Journal of Intelligent & Fuzzy Systems - Volume 39, issue 1

Authors: Alzubi, Jafar A. | Jain, Rachna | Kathuria, Abhishek | Khandelwal, Anjali | Saxena, Anmol | Singh, Anubhav

Article Type: Research Article

Abstract: The paper presents a Collaborative Adversarial Network (CAN) model for paraphrase identification, which is a collaborative network holding generator that is pitted against an adversarial network called discriminator. There has been tremendous research work and countless examinations done on sentence similarity demonstration. Learning and identifying the constant highlights, specifically in various areas and domains is the main focus of paraphrase identification. It Involves the capture of regular highlights between two sentences and the community-oriented learning upon traditional ill-disposed and adversarial learning for common feature extraction. The model outperforms the MaLSTM model, which is the baseline model, and also proves to …be comparable to many of the state-of-the-art techniques. Show more

Keywords: Paraphrase identification, text classification, adversarial networks, LSTM, NLP

DOI: 10.3233/JIFS-191933

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1021-1032, 2020

Authors: Hua, Shaoyang | Wang, Congqing | Wu, Xuewei

Article Type: Research Article

Abstract: Neural decoding is a technology to analyze intentions produced by neural activities, which has important applications in military, medical, entertainment and so on. As a typical application, decoding electromyogram (EMG) signals into corresponding gestures is an important content. In order to improve the accuracy of EMG signals recognition, researchers often extract effective features from EMG signals and classify gestures by constructing a reasonable classifier. However, because of the stochasticity of the signals, this method is not robust enough. This paper proposes a convolutional neural network (CNN) based on feature fusion, which can automatically learn and classify features from time-domain(TD) and …frequency-domain(FD). To make full use of information, two fusion methods are used and compared. Experiments show that the proposed fusion methods are superior to the traditional algorithm for both normal people and amputees, and have better performance compared with CNN method using only one kind of information. Show more

Keywords: Convolutional neural network (CNN), gestures recognition, neural decoding, surface electromyogram (sEMG)

DOI: 10.3233/JIFS-191964

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1033-1044, 2020

Authors: Zhou, Shuang | Zhang, Jianguo | Zhang, Lei | You, Lingfei

Article Type: Research Article

Abstract: In traditional mechanism reliability analysis, probability theory or statistical approaches are employed. However, these methods cannot be used under lack of data and great epistemic uncertainty. In this paper, an advanced mechanism reliability analysis method is put forward based on uncertain measure. To satisfy the subadditivity of epistemic uncertainties, a novel uncertainty quantification method based on uncertainty theory is proposed for mechanism reliability analysis. Then, a point kinematic reliability analysis method combined with uncertain measure is presented to calculate the kinematic uncertainty reliability of motion mechanism at each time instant. Three models are developed for estimating kinematic uncertainty reliability. Furthermore, …first-order Taylor series expansion is used to solve nonlinear limit state functions. A new kinematic uncertainty reliability index (KURI) is presented based on normal uncertainty distribution. Finally, by applying the proposed method to a numerical experiment, the trend of uncertainty reliability was found to be consistent with the traditional method. The two practical engineering applications show that the presented method are more reasonable compared with the classical approaches when the information of design parameters is insufficient. Show more

Keywords: Uncertainty quantification, mechanism reliability, reliability index, uncertainty theory, belief reliability

DOI: 10.3233/JIFS-191970

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1045-1059, 2020

Authors: Santos, Laércio Ives | D’Angelo, Marcos Flávio Silveira Vasconcelos | Cosme, Luciana Balieiro | de Oliveira, Heveraldo Rodrigues | Mendes, João Batista | Ekel, Petr Ya.

Article Type: Research Article

Abstract: Falls in the elderly are a public health problem because this population tends to have a longer recovery time and consequently longer hospital beds. Studies show that 84% of falls in hospital rooms occur near the bed, that led to strategies to prevent falls in the elderly population have been studied. In this context, this paper presents a schema for the detection and emission of bed exit alerts in the elderly. This schema uses signals derived from RFID sensors processed by a model based on Intelligent Swarm and Fuzzy Sets. The main contribution of this study is the use of …a Membership Windows that reduces the effects of missclassification of other strategies. The proposed work evaluated a data set containing 14 elderly aged between 66 and 86 years divided into two rooms. The results show that the presented approach improves the precision and recall in environments with greater uncertainty of classification. Show more

Keywords: Bed exit alarms, elderly care, intelligent swarm, fuzzy sets

DOI: 10.3233/JIFS-191971

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1061-1072, 2020

Authors: Rosyida, Isnaini | Widodo, | Indrati, Ch. Rini | Indriati, Diari

Article Type: Research Article

Abstract: We use the notion of fuzzy chromatic number (FCN) of fuzzy graphs based on fuzzy independent vertex sets introduced in 2015. Let G ˜ 1 be a path fuzzy graph and G ˜ 2 be any fuzzy graphs where their vertex sets are disjoint. Let G ˜ = G ˜ 1 □ G ˜ 2 be a cartesian product of G ˜ 1 and G ˜ 2 …. In this paper, we construct formula for FCN of G ˜ 1 □ G ˜ 2 and verify connection between maximum of FCN of both fuzzy graphs and FCN of their cartesian product. Also, we create an algorithm to determine FCN of the cartesian product according to the properties obtained. The last two statements show novelties of the present work. Evaluation of the algorithm is presented in the experimental results. Show more

Keywords: Fuzzy chromatic number, cartesian product, path, fuzzy graph, algorithm

DOI: 10.3233/JIFS-191982

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1073-1080, 2020

Authors: Ahmad, Ali | Koam, Ali N.A.

Article Type: Research Article

Abstract: The structures of many molecules such as dendrimers, alkanes and acyclic molecules are like trees. Rooted trees have wide applications in chemical graph theory such as enumeration and encoding of chemical structures. Structures of chemical compounds can be systematized in form of chemical and empirical formulae through mathematical means. Chemists have a long tradition of using atomic valences (vertex degrees) to find molecular structures graphically. In structural chemistry number of graph applications exist. This paper reflects the work on the following indices: first general Zagreb index M α , general Randić connectivity index R α , general …sum-connectivity index χ α , atom-bond connectivity index ABC , geometric-arithmetic index GA , fourth atom-bond connectivity index ABC 4 , fifth geometric-arithmetic index GA 5 , hyper-Zagreb index HM  (G ), first multiple Zagreb index PM 1  (G ), second multiple Zagreb index PM 2  (G ) and Zagreb polynomials M 1  (G , x ) , M 1  (G , x ) for line graph of complete m -ary tree. Show more

Keywords: Topological indices, line graph, complete m-ary trees

DOI: 10.3233/JIFS-191992

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1081-1088, 2020

Authors: Dai, Songsong

Article Type: Research Article

Abstract: The symmetric implicational methods for fuzzy reasoning characterizes the solution B * (A * ) of the formula (A  → 1 B ) → 2  (A *  → 1 B * ) for the fuzzy modus ponens (fuzzy modus tollens), where →1 and →2 are two different implications. In this study, we provide a predicate formal representation of the solution for the symmetric implicational methods based on the LΠ formal logic system, including detailed logic proofs. We bring the symmetric implicational methods within a logical framework and provide a sound logic foundation for the symmetric implicational methods of fuzzy reasoning.

Keywords: Fuzzy reasoning, symmetric implicational method, LΠ logic

DOI: 10.3233/JIFS-191998

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1089-1095, 2020

Authors: Mújica-Vargas, Dante

Article Type: Research Article

Abstract: In brain medical imaging, magnetic resonance is an important and effective means to support the computer aided diagnosis. Notwithstanding, inherent conditions such as atypical information, artifacts and vaguely delimited boundaries between existing tissues can hinder the segmentation task. A popular method to carry out this process is through Fuzzy C-Means algorithm, as well as its variants. These include the Intuitionistic Fuzzy C-Means algorithm, which is found suitable for brain magnetic resonance image segmentation, since it incorporates the advantage of intuitionistic fuzzy sets theory to handle the uncertainty. Most clustering algorithms depend of customized hand-crafted features as well as an appropriate …initialization process; this last aspect is a mandatory pre-requisite for convergence of the algorithm. In order to develop the brain image segmentation, in this paper we enhance the Intuitionistic Fuzzy C-Means performance by means of Robust Statistics. Explicitly, a non-parametric German-McClure Redescending M-Estimator is used at the initialization and clustering stages, it behaves such as a robust location estimator when the centroid vector is computed, and as a weighting when the membership matrix is updated. The fusion of both paradigms allows us to propose a clustering algorithm that develops efficiently the segmentation of magnetic resonance images, with the important merit of reduce the iteration required to converge. The robustness and effectiveness of this proposal is verified by experiments on simulated and real brain images. Show more

Keywords: Brain MRI image segmentation, intuitionistic fuzzy C-means, German-McClure redescending M-estimator

DOI: 10.3233/JIFS-192005

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1097-1108, 2020

Authors: Ding, Jianhua | Zhang, Zhiqiang

Article Type: Research Article

Abstract: Bayesian statistical inference is an important method of mathematical statistics in which both sample information and prior information are employed. Traditionally, it is often assumed that the sample observations from the population are observed precisely and characterized by crisp values. However, in many cases, the sample observations are collected in an imprecise way and characterized by uncertain values. In this paper, based on uncertain theory, we propose three kinds of uncertain Bayesian statistical inference including Bayesian point estimation, Bayesian interval estimation and Bayesian hypothesis test. Some numerical examples of uncertain Bayesian inference are presented to illustrate the proposed methods.

Keywords: Bayes’ theorem, uncertain variables, uncertain theory, uncertainty Bayesian statistical inference

DOI: 10.3233/JIFS-192014

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1109-1117, 2020

Authors: Song, Chenyang | Xu, Zeshui | Zhang, Yixin

Article Type: Research Article

Abstract: The k-Nearest Neighbor (k-NN) is one of the simplest intelligent algorithms in the field of pattern recognition and classification. The increasing complexity of practical applications brings more uncertainty and fuzziness. In this paper, we take advantage of the Dempster-Shafer evidence theory (D-S evidence theory) and the hesitant fuzzy set (HFS) in depicting uncertain preference and information, and develop the evidence k-Nearest Neighbor (Ek-NN) under the hesitant fuzzy environment. The fruit fly optimization algorithm (FOA) is adopted to determine the most appropriate value of k in Ek-NN, and a specific implementation process of the optimized Ek-NN based on FOA is also …provided. Moreover, two numerical examples about classification problems are presented to evaluate the performance of the proposed method. Comparative analysis and sensitivity analysis are further conducted to illustrate the advantages of the optimized Ek-NN based on FOA under the hesitant fuzzy environment. Show more

Keywords: k-Nearest neighbor, dempster-shafer evidence theory, hesitant fuzzy set, fruit fly optimization algorithm

DOI: 10.3233/JIFS-192026

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 1, pp. 1119-1129, 2020