Journal of Intelligent & Fuzzy Systems - Volume 26, issue 2

Authors: Meng, Fanyong | Tan, Chunqiao | Zhang, Qiang

Article Type: Research Article

Abstract: In this study, we first define the uncertain linguistic Choquet averaging (ULCA) operator and the generalized Shapley uncertain linguistic Choquet averaging (GS-ULCA) operator. Especially, the GS-ULCA operator does not only globally consider the importance of the elements and their ordered positions, but also overall reflect the correlations among them and their ordered positions. Meantime, some desirable properties are studied. Furthermore, an approach to multi-attribute group decision making under uncertain linguistic environment is developed, where the interactions among experts and attributes are respectively considered. Moreover, if the information about the weights of experts and attributes is incompletely known, the models for …the optimal fuzzy measures on expert set and attribute set are respectively established, which are based on gray relational analysis (GRA) method. Finally, a practical application of the developed approach to the problem of evaluating university faculty for tenure and promotion is provided. Show more

Keywords: Multi-attribute group decision making, uncertain linguistic variable, fuzzy measure, Choquet integral, generalized Shapley function

DOI: 10.3233/IFS-130767

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 769-780, 2014

Authors: Ozkok, Murat | Cebi, Selcuk

Article Type: Research Article

Abstract: In a shipyard production system, launching operation is vital process since launching stage is time consuming process as well as being high cost. Therefore, this is a significant issue for shipyards. Choosing the most appropriate one among launching methods gives an advantage to shipyards to obtain competitive power against their competitors. If this is done, shipyards can commit to delivery of more ships and make more profit. In this study, launching methods are evaluated in terms of various performance criteria by means of an integrated method including Analytic Hierarchy Process (AHP), Fuzzy Information Axiom (FIA), Technique for Order Performance by …Similarity to Ideal Solution (TOPSIS), and Strengths, Weaknesses, Opportunities, and Threats (SWOT) analyses. Then, the dry docking technique was determined as the most convenient launching method with respect to the conflicting criteria. Show more

Keywords: Ship launching, AHP, FIA, TOPSIS, SWOT

DOI: 10.3233/IFS-130768

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 781-791, 2014

Authors: Hazarika, Bipan

Article Type: Research Article

Abstract: An ideal I is a family of subsets of positive integers $\mathbb{N}$ which is closed under taking finite unions and subsets of its elements. In this paper we have introduced ideal convergent sequences of fuzzy real numbers using σ-uniform density. Furthermore, inclusion between Iσ -convergence and invariant convergence also Iσ -convergence and $[V_{\sigma}]^{F}_p$ -convergence were given.

Keywords: Ideal, I-convergence, σ-uniform density, fuzzy numbers, strongly σ-convergence

DOI: 10.3233/IFS-130769

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 793-799, 2014

Authors: Chaudhary, Arvind Kumar | Pandey, Arun Kumar | Dubey, Avanish Kumar

Article Type: Research Article

Abstract: Today's fast growing sheet metal industries are demanding overall improvement in cut quality rather than improving different quality characteristics individually. The laser cutting has proven to be the quality cutting process for almost any category of materials with few limitations. The multiple quality characteristics may be improved by controlling the process variables at optimum level. The paper presents a methodology for the simultaneous optimization of multiple quality characteristics in laser cutting process by developing the software ‘CATFMO’ (Computer Aided Taguchi-Fuzzy Multi-Optimization). The software results have been validated by comparing the published experimental data and found suitable. This methodology has been …applied for simultaneous optimization of kerf width, cut edge surface roughness and heat affected zone in laser cutting of difficult-to-laser-cut Aluminium alloy sheet. Show more

Keywords: Taguchi methodology, fuzzy logic, hybrid approach, multi-objective optimization, laser cutting process

DOI: 10.3233/IFS-130770

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 801-810, 2014

Authors: Tanveer, M.

Article Type: Research Article

Abstract: In the recent articles, Khan and Sumitra (Appl. Math. Sci., 5(29)(2011), 1421-1430) and Singh et al. (Int. J. Math. Anal., 5(27) (2011), 1301-1308) claim a fuzzy version of common fixed point theorem of Bouhadjera and Godet-Thobie [3]. The results of aforementioned articles contain flaws and are not correct in their present form. We provide some examples to demonstrate that this claim is false unless some additional conditions are imposed. Our note is desired to complete the interesting results in the quoted paper.

Keywords: Fuzzy metric space, compatible maps, sub compatible maps, sub sequential continuity and reciprocal continuity

DOI: 10.3233/IFS-120772

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 811-814, 2014

Authors: Chiang, Mao-Hsiung | Lee, Lian-Wang | Liu, Hsien-Hsush

Article Type: Research Article

Abstract: The electro-hydraulic displacement-controlled system (EHDCS) performs specific non-linear and time-varying characteristics such that an exact model-based controller is complicated to be realized and the servo control is difficult to be implemented. In this study, the design method and experimental implementation of an adaptive fuzzy controller with self-tuning fuzzy sliding-mode compensation (AFC-STFSMC) are proposed which has on-line tuning ability for dealing with the system time-varying and non-linear uncertain behaviours for adjusting the control rule parameters. This control strategy employs the adaptive fuzzy approximation technique to design the equivalent controller of the conventional sliding-mode control (SMC). Furthermore, the fuzzy sliding-mode control scheme …with self-tuning ability is introduced to compensate the approximation error of the equivalent controller for improving the control performance. The proposed AFC-STFSMC scheme can design the sliding-mode controller with no requirement of the system dynamic model, be free from chattering, be stable tracking control performance, and be robust to uncertainties. Moreover, the stability proof of the proposed scheme using Lyapunov method is presented. The experimental results of the position control and the path control in EHDCS with different strokes and external disturbance forces show that the proposed AFC-STFSMC approach can achieve excellent control performance and robustness with regard to parameter variations and external disturbance. Show more

Keywords: Electro-hydraulic displacement-controlled system, adaptive fuzzy control, fuzzy sliding-mode control, adaptive fuzzy controller with self-tuning fuzzy sliding-mode compensation, position control and path control

DOI: 10.3233/IFS-130773

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 815-830, 2014

Authors: Khashei, Mehdi | Bijari, Mehdi

Article Type: Research Article

Abstract: Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing forecasters. Both theoretical and empirical findings have indicated that integration of different models can be an effective way of improving upon their predictive performance, especially when the models in the hybridization are quite different. In the literature, several hybrid techniques have been proposed by combining linear and nonlinear models, in order to overcome the deficiencies of single models and yield results that are more accurate. However, recent research activities in hybrid linear and nonlinear models indicate that these models have two basic limitations that have …decreased their popularity for time series forecasting. These two basic limitations are: (a) the hybrid linear and nonlinear models have some assumptions that will degenerate their performance if the opposite situations occur, and (b) the hybrid linear and nonlinear models require a large amount of historical data in order to produce accurate results. In this paper, a novel hybrid model is proposed for time series forecasting by combining linear autoregressive integrated moving average (ARIMA), nonlinear artificial neural networks (ANNs), and fuzzy models. In the proposed model, no prior assumption of traditional hybrid linear and nonlinear models is considered for the relationship between the linear and nonlinear components. In the proposed model the data limitation of traditional hybrid linear and nonlinear models is also lifted through investing on the advantages of the fuzzy models. Empirical results of financial markets, especially exchange rate market, forecasting indicate that proposed model performs significantly better than its components used separately, traditional hybrid linear and nonlinear, and other fuzzy and nonfuzzy models in incomplete data situations. Show more

Keywords: Artificial neural network (p, d, q), fuzzy logic and models, time series forecasting, incomplete data, financial markets, exchange rate

DOI: 10.3233/IFS-130775

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 831-845, 2014

Authors: Altınok, Hıfsı

Article Type: Research Article

Abstract: In this study we introduce the concepts of Δm -statistical convergence of order β and strong $\Delta_{p}^{m}$ -Cesàro summability of order β for sequences of fuzzy numbers by helping many examples. Also, we establish some properties which are valid for sequences of real numbers, but not for sequences of fuzzy numbers.

Keywords: Fuzzy number, statistical convergence, cesàro summability, difference operator

DOI: 10.3233/IFS-130776

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 847-856, 2014

Authors: Praczyk, Tomasz

Article Type: Research Article

Abstract: The neuro-evolution is a domain of artificial intelligence which uses the evolutionary approach to produce artificial neural networks. There are many neuro-evolutionary methods and one of them is Assembler Encoding. This paper compares Assembler Encoding with other methods from the range of neuro-evolution and and reinforcement learning. During comparison tests, the task was to form neuro-controllers for three variants of the inverted pendulum problem. The variants differed in the amount of information supplied to each neuro-controller and in the number of poles installed on a cart.

Keywords: Evolutionary neural networks

DOI: 10.3233/IFS-130777

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 857-868, 2014

Authors: Serra, Ginalber L.O. | Silva, Joabe A.

Article Type: Research Article

Abstract: This paper proposes the analysis and design of TS fuzzy robust PID control based on gain and phase margins specifications for uncertain nonlinear dynamic systems with time delay. The input-output data set of the uncertain nonlinear time delay dynamic system is decomposed into several input-output spaces by Gustafson-Kessel (GK) clustering algorithm, which are used to compute several linear submodels by least squares algorithm, and grouped in a Takagi-Sugeno (TS) fuzzy inference system. From the gain and phase margins specifications, in the frequency domain, analytical formulas are derived for fuzzy model based robust PID control design via Paralel and Distributed Compensation …(PDC) strategy, considering the influence of the time delay. The main contribution of the paper is the proposal of two theorems related to necessary and sufficient conditions for fuzzy robust control design. The first theorem shows that the robust PID controller in the i-th rule of the fuzzy robust PID controller guarantees the gain and phase margins specifications for the corresponding linear model. The second theorem shows that the robust PID controller in the i-th rule of the fuzzy robust PID controller guarantees the stability for all linear models. A simulation example illustrates the efficiency of the fuzzy controller for control of a single link robotic manipulator when compared to others control methods. The experimental results for real-time fuzzy robust PID control of a termic process are obtained to demonstrate the effectiveness and practical viability of the proposed strategy. Show more

Keywords: Fuzzy model based control, robust stability, PID controller, nonlinear systems, time delay

DOI: 10.3233/IFS-130778

Citation: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 2, pp. 869-888, 2014