Journal of Intelligent & Fuzzy Systems - Volume 36, issue 6

Authors: Wang, Rongrong | Han, Shengwei

Article Type: Research Article

Abstract: Fuzzy posets can be regarded as a generalization of classical posets. Many concepts and results in posets can be generalized to fuzzy posets. In order to further improve the fuzzy poset theory, in this paper, we shall introduce the concept of prime (distributive) fuzzy posets which can be seen as the correspondence of prime (distributive) posets in fuzzy setting. First, we consider the extensions of fuzzy ideals in a fuzzy poset. Then by the extensions of fuzzy ideals, we give a characterization for prime (distributive) fuzzy posets, that is, a fuzzy poset X is prime (distributive) if and only if …all extensions of normal fuzzy ideals of X are Frink (strong) fuzzy ideals. This paper generalizes the work of Halas in posets into fuzzy posets. Show more

Keywords: Fuzzy poset, extension of fuzzy ideal, prime fuzzy poset, distributive fuzzy poset

DOI: 10.3233/JIFS-181352

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5513-5520, 2019

Authors: Guan, Hao | An, Zhiyong

Article Type: Research Article

Abstract:  Visual tracking is a popular research topic in computer vision. In this paper, we propose a novel tracking framework which leverages stable and adaptive memories of target appearance for robust tracking where the target undergoes significant appearance change as well as background clutter. First, we define a stable-adaptive memory network which exploits the embedding of the target patch in the first video frame, named as "reliable memory", as well as the embeddings of patches collected online that are referred as "adaptive memories". Through the fusion of these two types of memories, a good balance between stability and plasticity can be …made. During tracking, the network searches the candidate which has the highest similarity with the memorized patterns as the tracking result. Second, we train an online detector to re-detect the target in case of tracking failure and update the memory network. By virtue of the proposed mechanism, our tracker can handle the drift problem well and is able to track the object in challenging situations robustly. Experimental results on challenging benchmark video sequences show that the proposed tracking framework achieves state-of-the-art tracking performance with high accuracy and robustness. Show more

Keywords: Visual tracking, convolutional network, online learning, object detection

DOI: 10.3233/JIFS-181362

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5521-5531, 2019

Authors: Wang, Yupin | Sun, Shurong

Article Type: Research Article

Abstract: This paper reports the investigation of the existence and uniqueness of solution to Cauchy problems for a class of nonlinear fuzzy fractional differential equations with the Riemann-Liouville H -derivative. Further, E q -Ulam type stability results are presented by using direct analysis methods. Finally, several numerical simulations are provided to verify the correctness and effectiveness of the main results.

Keywords: Fuzzy fractional differential equation, initial value problem, strongly generalized Hukuhara differentiability, fractional hyperbolic function, Ulam type stability

DOI: 10.3233/JIFS-181369

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5533-5545, 2019

Authors: Zheng, Xinghua | Ma, Zhengming | Che, Hanjian | Li, Lei

Article Type: Research Article

Abstract:  At present, manifold learning is mainly applied to dimensionality reduction. However, from viewpoint of dimensionality reduction, manifold learning algorithms are only local feature preserving algorithms. For example, Local Linear Embedding is local linear preserving, Local Tangent Space Alignment is local homeomorphic preserving and Laplacian Eigenmap is local similarity preserving. The community of dimensionality reduction is now pursuing the algorithms which can preserve both local and global features of data during dimensionality reduction. In this paper, a new algorithm of dimensionality reduction, called Hilbert-Schmidt Independence Criterion Regularized Manifold Learning (HSIC-ML for short), is proposed, in which HSIC between the high dimensional …data and the dimension-reduced data is added as a regularization term to the objective functions of manifold learning. The addition of HSIC regularization term makes HSIC-ML capable of preserving both local and global features during dimensionality reduction. HSIC is a criterion measuring the statistical dependence between two data sets and has been widely applied to machine learning in recent years. However, since HSIC was first proposed around 2005, there seems to have not been applied directly to dimensionality reduction, not applied as a regularization term either. The proposed HSIC-ML may be the first try in this respect. The experimental results presented in this paper show that the manifold learning with HSIC regularization performs better than that without HSIC regularization. Show more

Keywords: Dimensionality reduction, manifold learning, Hilbert-Schmidt Independence Criterion, regularization

DOI: 10.3233/JIFS-181379

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5547-5558, 2019

Authors: Ercan, Sinan | Altinok, Hifsi | Altin, Yavuz

Article Type: Research Article

Abstract: Dual number algebra is a powerful mathematical tool for the kinematic and dynamic analysis of spatial mechanisms. The algebra of dual numbers has been originally conceived by Clifford [1 ], but its first applications to mechanics are due to Kotelnikov [2 ] and Study [3 ]. In this paper, we focus on summability of sequences of dual numbers. We introduce the concepts of strongly N θ p ( D ) -summability and lacunary statistical convergence for sequences of dual numbers. We give some certain properties of these concepts and some inclusion relations.

Keywords: Statistical convergence, lacunary sequence, dual numbers

DOI: 10.3233/JIFS-181415

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5559-5564, 2019

Authors: Wang, Jun | Zhang, Runtong | Li, Li | Zhu, Xiaomin | Shang, Xiaopu

Article Type: Research Article

Abstract: The recently proposed q -rung orthopair fuzzy set (q -ROFS) is an effective tool for handling fuzziness and uncertainty in the process of multi-attribute group decision making (MAGDM). Considering that in most MAGDM problems, not only decision makers’ quantitative evaluation information but also their qualitative assessment opinions should be taken into account, this paper proposes a concept of q -rung orthopair uncertain linguistic sets (q -ROULSs) by combining q -ROFSs with uncertain linguistic variables (ULVs). The proposed q -ROULSs parallel to intuitionistic uncertain linguistic sets (IULSs) and Pythagorean uncertain linguistic sets (PULSs), but provide more freedom for decision makers to …express their evaluation information. Afterwards, we propose operational laws and a comparison law for q -ROULSs. To effectively aggregate q -rung orthopair uncertain linguistic information, we extend the Muirhead mean (MM) operator to q -ROULSs and propose a family of q -rung orthopair uncertain linguistic Muirhead mean operators. The prominent advantage of the proposed operators is that the interrelationship among any numbers of input arguments can be captured. In addition, some desirable properties and special cases of the proposed operators are studied. Moreover, we propose a new method to MAGDM problems based on the proposed operators within q -rung orthopair uncertain linguistic context. Finally, we conduct a numerical experiment to demonstrate the validity and superiorities of the proposed method. Show more

Keywords: q-rung orthopair fuzzy set, q-rung orthopair uncertain linguistic set, Muirhead mean, q-rung orthopair uncertain linguistic Muirhead mean, multi-attribute group decision making

DOI: 10.3233/JIFS-181425

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5565-5581, 2019

Authors: Prasertpong, Rukchart | Siripitukdet, Manoj

Article Type: Research Article

Abstract: The Mareay’s rough set has been regarded as an approximation processing model in an approximation space induced by an arbitrary binary relation on the single universe. This is an effective mathematical tool for dealing with uncertain knowledge and vagueness in data for the single universe. Based on this induced notion, we firstly establish and verify two new classes, called a successor class and a core of a successor class induced by an arbitrary binary relation between two universes. Then we propose a generalization of the Mareay’s rough set in an approximation space based on cores of successor classes induced by …an arbitrary binary relation between two universes, with a corresponding example. Some interesting algebraic properties of the new approximation processing model are investigated. We develop the use of the novel rough set in a semigroup under a preorder and compatible relation. We establish the notions of rough semigroups, rough ideals and rough completely prime ideals. Then we provide sufficient conditions of rough semigroups, rough ideals and rough completely prime ideals. Under homomorphism problems in semigroups, the relationship between the rough semigroup (resp. rough ideal and rough completely prime ideal) and the homomorphic image of the rough semigroup (resp. rough ideal and rough completely prime ideal) is demonstrated. Show more

Keywords: Rough sets, approximation spaces, semigroups, rough semigroups, rough ideals, rough completely prime ideals, binary relations, preorder relations, compatible relations.

DOI: 10.3233/JIFS-181435

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5583-5596, 2019

Authors: Kirişci, Murat

Article Type: Research Article

Abstract: In this paper, we study the concept of Fibonacci statistical convergence on intuitionisitic fuzzy normed space. We define the Fibonacci statistically Cauchy sequences with respect to an intuitionisitic fuzzy normed space and introduce the Fibonacci statistical completenes with respect to an intuitionisitic fuzzy normed space.

Keywords: intuitionistic fuzzy normed space, Fibonacci numbers, statistical convergenc, Fibonacci statistical Cauchy, statistical completeness

DOI: 10.3233/JIFS-181455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5597-5604, 2019

Authors: Farooq, Muhammad | Mahmood, Tariq | Khan, Asghar | Izhar, Muhammad | Davvaz, Bijan

Article Type: Research Article

Abstract: Fuzzy set theory and Rough set theory are two useful mathematical tools for dealing with uncertainty and provides a general mathematical framework for dealing with uncertainty. In this paper, we introduce the notions of hyperideals of hyperquantales. The notions of (upper, lower) rough hyperideals of hyperquantales are given. Furthermore the notions of fuzzy hyperideals of hyperquantales are introduce and investigate their properties. Then, we introduce the concept of prime fuzzy hyperideals and establish relationships between these hyperideals and prime fuzzy hyperideals of hyperquantales. Finally we define rough upper (lower) fuzzy hyperideals of hyperquantales and investigate several related properties.

Keywords: Rough set, fuzzy set, hyperquantale, fuzzy hyperideal, rough fuzzy hyperideal.

DOI: 10.3233/JIFS-181460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5605-5615, 2019

Authors: Souidi, Mohammed El Habib | Siam, Abderrahim | Pei, Zhaoyi

Article Type: Research Article

Abstract: Coalition formation algorithms based on organizational modeling frameworks can be considered as the earliest approaches applied to the Pursuit-Evasion problem. In this paper we have based on an extension of AGRMF (Agent-Group-Role-Membership-Function) organizational model with a limited overlapping degree of the pursuit groups to allow the coalition of the pursuers. The limited overlapping provides certain equilibrium between the pursuit groups through the elimination of negative externality problem. Regarding the path planning we have based on Markov Decision Process principles (MDP) resolved via the application of value iteration algorithm. To avoid the obstacles encountered, we have based on the recent Reward …Bug Algorithm (RBA). This algorithm is based on the payoff returned by the application of MDP. The simulation results reflect the improvement provided by this new approach in relation to recent methods applied to this kind of problems. Show more

Keywords: Pursuit-evasion, organizational modeling frameworks, overlapping coalition, Markov decision process

DOI: 10.3233/JIFS-181471

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5617-5629, 2019