Journal of Intelligent & Fuzzy Systems - Volume 32, issue 1

Authors: Fazakis, Nikos | Karlos, Stamatis | Kotsiantis, Sotiris | Sgarbas, Kyriakos

Article Type: Research Article

Abstract: The most important asset of semi-supervised learning (SSL) methods is the use of available unlabeled data combined with an enough smaller set of labeled examples, so as to increase the classification accuracy compared with the default procedure of supervised methods, in which during the training only the labeled data are used. The encapsulation of classifier ensembles that produce different models through training process into semi-supervised schemes seems to be a promising strategy for enhanced learning ability. In this work, a Self-trained Rotation Forest (Self-RotF) algorithm and a variant of this (Weighted-Self-RotF) are presented. We performed an in depth comparison with …other well-known semi-supervised classification methods on standard benchmark datasets and after having tested their performance with statistical tests, we finally reached to the point that the presented technique had better accuracy in most cases. Show more

Keywords: Machine learning, semi-supervised methods, Rotation Forest, classification using labeled and unlabeled data, ensemble methods

DOI: 10.3233/JIFS-152641

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 711-722, 2017

Authors: Zhao, Ruiying | Chen, Ye-Hwa | Jiao, Shengjie

Article Type: Research Article

Abstract: The paper considers an optimal design problem for a class of uncertain systems. The systems are nonlinear and the state is constrained to be positive. The uncertainty of the system is time-varying and bounded, with the bound lies within a prescribed fuzzy set. The control input of the system may also be constrained to be one-sided (i.e., either positive or negative). A transformation of the state is proposed to release the state constraint. Based on a partial sign-definiteness knowledge of the uncertainty, a one-sided robust control is presented. The control structure is deterministic and is not fuzzy if -then …rule-based. By using the fuzzy description of uncertainty, the paper proposes an optimal design problem of the one-sided robust control. It is proven that the global solution to this optimal design problem always exists and is unique. The performance of the resulting controlled system is deterministically guaranteed as well as fuzzily optimized. The control design is illustrated by applying to a drug administration problem. Show more

Keywords: Fuzzy dynamic system, state constraint, control constraint, fuzzy set theory, optimal design

DOI: 10.3233/JIFS-15802

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 723-735, 2017

Authors: Gao, Ninghua | Li, Qingguo | Huang, Xiaokun

Article Type: Research Article

Abstract: Based on a complete residuated lattice, algebraic fuzzy closure operators and algebraic fuzzy closure L -systems on a fuzzy complete lattice are defined and investigated. We establish a “one-to-one” correspondence between algebraic fuzzy closure operators and algebraic fuzzy closure L -systems under a condition on fuzzy order. Moreover, it is shown that the category of (algebraic) fuzzy closure operator spaces is isomorphic to the category of (algebraic) fuzzy closure L -system spaces.

Keywords: (Algebraic) fuzzy closure operators, (Algebraic) fuzzy closure L-systems, fuzzy complete lattices, category

DOI: 10.3233/JIFS-15979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 737-748, 2017

Authors: Liu, Caihui | Pedrycz, Witold | Wang, Meizhi

Article Type: Research Article

Abstract: In this paper, we study covering-based multigranulation decision-theoretic rough sets in a multi-covering space. From viewpoints of granule, we propose the notions of covering-based mean multigranulation decision-theoretic rough sets, covering-based optimistic multigranulation decision-theoretic rough sets and covering-based pessimistic multigranulation decision-theoretic rough sets, realized, on the basis of Bayesian decision procedure. We first investigate some basic properties of those models. Then, we investigate the relationships between the proposed covering-based multigranulation decision-theoretic rough set models and other related rough set models. Thirdly, we elaborate on the interrelationships among the proposed models. Finally, an example is employed to illustrate the application of the …proposed models. Show more

Keywords: Bayesian decision procedure, covering, decision-theoretic rough sets, multigranulation rough sets

DOI: 10.3233/JIFS-16020

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 749-765, 2017

Authors: Yang, Wei | Pang, Yongfeng | Shi, Jiarong | Yue, Hongyun

Article Type: Research Article

Abstract: This study develops a new multiple attribute decision making method based on linear assignment method with linguistic hesitant intuitionistic fuzzy information considering correlation. First, we develop some linguistic hesitant intuitionistic fuzzy correlated aggregation operators by using Choquet integral. Then we propose a new linguistic hesitant intuitionistic fuzzy linear assignment method considering correlation of attributes. A numerical example has been presented to illustrate feasibility and practical advantages of the new method. Comparisons of new method with other methods, including the linguistic hesitant intuitionistic fuzzy correlated TOPSIS method, the method based on the generalized linguistic hesitant intuitionistic fuzzy correlated averaging (GLHIFCA) operator, …have been conducted. Show more

Keywords: Multiple attribute decision making, hesitant fuzzy set, linear assignment method, Choquet integral, aggregation operator

DOI: 10.3233/JIFS-16042

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 767-780, 2017

Authors: Çetkin, Vildan | Aygünoğlu, Abdülkadir | Aygün, Halis

Article Type: Research Article

Abstract: It is known that compactness occupies a very important place in general topology and also in fuzzy topology. In this paper, a stronger form of a fuzzy soft topology which is called a parameterized L -fuzzy soft topology is presented and compactness of a L -fuzzy soft set is established in the described topological space, where L is a complete DeMorgan algebra. Then the fundamental properties and characterizations of compactness are observed.

Keywords: Fuzzy soft set, fuzzy soft topology, continuity, compactness

DOI: 10.3233/JIFS-16043

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 781-790, 2017

Authors: Raj, Retheep | Sivanandan, K.S.

Article Type: Research Article

Abstract: In this work, angular displacement and angular velocity of the elbow during continuous flexion and extension movement are estimated using three different models, with Surface Electromyography (SEMG) time domain parameters as model inputs, and the results are compared to select the model that gives the most accurate results. Surface Electromyography (SEMG) is recorded using surface electrodes placed on the biceps brachii muscles during continuous flexion and extension of the elbow joint. SEMG recording is done with elbow angle changing at different angular velocities. The obtained SEMG signals are segmented into 250-millisecond duration windows using disjoint windowing technique. Two time-domain parameters, …Integrated Electromyography (IEMG) and Zero crossing (ZC) are derived from each windowed SEMG signals. The obtained value of IEMG and ZC are fed as the inputs to the Multiple Input Multiple Output (MIMO) model for the estimation of elbow angular displacement and elbow angular velocity. In this work three Multiple Input Multiple Output (MIMO) nonlinear black box model are developed using a Nonlinear Auto Regressive with eXogenous inputs (NARX) structure: (1) Multi-Layered Perceptron Neural Network (MLPNN) model based on NARX input, (2) Elman neural network model based on NARX input and (3) Adaptive Neuro-Fuzzy Inference System (ANFIS) model based on NARX input. The results obtained from the three different models are compared using statistical parameters like regression coefficient and root mean square error (RSME). Based on this comparison the paper proposes that the estimation of elbow kinematics using ANFIS NARX model gives more accurate results when compared with Elman NARX model and Multi-Layered Perceptron Neural Network (MLPNN) NARX model. Show more

Keywords: Surface Electromyography, time domain features, NARX structure, Multi-Layered Perceptron Neural Network (MLPNN), Elman Neural Network (ENN), Adaptive Neuro-Fuzzy Inference System (ANFIS), elbow joint angular displacement, elbow angular velocity, Integrated EMG (IEMG), Zero crossing (ZC)

DOI: 10.3233/JIFS-16070

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 791-805, 2017

Authors: Li, Weijiang | Qi, Jing | Yu, Zhengtao | Li, Dongjun

Article Type: Research Article

Abstract: Nowadays, we are living in an information overload age. A tremendous amount of information has been produced on the Internet, how to find the interesting information is the main goal of recommendation system research. However, the most of current traditional recommendation algorithms (such as Collaborative filtering) are suffering from flowing difficulties: (i) The traditional recommendation system assume that users are independent and identically distributed; this assumption fails to consider the social relation and connection between users, which is not consistent with the social relations in our real world. (ii) Although there are some recommendation system research began to focus on …the trust relationship between users, trust information is also very sparse. This leads to most of datasets only contains very little information about the user’s relationship. In this paper, we propose an innovative method that integrated users’ trust propagation and singular value decomposition into recommendation Algorithm to improve the quality of the recommendation effectively and efficiently. We performed our experiments on two real data sets respectively, the public domain Epinions.com and Filemtrust.com. The experimental results show that our method has a better outperform. Show more

Keywords: Recommendation system, trust propagation, singular value decomposition

DOI: 10.3233/JIFS-16073

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 807-816, 2017

Authors: Rashidi, Farzan

Article Type: Research Article

Abstract: Engine idle speed control problem has significant effects on fuel consumption, combustion stability and pollutions produced in urban traffics. In this paper, a Multi-Agent adaptive Critic based NeuroFuzzy Controller (MACNFC) for engine idle speed is presented to improve fuel efficiency, reduce emissions, and increase disturbance rejection capability while preventing the engine from stalling. The proposed MACNFC consists of a neurofuzzy controller, a learning mechanism and a set of fuzzy critic agents. It is assumed that each critic has been well designed to serve a particular objective. The role of the critics is to evaluate the controller performance in terms of …satisfactory achievements of the control objectives through evaluation of plant output and provide appropriate continues reinforcement signals. If these signals become zero, it means that the critics are satisfied by the performance of the controller from their own point of view. If deviation of signals from zero become larger, it shows the more stress and more dissatisfaction. The reinforcement signals provided by critics contribute collaboratively to update neurofuzzy controller parameters via the learning mechanism for achieving predefined criteria and goals. The controller should modify its characteristics so that all reinforcement signals are decreased and consequently all critics are satisfied. To illustrate the effectiveness of the proposed method some simulations are given. Obtained results show that proposed method not only maintains the engine speed as close as possible to a desired value in the presence of various disturbances, but also improves fuel consumption for large production volumes of engine operating in different idle speed regimes. Show more

Keywords: Idle speed control, engine model, fuel consumption, disturbance rejection, neurofuzzy controller, critic agent

DOI: 10.3233/JIFS-16083

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 817-829, 2017

Authors: Qin, Keyun | Yang, Jilin | Liu, Zhicai

Article Type: Research Article

Abstract: Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool for dealing with uncertainties. This paper is devoted to the discussion of fuzzy soft set based approximate reasoning. First, based on fuzzy implication operators, the notion of fuzzy soft implication relation between fuzzy soft sets is introduced. The composition method of fuzzy soft implication relations is provided. Second, Triple I methods for fuzzy soft modus ponens (FSMP)and fuzzy soft modus tollens (FSMT) are investigated. Computational formulas for FSMP and FSMT with respect to left-continuous t-norms and its residual implication are presented. At last, the reversibility properties …of Triple I methods are analyzed. Show more

Keywords: Fuzzy set, soft set, fuzzy soft implication relation, triple I method, left-continuous t-norm

DOI: 10.3233/JIFS-16088

Citation: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 831-839, 2017