IEEE International Conference on Fuzzy Systems

Publications in this journal

• Conference Proceeding: On another approach to the definition of an L-fuzzy valued integral

  V. Ruza, S. Asmuss
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  ABSTRACT: We continue to develop a construction of an L-fuzzy valued measure extending a crisp measure defined on a σ-algebra of crisp sets to an L-fuzzy valued measure defined on a T_M- tribe. We describe two equivalent approaches to define an L-fuzzy valued integral of non-negative measurable functions.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Manufacturing modeling using an evolutionary fuzzy regression

  K.Y. Chan, T.S. Dillon, S.H. Ling, C.K. Kwong
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  ABSTRACT: Fuzzy regression is a commonly used approach for modeling manufacturing processes in which the availability of experimental data is limited. Fuzzy regression can address fuzzy nature of experimental data in which fuzziness is not avoidable while carrying experiments. However, fuzzy regression can only address linearity in manufacturing process systems, but nonlinearity, which is unavoidable in the process, cannot be addressed. In this paper, an evolutionary fuzzy regression which integrates the mechanism of a fuzzy regression and genetic programming is proposed to generate manufacturing process models. It intends to overcome the deficiency of the fuzzy regression, which cannot address nonlinearities in manufacturing processes. The evolutionary fuzzy regression uses genetic programming to generate the structural form of the manufacturing process model based on tree representation which can address both linearity and nonlinearities in manufacturing processes. Then it uses a fuzzy regression to determine outliers in experimental data sets. By using experimental data excluding the outliers, the fuzzy regression can determine fuzzy coefficients which indicate the contribution and fuzziness of each term in the structural form of the manufacturing process model. To evaluate the effectiveness of the evolutionary fuzzy regression, a case study regarding modeling of epoxy dispensing process is carried out.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Rough set approach to user modeling

  B.H. Wu
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  ABSTRACT: The intelligence of an interactive system is exhibited through the evolution of its intelligent behaviors, namely, its effectiveness in performing tasks and its adaptiveness to both variations of task conditions and different users. Having a good user modeling component in any intelligent interactive system becomes crucial to the performance of that system. We have developed a computational approach to building intelligent tutoring systems (ITS) in conjunction with our framework for ITS [1]. This computational approach employs two exploratory AI techniques-a hybrid knowledge representation model as an implementation mechanism of ITS and a rough set [2] approximation approach to user modeling. In this article, we focus on discussing the rough set approach to user modeling of the system in detail.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Synchronization of uncertain fractional order chaotic systems via adaptive interval type-2 fuzzy sliding mode control

  Tsung-Chih Lin, Tun-Yuan Lee, V.E. Balas
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  ABSTRACT: In this paper, a novel adaptive interval type-2 fuzzy sliding mode control (AITFSMC) is proposed to handle high level uncertainties facing the fuzzy logic controller (FLC) in dynamic fractional order chaotic systems such as uncertainties in inputs to the FLC, uncertainties in control outputs, linguistic uncertainties and uncertainties associated with the noisy training data. Based on the learning algorithm combining Lyapunov approach and sliding mode control, free parameters of the AITSMC can be tuned on line by output feedback control law and adaptive law to synchronize two different uncertain fractional order chaotic systems. Meanwhile, the chattering phenomena in the control efforts can be reduced. During the design procedure, not only the stability and robustness can be guaranteed but also the external disturbance on the synchronization error can be attenuated. The numerical simulation is performed to illustrate the effectiveness of the proposed control strategy.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Linguistic description of adult skeletal age-at-death estimations from fuzzy integral acquired fuzzy sets

  D.T. Anderson, J.M. Keller, M. Anderson, D.J. Wescott
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  ABSTRACT: Previously, we introduced a novel method to estimate adult skeletal age-at-death using the Sugeno fuzzy integral (FI). Specifically, we took a multi-hypothesis testing approach to make the classical FI yield a fuzzy set (FS)-valued result, which is not guaranteed to be normal or convex, based on interval-valued sources of information (aging methods). We showed quantitative results for summarizing the FS and comparing the single decision to a known age-at-death. In this article, we extend our prior work and present formulas to measure the uncertainty in the resultant FSs. We generate linguistic descriptions to establish domain standardization for the goal of assisting forensic and biological anthropologists. Specifically, we introduce fuzzy class definitions for age-at-death FSs and we present an OWA contrast approach to measure the degree of specificity in age-at-death FSs.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Apply different fuzzy integrals in unit selection problem of real time strategy game

  Y.J. Li, P.H.F. Ng, H.B. Wang, S.C.K. Shiu, Y. Li
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  ABSTRACT: Choquet Integral (CI), which is known as a fuzzy measure-based technique, has been a general aggregation tool for multi-criteria decision making problem. In this paper, we apply Choquet Integral to unit selection problem in Real Time Strategy (RTS) game. In addition, three new fuzzy integrals named Mean based Fuzzy Integral (Me-based FI), Max-based Fuzzy Integral (Ma-based FI), and Order-based Fuzzy Integral (Or-based FI) are developed, which relax the monotonicity requirement of the traditional fuzzy measures and consider different properties of game play. We compare the performance of Choquet Integral and the new proposed ones on this practical application with highly non-monotonic data. Experiments show that the proposed new fuzzy integrals achieved better learning performance and testing result.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: A bacterial foraging PSO — DE algorithm for solving reserve constrained Dynamic Economic Dispatch problem

  K. Vaisakh, P. Praveena, S.R.M. Rao
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  ABSTRACT: This paper introduces a solution to Dynamic Economic Dispatch (DED) problem using a hybrid optimization methodology bacterial foraging and PSO-DE (BPSO-DE) by integrating Bacterial foraging optimization Algorithm (BFOA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). In the proposed method BFOA performs local search and global search for entire search space is accomplished through PSO-DE operators in this way they move to reach the global optimization. The BFOA also takes care of the constraints such as ramp-rate limits, valve-point loading effects, system load demand, prohibited operating zones, power losses and spinning reserve capacity. A ten unit test system is considered to show the effectiveness of the proposed method over other existing methods.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Fuzzy PID controller design for artificial finger based SMA actuators

  A. Khodayari, M.M. Kheirikhah, M. Talari
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  ABSTRACT: Shape Memory Alloy (SMA) wires are currently employed in robotics, as well as prosthetic limbs and medical equipment. Due to advantages such as reducing the size in the application, high power-to-weight ratio, elimination of complex transmission systems and noiseless actuation, and human machine interface, these materials are used as actuators in the prosthesis limb. Because of hysteresis property and nonlinear behavior of SMA, control of these actuators is very complicated. In this paper, the design of control algorithms has been discussed for SMA actuators in the artificial fingers with 3 DOF, which includes PID-fuzzy controller. Gains of controllers are set so that the current applied to SMA wires has minimum overshoot and output of system has minimal time to achieve stability. The simulation results compared with actual measured data show how well the controllers decrease the overshoot and time of stability of input signal to SMA wires.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Is it rational to partition a data set using kernel-clustering?

  K. Sarkar, N.R. Pal
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  ABSTRACT: Many interesting papers have been written in the recent past on kernel clustering and many attractive results have also been demonstrated. Here we question the rationality behind such clustering approaches. Using simple data sets we argue and demonstrate that it is not a good idea to find clusters in the kernel space when the objective is to look for clusters in the original data because in the kernel space the data may have a different geometry from that in the original feature space. In particular we demonstrate the following : (1) improper choice of the number of clusters may lead to very counterintuitive clusters (e.g., instead of merging nearby clusters, it may merge clusters that are far from each other) and (2) improper choice of kernel parameters has a significant effect on the extracted clusters and it can even impose arbitrary cluster structures that are undoubtedly absent in the original data. However, we definitely do not imply that kernel clustering can never produce desirable results. In fact, kernel clustering could be useful provided we can choose right kernel parameters. But the process being unsupervised, we do not have a solution to this issue yet. In this study, for illustration, we use one variant of the kernel Fuzzy C-Means (KFCM) clustering algorithm in conjunction with Polynomial kernels.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Generalized projective synchroization of time-delayed chaotic systems via sliding adaptive fuzzy control

  N. Farzbod, H. Zarabadipour, M.A. Shoorehdeli, F. Farivar
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  ABSTRACT: In this paper, generalized projective synchronization (GPS) of two time-delayed chaotic systems using sliding adaptive fuzzy control (SAFC) is investigated. The proposed method combines the advantages of the adaptive control, fuzzy systems and sliding mode control theory. Lyapunov stability theory is employed to guarantee the stability of error dynamics. Assuming that the parameters of the chaotic drive system are unknown, recursive least square (RLS) method is applied to estimate these unknown parameters. Simulation results show the validity and effectiveness of the proposed method for synchronization of two identical and nonidentical time-delayed chaotic systems.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Human motion tracking for cognitive rehabilitation in informationally structured space based on sensor networks

  Y. Toda, Y. Kodai, E. Hiwada, N. Kubota
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  ABSTRACT: This paper discusses measurement methods of human behaviors based on sensor network and human interaction of rehabilitation using robot partners. First, we explain robot partners and sensor networks for rehabilitation. Next, we apply a steady-state genetic algorithm to extract human motions from 3D distance image. Finally, we discuss the effectiveness of the proposed methods through several experimental results.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: A distributed smart routing scheme for terrestrial sensor networks with hybrid Neural Rough Sets

  F. Jiang, M. Frater, S.S.H. Ling
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  ABSTRACT: The limited power consumption, as a major constraint, presents challenges in improving the network throughput for Wireless Sensor Networks (WSNs). Due to the limited computational power, the applications of WSNs in Terrestrial Networks require the capability to pre-process the observation data so as to remove irrelevant features or factors from multi-dimensional dataset. This paper proposes a intelligent distributed energy efficient routing algorithm inspired from natural learning and adaptation process with the aid of hybrid Neural Rough Sets theory, which is used to efficiently reduce the dimensionality of input dataset. The algorithmic implementation and experimental validation are described in this paper. Details of the algorithm and its testing procedures are presented in comparison with the other power-aware protocols, e.g., mini-hop. The validation of the proposed model is carried out via a wireless sensor network test-bed implemented in Castalia Simulator. The experimental results show the network performance measurements such as delay, throughput and packet loss that have been greatly improved as the outcome of applying this integration with Neural Rough Sets.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Fusion of fuzzy logic and PD control for a five-fingered smart prosthetic hand

  Cheng-Hung Chen, D.S. Naidu
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  ABSTRACT: A hybrid of soft control technique of adaptive neuro-fuzzy inference system (ANFIS) and fuzzy logic (FL) and hard control technique of proportional-derivative (PD) for a five-fingered, smart prosthetic hand is presented. The ANFIS is used for inverse kinematics and FL is used for tuning the PD parameters with two input layers (error and error change) using 7 triangular membership functions and 49 fuzzy logic rules. Simulation results with FL-tuned PD controller exhibit superior performance compared to the PD and PID control alone.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: An approach for stability analysis of polynomial fuzzy model-based control systems

  M. Narimani, H.K. Lam, K. Althoefer, R. Dilmaghani, C. Wolfe, C. Deters
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  ABSTRACT: Stability analysis of polynomial fuzzy model-based (PFMB) control systems under the parallel distributed compensation (PDC) design technique is investigated. A new polynomial fuzzy controller (PFC) is introduced to release conservativeness in the existing approaches. Compared to the conventional (PFC), the controller under consideration in this paper has a favorable property which introduces some more variables in the stability conditions such that, the solution of the derived stability conditions can be explored in a larger group of potential solutions. This property may lead to further relax stability conditions. However, the stability conditions will not be in the form of SOS conditions. Hence, particle swarm optimization (PSO) is employed to explore the solution of the derived stability conditions which are in the form of state-dependent BMI. It is shown that the conventional PFC is a special case of that of proposed one. Finally, a simulation example is given to illustrate the effectiveness of the proposed approach.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Probing performance evaluation for NPD process by using fuzzy MCDM approach

  Chia-Chun Hsiang, Meng-Jong Kuan, Gwo-Hshiung Tzeng
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  ABSTRACT: Due to the rapid changing marketplace, technology, equipment and raw materials, companies pursuit competitiveness by the new product and new product development (NPD) process for the purpose of innovation, high quality, and speed to the market. It is a gradual trend that the product life cycle is becoming shorter. The product manager intends to achieve the highest customer satisfaction, product value and product continuity. Therefore, to evaluate performance of NPD becomes a critical issue on the NPD process selection which is considered in many different uncertain aspects. Thus, this situation can be regarded as a fuzzy multiple criteria decision-making (FMCDM) problem, so the vagueness and uncertainty of subjective perception could be considered. In this paper, the non-additive (called super-additive) fuzzy integral is used to deal with evaluation of fuzzy MCDM problems particularly while there is dependence among the selected criteria. We can evaluate the quality performance of NPD process according to the result of empirical analysis. Consequently, DEMATEL is used to explore the relevance for the selected criteria of NPD process which is used to find the directions of problem-solving. The results of this study will provide NPD project team a guidance to satisfy the customer needs and creative the value of enterprise business.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: An adaptive type-2 input based nonsingleton type-2 Fuzzy Logic System for real world applications

  N. Sahab, H. Hagras
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  ABSTRACT: A Fuzzy Logic System (FLS) is generally credited with being an adequate methodology for real world applications which are subject to high uncertainty levels. Recent works have shown that interval type-2 FLSs can outperform type-1 FLSs in the applications which encompass high uncertainty levels. However, the majority of interval type-2 FLSs handle the linguistic and input numerical uncertainties using singleton interval type-2 FLSs that mix the numerical and linguistic uncertainties to be handled only by the linguistic labels type-2 fuzzy sets. This ignores the fact that if input numerical uncertainties were present, they should affect the incoming inputs to the FLS. Even in the papers that employed nonsingleton type-2 FLSs, the input signals were assumed to have a predefined shape (mostly Gaussian or triangular) which might not reflect the real uncertainty distribution which can vary with the associated measurement. In our previous work, we have presented some of the theoretical basis for generating an adaptive type-2 fuzzy input which is better able to represent the encountered uncertainty at a given measurement. The nonsingleton type-2 fuzzy inputs are dynamic and they are automatically generated from data and they do not assume a specific shape about the uncertainty distribution associated with the given sensor. In this paper, we will present an overview on how the adaptive type-2 input based nonsingleton interval type-2 FLS can operate in real time. We will present real world experiments using a mobile robot which will show how under high input uncertainty levels, the nonsingleton type-2 FLS can give a good performance and outperform its singleton type-2 and type-1 FLSs counterparts.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: A clustering method for geometric data based on approximation using conformal geometric algebra

  Minh Tuan Pham, K. Tachibana, T. Yoshikawa, T. Furuhashi
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  ABSTRACT: Clustering is one of the most useful methods for understanding similarity among data. However, most conventional clustering methods do not pay sufficient attention to the geometric properties of data. Geometric algebra (GA) is a generalization of complex numbers and quaternions able to describe spatial objects and the relations between them. This paper uses conformal GA (CGA), which is a part of GA, to transform a vector in a real vector space into a vector in a CGA space and presents a proposed new clustering method using conformal vectors. In particular, this paper shows that the proposed method was able to extract the geometric clusters which could not be detected by conventional methods.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: Fuzzy reinforcement learning for System of Systems (SOS)

  H. Berenji, M. Jamshidi
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  ABSTRACT: The System of Systems (SOS) technology is an advanced technology for Intelligent Systems that is developed with multiple intelligent systems. Recently, there has been a growing interest in a class of complex systems (robotic swarm as an example) whose constituents are themselves complex. Performance optimization, robustness and reliability among an emerging group of heterogeneous systems in order to realize a common goal have become the focus of various applications including military, security, aerospace, space, manufacturing, service industry, environmental systems, and disaster management, to name a few. In this paper, we discuss how Fuzzy Reinforcement Learning (FRL) can be used in SOS.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
• Conference Proceeding: A two-step approach of feature construction for a genetic learning algorithm

  D. Garcia, A. Gonzalez, R. Perez
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  ABSTRACT: Traditionally, fuzzy rule based models work with a fixed set of features to describe a particular problem. Our proposal is to use feature construction by means of functions in order to obtain new variables that allow us to get more information about the problem. In particular, we propose the use of previously defined functions over the input variables in the antecedent of the rules. This let us to know if a combination of variables is able to provide us with more information than each one of them separately. In addition, we use a structure that helps us to manage and also restrict the number of functions under consideration by the learning algorithm. We also present a new model of rule in order to represent this kind of knowledge by extending a basic learning fuzzy rule-based model. Finally, we show the experimental study associated with this work.
  Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011