction model for predicting the time of reinforcement corrosion of structures exposed to chloride-induced corrosion environment. In this work, RILEM model formula and Crank's solution of Fick's second law of diffusion is used. The parameters of the models are regarded as fuzzy numbers with proper membership function adapted to statistical data of the governing parameters instead of random variables of probabilistic modeling of Monte Carlo Simulation and the fuzziness of the time to corrosion initiation is determined by the fuzzy arithmetic of interval arithmetic and extension principle. An analysis is implemented by comparing deterministic calculation with fuzzy arithmetic for above two prediction models.

ON SOLVING FUZZY EQUATION

  • Hong, Dug-Hun
    • Journal of applied mathematics & informatics
    • /
    • v.8 no.1
    • /
    • pp.213-223
    • /
    • 2001
  • The use of fuzzy number over interval of confidence instead of possibilitic consideration for solving fuzzy equation is proposed. This approach of solving fuzzy equation by interval arithmetic and ${\alpha}$-cuts has a considerable advantage. Through theoretical analysis, an illustrative example and computational results, we show that the proposed approach is more general and straight-forword.

Hybrid Fuzzy Least Squares Support Vector Machine Regression for Crisp Input and Fuzzy Output

  • Shim, Joo-Yong;Seok, Kyung-Ha;Hwang, Chang-Ha
    • Communications for Statistical Applications and Methods
    • /
    • v.17 no.2
    • /
    • pp.141-151
    • /
    • 2010
  • Hybrid fuzzy regression analysis is used for integrating randomness and fuzziness into a regression model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and nonlinear regression models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy nonlinear regression analysis by constructing a fuzzy linear regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to modeling nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying model function for fuzzy nonlinear regression model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.

A Learning Algorithm of Fuzzy Neural Networks Using a Shape Preserving Operation

  • Lee, Jun-Jae;Hong, Dug-Hun;Hwang, Seok-Yoon
    • Journal of Electrical Engineering and information Science
    • /
    • v.3 no.2
    • /
    • pp.131-138
    • /
    • 1998
  • We derive a back-propagation learning algorithm of fuzzy neural networks using fuzzy operations, which preserves the shapes of fuzzy numbers, in order to utilize fuzzy if-then rules as well as numerical data in the learning of neural networks for classification problems and for fuzzy control problems. By introducing the shape preseving fuzzy operation into a neural network, the proposed network simplifies fuzzy arithmetic operations of fuzzy numbers with exact result in learning the network. And we illustrate our approach by computer simulations on numerical examples.

  • PDF

UTLIZATION OF FUZZY AND VOLETTRA ALGORITHM FOR 3D BATHYMETRY SIMULATION FROM TOPSAR POLARISED DATA

  • Marghany, Maged;Hussien, Mohd. Lokman
    • Proceedings of the KSRS Conference
    • /
    • 2003.11a
    • /
    • pp.432-434
    • /
    • 2003
  • The main objective of this research is to utilize the parallel Fuzzy arithmetic for constructing ocean bathymetry from polarized remote sensing data such as TOPSAR image. In doing so, the parallel library for Fuzzy arithmetic has been developed. Three- dimensional surface modeling consisted of Volettra model, non-linear model which construct a global topological structure between the data points, used to support an approximation of real surface. The output of the parallel library was a digital terrain model for bathymetry along the coastal waters of Kuala Terengganu Malaysia. This paper describes the principles behind the Fuzzy algorithm, indicates for what type of application it might be useful, notes on the accuracy and gives an example of an application.

  • PDF