Fuzzy Modelling Research Papers - Academia.edu (original) (raw)

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- by Shang-Ming Zhou
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- Pure Mathematics, Fuzzy Inference, Complex System, Adaptive learning

Networked control systems (NCS) are feedback systems closed through data networks. NCS have many advantages compared with traditional systems; however, the network-induced delay and other characteristics of data networks may degrade the... more

- by Joseph Yame
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- Control Theory, Fault Detection, Fault Tolerant Control, Fault diagnosis

This study considers the robust identification of the parameters describing a Sugeno type fuzzy inference system with uncertain data. The objective is to minimize the worst-case residual error using a numerically efficient algorithm. The Sugeno type fuzzy systems are linear in consequent parameters but nonlinear in antecedent parameters. The robust consequent parameters identification problem can be formulated as second-order cone programming problem. The optimal solution of this second-order cone problem can be interpreted as solution of a Tikhonov regularization problem with a special choice of regularization parameter which is optimal for robustness (Ghaoui and Lebret (1997). SAIM Journal of Matrix Analysis and Applications 18, 1035–1064). The final regularized nonlinear optimization problem allowing simultaneous identification of antecedent and consequent parameters is solved iteratively using a generalized Gauss–Newton like method. To illustrate the approach, several simulation studies on numerical examples including the modelling of a spectral data function (one-dimensional benchmark example) is provided. The proposed robust fuzzy identification scheme has been applied to approximate the physical fitness of patients with a fuzzy expert system. The identified fuzzy expert system is shown to be capable of capturing the decisions (experiences) of a medical expert.

- by mohit kumar
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- Applied Mathematics, Fuzzy Expert System, Matrix Analysis, Tikhonov Regularization
- by Mehdi Ghatee
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- Applied Mathematics, Engineering Design, Fuzzy System, Linear System

- by Saim. Ch
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- Applied Mathematics, Fuzzy Expert System, Matrix Analysis, Tikhonov Regularization
- by Morteza Seidi
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- Fuzzy Control, Fuzzy Controller, Robot Manipulator, Fuzzy Modelling
- by Domonkos Tikk
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- Mechanical Engineering, Computational Complexity, Fuzzy Inference, Linear Model

This study presents a method of adaptive identification of parameters describing Sugeno fuzzy inference system in presence of bounded disturbances while maintaining the readability and interpretability of the fuzzy model during and after identification. This method do not require any a priori knowledge of a bound on the disturbance and noise and of a bound on the unknown parameters values. The method can be used for the robust and adaptive identification of slowly time varying nonlinear systems using fuzzy inference systems. The suggested method was used to build a fuzzy expert system that approximates the functional relationship between physical fitness and some of the measurable physiological parameters by their real measurements and opinion (human-experiences) of a medical expert.

- by Mohit Kumar
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- Applied Mathematics, Computer Science, A Priori Knowledge, Fuzzy Expert System
- by Joseph-julien Yame
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- Control Theory, Fault Detection, Fault Tolerance, Optimization

Uniaxial Compressive Strength (UCS), considered to be one of the most useful rock properties for mining and civil engineering applications, has been estimated from some index test results by fuzzy and multiple regression modelling. Laboratory investigations including Uniaxial Compressive Strength (UCS), Point Load Index test (PL), Schmidt Hammer Hardness test (SHR) and Sonic velocity (Vp) test have been carried out on nine different rock types yielding to 305 tested specimens in total. Average values along with the standard deviations (Stdev) as well as Coefficients of variation (CoV) have been calculated for each rock type. Having constructed the Mamdani Fuzzy algorithm, UCS of intact rock samples was then predicted using a data driven fuzzy model. The predicted values derived from fuzzy model were compared with multi-linear statistical model. Comparison proved that the best model predictions have been achieved by fuzzy modelling in contrast to multi-linear statistical modelling. As a result, the developed fuzzy model based on point load, Schmidt hammer and sonic velocity can be used as a tool to predict UCS of intact rocks.

- by Murat Karakus
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- Civil Engineering, Statistical Modelling, Standard Deviation, Compressive Strength
- by Robert John
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- Cognitive Science, Applied Mathematics, Soft Computing, Inventory Management

Supply chain networking decisions are very important for the medium- and long-term planning success of manufacturing companies. The inputs to supply chain planning models are subject to environmental and system uncertainties. In this paper, a fuzzy set theory-based model is proposed to deal with those uncertainties. For this purpose, a possibilistic linear programming (PLP) model is used to make strategic

- by Özgür Kabak
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- Supply Chain Management, Fuzzy set theory, Supply Chain, Multidisciplinary
- by Konstantinos Zikidis
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- Reinforcement Learning, Back Propagation, Pure Mathematics, Neural Network
- by Mario Gongora
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- Cognitive Science, Applied Mathematics, Soft Computing, Inventory Management
- by Piermaria Corona
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- Decision Making, Sustainable Development, Land Use Planning, Case Study

- by Özgür Kabak
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- Supply Chain Management, Fuzzy set theory, Supply Chain, Multidisciplinary

We use for the first time fuzzy mathematics to aid in the determination of which tests of preschool, hard of hearing and deaf children are the best predictors of success when these students are mainstreamed in the public school system. The techniques are those of group decision making and consensus under fuzzy preferences and fuzzy majority and techniques of fuzzy outranking relations in preference modelling.

- by Jenna Voss
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- Psychology, Cognitive Science, Statistics, Group Decision Making

This research applies the fuzzy set theory via Geographical Information Systems (GIS) – based analysis, in order to model slope erosion by runoff. For this purpose, the following steps were accomplished: definition of input variables (rocks’ susceptibility to erosion, slope inclination, slope morphology), development of a fuzzy inference system based on theoretical and empirical knowledge, transformation of input to output variables (erosion – deposition) and visualization of the output variables (spatial distribution of erosion–deposition processes). The method was applied on the drainage basin of Corinth, located in the north–eastern part of Peloponnese (Greece), where a series of catastrophic erosional events have recently occurred.

- by Niki Evelpidou and +2
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- Greece, Fuzzy Modelling, GIS based Analysis, slope erosion

This study aims at improving the characterisation and quantification of vegetative drought as a vague spatial phenomenon. 10-day NOAA-AVHRR NDVI images of East Africa from September 2005 to April 2006 are used. Vegetative drought is characterised using a membership function to model the gradual transition between drought and non-drought classes. Measures are implemented to quantify the areas and vagueness of

- by Wietske Bijker and +1
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- Earth Sciences, Environmental Science, Remote Sensing, Fuzzy set theory
- by Arūnas Lipnickas
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- Genetics, Genetic Algorithm, Air flow, Fault diagnosis
- by Graciela Metternicht
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- Remote Sensing, Fuzzy Logic, Change detection, Geomatic Engineering
- by Antonio Sala
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- Engineering, Tensor product semigroups, Fuzzy Control, Membership Function

This paper presents a fuzzy system approach to the prediction of nonlinear time series and dynamical systems based on a fuzzy model that includes its derivative information. The underlying mechanism governing the time series, expressed as a set of IF-THEN rules, is discovered by a modified structure of fuzzy system in order to capture the temporal series and its temporal

- by Fernando Gouveia
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- Computer Science, Time Series, Nonlinear Time Series, Time Series Prediction

- by Paulo Salgado
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- Time Series, Nonlinear Time Series, Time Series Prediction, Fuzzy System

Abstract:-In this paper an adaptive neural-fuzzy walking control of an autonomous biped robot is proposed. This control system uses a feed forward neural network based on nonlinear regression. The general regression neural network is used... more

- by Manuel Crisóstomo
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- Neural Network, Control system, Nonlinear Regression, Inverted Pendulum

Linguistic equations are useful for taking into account non-linearity especially in multivariable application systems. The main benefit is better and more accurate decision-making due to the model-based approach and systematic knowledge management. Insight to the process dynamic operation is the most important issue. Automatic generation of systems, model-based techniques and adaptation techniques are very valuable in developing and tuning the

- by Esko Juuso
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- Knowledge Management, Decision Making, Fuzzy Control, Dynamic Simulation
- by Richard Jensen
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- Set Theory, Informatics, Data Analysis, Fuzzy set theory
- by Domonkos Tikk
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- Information Technology, Telecommunications, Fuzzy Logic, Fuzzy Sets

This study considers the problem of Robust Fuzzy approximation of a time-varying nonlinear process in the presence of uncertainties in the identification data using a Sugeno Fuzzy System while maintaining the interpretability of the fuzzy model during identification. A recursive procedure for the estimation of fuzzy parameters is proposed based on solving local optimization problem that attempt to minimize the worst-case effect of data uncertainties on approximation performance. To illustrate the approach, several simulation studies on numerical examples are provided. The developed scheme was applied to handle the vagueness, ambiguity and uncertainty inherently present in the general notion of a Medical Expert about Physical Fitness based on a set of various Physiological parameters measurements.

- by Tarik Ozkul
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- Applied Mathematics, Fuzzy Logic, Indexation, Electrical And Electronic Engineering
- by Shang-Ming Zhou
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- Pure Mathematics, Fuzzy Inference, Complex System, Adaptive learning
- by Antonio Dourado
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- Fuzzy Control, Control system, Real Time Control, Real Time

The technique of the direct and inverse fuzzy (F-)transforms of three different types is introduced and approximating properties of the inverse F-transforms are described. A method of lossy image compression and reconstruction on the basis of the F-transform is presented. In classical mathematics, various kinds of transforms (Fourier, Laplace, integral, wavelet) are used as powerful methods for construction of approximation

- by Irina Perfilieva
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- Data Compression, Image compression, Differential equation, Fuzzy Modelling
- by Vladimiro Miranda
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- Decision Making, Optimal Control, Fuzzy Logic, Fuzzy set theory
- by Vladimiro Miranda
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- Power Systems, Fuzzy Logic, Fuzzy set theory, Linear Programming
- by R. Sanchez
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- Modeling, Pulp, Neural Network, Multidisciplinary

- by mohit kumar
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- Applied Mathematics, Computer Science, A Priori Knowledge, Fuzzy Expert System
- by Coco Rulinda
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- Earth Sciences, Environmental Science, Remote Sensing, Fuzzy set theory
- by Michele Emdin
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- Artificial Intelligence, Expert Systems, Information Extraction, Pure Mathematics

- by Ralf Wieland
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- Engineering, Neural Network, Uncertainty modelling, Fuzzy Modelling