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Showing papers on "Fuzzy logic published in 2006"


Journal ArticleDOI
TL;DR: This paper demonstrates that it is unnecessary to take the route from general T2 FS to IT2 FS, and that all of the results that are needed to implement an IT2 FLS can be obtained using T1 FS mathematics.
Abstract: To date, because of the computational complexity of using a general type-2 fuzzy set (T2 FS) in a T2 fuzzy logic system (FLS), most people only use an interval T2 FS, the result being an interval T2 FLS (IT2 FLS). Unfortunately, there is a heavy educational burden even to using an IT2 FLS. This burden has to do with first having to learn general T2 FS mathematics, and then specializing it to an IT2 FSs. In retrospect, we believe that requiring a person to use T2 FS mathematics represents a barrier to the use of an IT2 FLS. In this paper, we demonstrate that it is unnecessary to take the route from general T2 FS to IT2 FS, and that all of the results that are needed to implement an IT2 FLS can be obtained using T1 FS mathematics. As such, this paper is a novel tutorial that makes an IT2 FLS much more accessible to all readers of this journal. We can now develop an IT2 FLS in a much more straightforward way

1,892 citations


Journal ArticleDOI
TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
Abstract: Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

1,575 citations


Journal ArticleDOI
TL;DR: In this article, a hierarchical multiple criteria decision-making (MCDM) model based on fuzzy-sets theory is proposed to deal with the supplier selection problems in the supply chain system.

1,559 citations


Journal ArticleDOI
TL;DR: It is shown that the proposed fuzzy TOPSIS method performs better than the other fuzzy versions of the TOPSis method.
Abstract: This paper proposes a fuzzy TOPSIS method based on alpha level sets and presents a nonlinear programming (NLP) solution procedure. The relationship between the fuzzy TOPSIS method and fuzzy weighted average (FWA) is also discussed. Three numerical examples including an application to bridge risk assessment are investigated using the proposed fuzzy TOPSIS method to illustrate its applications and the differences from the other procedures. It is shown that the proposed fuzzy TOPSIS method performs better than the other fuzzy versions of the TOPSIS method.

791 citations


Journal ArticleDOI
TL;DR: A new weight evaluation process using entropy method was applied in water quality assessment of the Three Gorges reservoir area and showed that this method was favorable for fuzzy synthetic evaluation when there were more than one evaluating objects.
Abstract: Considering the difficulty of fuzzy synthetic evaluation method in calculation of the multiple factors and ignorance of the relationship among evaluating objects, a new weight evaluation process using entropy method was introduced. This improved method for determination of weight of the evaluating indicators was applied in water quality assessment of the Three Gorges reservoir area. The results showed that this method was favorable for fuzzy synthetic evaluation when there were more than one evaluating objects. One calculation was enough for calculating every monitoring point. Compared with the original evaluation method, the method predigested the fuzzy synthetic evaluation process greatly and the evaluation results are more reasonable.

692 citations


Journal ArticleDOI
TL;DR: The aim of this paper is to extend the TOPSIS method to decision-making problems with fuzzy data, and the rating of each alternative and the weight of each criterion are expressed in triangular fuzzy numbers.

556 citations


Journal ArticleDOI
TL;DR: A method of image compression and reconstruction on the basis of the F-transform, which is a fuzzy partition of a universe into fuzzy subsets (factors, clusters, granules etc.), is presented.

548 citations


Journal ArticleDOI
TL;DR: In this paper, the authors describe a fuzzy vault, a cryptographic construction that allows a player Alice to place a secret value in a secure vault and "lock" it using a set A of elements from some public universe U. If Bob tries to "unlock" the vault using another set B of similar length, he obtains only if B is close to A, i.e., only if A and B overlap substantially.
Abstract: We describe a simple and novel cryptographic construction that we refer to as a fuzzy vault. A player Alice may place a secret value ? in a fuzzy vault and "lock" it using a set A of elements from some public universe U. If Bob tries to "unlock" the vault using a set B of similar length, he obtains ? only if B is close to A, i.e., only if A and B overlap substantially. In constrast to previous constructions of this flavor, ours possesses the useful feature of order invariance, meaning that the ordering of A and B is immaterial to the functioning of the vault. As we show, our scheme enjoys provable security against a computationally unbounded attacker. Fuzzy vaults have potential application to the problem of protecting data in a number of real-world, error-prone environments. These include systems in which personal information serves to authenticate users for, e.g., the purposes of password recovery, and also to biometric authentication systems, in which readings are inherently noisy as a result of the refractory nature of image capture and processing.

540 citations


Journal ArticleDOI
TL;DR: In this paper, an integrated framework based on fuzzy-QFD and a fuzzy optimization model is proposed to determine the product technical requirements (PTRs) to be considered in designing a product.

525 citations


Journal ArticleDOI
TL;DR: In this paper, apart from conventional weighting system, objective weight assignment procedures based on techniques such as artificial neural network (ANN), fuzzy set theory and combined neural and fuzzy set theories have been assessed for preparation of LSZ maps in a part of the Darjeeling Himalayas.

505 citations


Journal ArticleDOI
TL;DR: The condition is represented in the form of linear matrix inequalities (LMIs) and is shown to be less conservative than some relaxed quadratic stabilization conditions published recently in the literature and to include previous results as special cases.
Abstract: This paper proposes a new quadratic stabilization condition for Takagi-Sugeno (T-S) fuzzy control systems. The condition is represented in the form of linear matrix inequalities (LMIs) and is shown to be less conservative than some relaxed quadratic stabilization conditions published recently in the literature. A rigorous theoretic proof is given to show that the proposed condition can include previous results as special cases. In comparison with conventional conditions, the proposed condition is not only suitable for designing fuzzy state feedback controllers but also convenient for fuzzy static output feedback controller design. The latter design work is quite hard for T-S fuzzy control systems. Based on the LMI-based conditions derived, one can easily synthesize controllers for stabilizing T-S fuzzy control systems. Since only a set of LMIs is involved, the controller design is quite simple and numerically tractable. Finally, the validity and applicability of the proposed approach are successfully demonstrated in the control of a continuous-time nonlinear system.

Journal ArticleDOI
TL;DR: This paper presents an algorithm for network reconfiguration based on the heuristic rules and fuzzy multiobjective approach for minimizing the number of tie-switch operations.
Abstract: This paper presents an algorithm for network reconfiguration based on the heuristic rules and fuzzy multiobjective approach. Multiple objectives are considered for load balancing among the feeders and also to minimize the real power loss, deviation of nodes voltage, and branch current constraint violation, while subject to a radial network structure in which all loads must be energized. These four objectives are modeled with fuzzy sets to evaluate their imprecise nature and one can provide his or her anticipated value of each objective. Heuristic rules are also incorporated in the algorithm for minimizing the number of tie-switch operations. The effectiveness of the proposed method is demonstrated through an example.

Journal ArticleDOI
TL;DR: The proposed fuzzy Lyapunov function is formulated as a line-integral of a fuzzy vector which is a function of the state, and it can be regarded as the work done from the origin to the current state in the fuzzy vector field.

Journal ArticleDOI
TL;DR: The objective of this paper is to incorporate the concept of fuzzy (linguistic) quantifiers into the GIS-based land suitability analysis via ordered weighted averaging (OWA) via quantifier-guided OWA procedure.

Journal ArticleDOI
TL;DR: In this article, a fuzzy multiobjective linear model is developed to overcome the vagueness of the information for the first time in a fuzzy supplier selection problem, an asymmetric fuzzy-decision-making technique is applied to enable the decision-maker to assign different weights to various criteria.

Journal ArticleDOI
TL;DR: An information measure is proposed to computing discernibility power of a crisp equivalence relation or a fuzzy one, which is the key concept in classical rough set model and fuzzy-rough set model, and a general definition of significance of nominal, numeric and fuzzy attributes is presented.

Journal ArticleDOI
TL;DR: The FOGA (fuzzy ontology generation framework) is proposed for automatic generation of fuzzy ontology on uncertainty information and a fuzzy-based technique for integrating other attributes of database to the ontology is proposed.
Abstract: Ontology is an effective conceptualism commonly used for the semantic Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. Typically, fuzzy ontology is generated from a predefined concept hierarchy. However, to construct a concept hierarchy for a certain domain can be a difficult and tedious task. To tackle this problem, this paper proposes the FOGA (fuzzy ontology generation framework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: fuzzy formal concept analysis, concept hierarchy generation, and fuzzy ontology generation. We also discuss approximating reasoning for incremental enrichment of the ontology with new upcoming data. Finally, a fuzzy-based technique for integrating other attributes of database to the ontology is proposed

Journal ArticleDOI
Nima Amjady1
TL;DR: An efficient method based on a new fuzzy neural network has inter-layer and feed-forward architecture with a new hypercubic training mechanism for short-term price forecasting of electricity markets and can provide more accurate results than other price forecasting techniques.
Abstract: In this paper, an efficient method based on a new fuzzy neural network is proposed for short-term price forecasting of electricity markets. This fuzzy neural network has inter-layer and feed-forward architecture with a new hypercubic training mechanism. The proposed method predicts hourly market-clearing prices for the day-ahead electricity markets. By combination of fuzzy logic and an efficient learning algorithm, an appropriate model for the nonstationary behavior and outliers of the price series is presented. The proposed method is examined on the Spanish electricity market. It is shown that the method can provide more accurate results than the other price forecasting techniques, such as ARIMA time series, wavelet-ARIMA, MLP, and RBF neural networks.

Journal ArticleDOI
TL;DR: A new dynamic time-delay fuzzy wavelet neural network model is presented for nonparametric identification of structures using the nonlinear autoregressive moving average with exogenous inputs approach and incorporates the imprecision existing in the sensor data effectively.
Abstract: A new dynamic time-delay fuzzy wavelet neural network model is presented for nonparametric identification of structures using the nonlinear autoregressive moving average with exogenous inputs approach. The model is based on the integration of four different computing concepts: dynamic time delay neural network, wavelet, fuzzy logic, and the reconstructed state space concept from the chaos theory. Noise in the signals is removed using the discrete wavelet packet transform method. In order to preserve the dynamics of time series, the reconstructed state space concept from the chaos theory is employed to construct the input vector. In addition to denoising, wavelets are employed in combination with two soft computing techniques, neural networks and fuzzy logic, to create a new pattern recognition model to capture the characteristics of the time series sensor data accurately and efficiently. The model balances the global and local influences of the training data and incorporates the imprecision existing in the sensor data effectively. Experimental results on a five-story steel frame are employed to validate the computational model and demonstrate its accuracy and efficiency.

Journal ArticleDOI
TL;DR: A new method that transfers the house of quality (HOQ) approach typical of quality function deployment (QFD) problems to the supplier selection process is suggested and symmetrical triangular fuzzy numbers are suggested to capture the vagueness in people's verbal assessments.

Journal ArticleDOI
TL;DR: In SAFIS, the concept of ''Influence'' of a fuzzy rule is introduced and using this the fuzzy rules are added or removed based on the input data received so far.

Journal ArticleDOI
TL;DR: A control structure that makes possible the integration of a kinematic controller and an adaptive fuzzy controller for trajectory tracking is developed for nonholonomic mobile robots using a fuzzy logic system (FLS).
Abstract: In this paper, a control structure that makes possible the integration of a kinematic controller and an adaptive fuzzy controller for trajectory tracking is developed for nonholonomic mobile robots. The system uncertainty, which includes mobile robot parameter variation and unknown nonlinearities, is estimated by a fuzzy logic system (FLS). The proposed adaptive controller structure represents an amalgamation of nonlinear processing elements and the theory of function approximation using FLS. The real-time control of mobile robots is achieved through the online tuning of FLS parameters. The system stability and the convergence of tracking errors are proved using the Lyapunov stability theory. Computer simulations are presented which confirm the effectiveness of the proposed tracking control law. The efficacy of the proposed control law is tested experimentally by a differentially driven mobile robot. Both simulation and results are described in detail.

Journal ArticleDOI
TL;DR: In this article, a utility-based grade match method is proposed to transform both numerical data and qualitative (fuzzy) assessment information of various formats into the fuzzy belief structure, leading to a fuzzy belief decision matrix.

Journal ArticleDOI
TL;DR: F fuzzy number logic is introduced in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP, referred to as fuzzy AHP.
Abstract: Selecting process of a machine tool has been very important issue for companies for years, because the improper selection of a machine tool might cause of many problems affecting negatively on productivity, precision, flexibility and company’s responsive manufacturing capabilities. On the other hand, selecting the best machine tool from its increasing number of existing alternatives in market are multiple-criteria decision making (MCDM) problem in the presence of many quantitative and qualitative attributes. Therefore, in this paper, an analytic hierarchy process (AHP) is used for machine tool selection problem due to the fact that it has been widely used in evaluating various kinds of MCDM problems in both academic researches and practices. However, due to the vagueness and uncertainty on judgments of the decision-maker(s), the crisp pair wise comparison in the conventional AHP seems to insufficient and imprecise to capture the right judgments of decision-maker(s). That is why; fuzzy number logic is introduced in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP. Shortly, in this study, an intelligent approach is proposed, where both techniques; fuzzy logic and AHP are come together, referred to as fuzzy AHP. First, the fuzzy AHP technique is used to weight the alternatives under multiple attributes; second Benefit/Cost (B/C) ratio analysis is carried out by using both the fuzzy AHP score and procurement cost, of each alternative. The alternative with highest B/C ratio is found out and called as the ultimate machine tool among others. In addition, a case study is also presented to make this approach more understandable for a decision-maker(s).

Journal ArticleDOI
TL;DR: This paper defines precompact set in intuitionistic fuzzy metric spaces and proves that any subset of an intuitionism fuzzy metric space is compact if and only if it is precompacts and complete.
Abstract: In this paper, we define precompact set in intuitionistic fuzzy metric spaces and prove that any subset of an intuitionistic fuzzy metric space is compact if and only if it is precompact and complete. Also we define topologically complete intuitionistic fuzzy metrizable spaces and prove that any G δ set in a complete intuitionistic fuzzy metric spaces is a topologically complete intuitionistic fuzzy metrizable space and vice versa. Finally, we define intuitionistic fuzzy normed spaces and fuzzy boundedness for linear operators and so we prove that every finite dimensional intuitionistic fuzzy normed space is complete.

01 Jan 2006
TL;DR: Different from the existing ER algorithm that is of a recursive nature, the new fuzzy ER algorithm provides an analytical means for combining all attributes without iteration, thus providing scope and flexibility for sensitivity analysis and optimisation.
Abstract: Many multiple attribute decision analysis (MADA) problems are characterised by both quantitative and qualitative attributes with various types of uncertainties. Incompleteness (or ignorance) and vagueness (or fuzziness) are among the most common uncertainties in decision analysis. The evidential reasoning (ER) approach has been developed in the 1990s and in the recent years to support the solution of MADA problems with ignorance, a kind of probabilistic uncertainty. In this paper, the ER approach is further developed to deal with MADA problems with both probabilistic and fuzzy uncertainties. In this newly developed ER approach, precise data, ignorance and fuzziness are all modelled under the unified framework of a distributed fuzzy belief structure, leading to a fuzzy belief decision matrix. A utility-based grade match method is proposed to transform both numerical data and qualitative (fuzzy) assessment information of various formats into the fuzzy belief structure. A new fuzzy ER algorithm is developed to aggregate multiple attributes using the information contained in the fuzzy belief matrix, resulting in an aggregated fuzzy distributed assessment for each alternative. Different from the existing ER algorithm that is of a recursive nature, the new fuzzy ER algorithm provides an analytical means for combining all attributes without iteration, thus providing scope and flexibility for sensitivity analysis and optimisation. A numerical example is provided to illustrate the detailed implementation process of the new ER approach and its validity and wide applicability. 2004 Elsevier B.V. All rights reserved.

Journal ArticleDOI
TL;DR: The novelty in the paper is development of the absolute agility index, a unique and unprecedented attempt in agility measurement, using fuzzy logic to address the ambiguity in agility evaluation.

Journal ArticleDOI
TL;DR: In this article, a maximum power point tracker using fuzzy set theory is presented to improve energy conversion efficiency of photovoltaic (PV) generation, by using a fuzzy cognitive network, which is in close cooperation with the presented fuzzy controller.
Abstract: The studies on the photovoltaic (PV) generation are extensively increasing, since it is considered as an essentially inexhaustible and broadly available energy resource. However, the output power induced in the photovoltaic modules depends on solar radiation and temperature of the solar cells. Therefore, to maximize the efficiency of the renewable energy system, it is necessary to track the maximum power point of the PV array. In this paper, a maximum power point tracker using fuzzy set theory is presented to improve energy conversion efficiency. A new method is proposed, by using a fuzzy cognitive network, which is in close cooperation with the presented fuzzy controller. The new method gives a very good maximum power operation of any PV array under different conditions such as changing insolation and temperature. The simulation studies show the effectiveness of the proposed algorithm

Journal ArticleDOI
TL;DR: A methodology based on fuzzy inference systems (FIS) to assess water quality and a water quality index calculated with fuzzy reasoning has been developed and emerges as a suitable and alternative tool to be used in developing effective water management plans.

MonographDOI
01 Jan 2006
TL;DR: The book presents a meta-modelling framework for mapping FuzzyEER Model Concepts to Relations and FSQL, a fuzzy SQL forFuzzy Databases, and some examples of use cases.
Abstract: Sample of Contents: State of the Art in Fuzzy Database Modeling FuzzyEER Mapping FuzzyEER Model Concepts to Relations FSQL: A Fuzzy SQL for Fuzzy Databases.