Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Chang, Furong | Zhang, Bofeng | Zhao, Yue | Wu, Songxian | Zou, Guobing | Niu, Sen

Article Type: Research Article

Abstract: A bipartite network is a special kind of complex network that consists of two different types of nodes with edges existing only between the different node types. There are numerous real-world examples of bipartite networks, such as scientific collaboration networks and film-actor networks, among many others. Detecting the community structure of bipartite networks not only contributes to a deeper understanding of their hidden structure, but also lays the foundation for research into the personalized recommendation technology. Most existing algorithms, however, only focus on the detection of non-overlapping community structures while ignoring overlapping community structures. In this study, we developed a …micro-bipartite network model, Bi-EgoNet along with an algorithm called Overlapping Community Detection using Bi-EgoNet (OCDBEN). This algorithm first extracts the sub-bi-community set from each Bi-EgoNet using similarity within the bipartite network and then constructs a global community structure by merging the sub-bi-communities using the double-merger strategy. We evaluated the OCDBEN algorithm with several synthetic and real-world bipartite networks and compared it with existing state-of-the-art algorithms. The experimental results demonstrated that OCDBEN outperformed existing algorithms in both accuracy and effectiveness. Show more

Keywords: Overlapping community, bipartite networks, complex network

DOI: 10.3233/JIFS-190320

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Tao, Liang | Siqi, Qian | Zhaochao, Meng | Gao Feng, Xie

Article Type: Research Article

Abstract: With the construction of large-scale wind turbines, how to reduce the operation and maintenance costs has become an urgent problem to be solved. In this paper, by extracting the actual operation data of the wind turbine in Supervisory Control and Data Acquisition (SCADA) system, the Bidirectional Recurrent Neural Networks (BRNN) is used to establish the wind turbine operation prediction model. By eliminating abnormal data points caused by accidental factors through box diagram, the fault risk threshold of wind turbine components is optimized. Then, based on the residual between the actual value and the measured value of the large sliding window, …the early fault warning is realized according to Wright criterion. Finally, the model proposed in this paper is applied to the actual wind turbine, which proves the reliability and accuracy of the method. Show more

Keywords: BRNN, box-plot, large sliding window, Letts’criterion, early fault warning

DOI: 10.3233/JIFS-190642

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: Vanitha, V. | Krishnan, P.

Article Type: Research Article

Abstract: An e-learning system offering a personalised learning path will be vastly appealing to the learners. Adaptive techniques when employed in e-learning can sustain the interest and motivation of the learners and help them to complete the enrolled courses successfully. In addition, it would improve their performance and thus, enhance the overall learning experience. Personalisation takes into consideration the characteristics of the individual learner and the diversity in his/her needs. The main challenge is finding a match between these individual characteristics and the sequence of the learning content. It is a complex task to implement as it involves selection of the …appropriate material from a vast amount of the available learning materials. It is a challenge to perform this process manually as it requires both technical savvy and pedagogical skills. In this paper, a stigmergy model is proposed, which was applied to build a customised learning path. The aim was to provide personalisation that satisfied the needs of an individual in a widely heterogeneous e-learning environment. Compared with the traditional teaching method, this tailored learning path, generated using the proposed approach, shows promise and was found to enhance the performance of the learners. Show more

Keywords: Learning path, learning content sequence, personalised E-learning, ant colony optimisation, curriculum sequencing

DOI: 10.3233/JIFS-190349

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Maheshwari, Karan | Joseph Raj, Alex Noel | Mahesh, Vijayalakshmi G.V. | Zhuang, Zhemin | Rufus, Elizabeth | Shivakumara, Palaiahnakote | Naik, Ganesh R.

Article Type: Research Article

Abstract: In today’s world, there have been lots of unique optical character recognition systems. One drawback of these systems is that they cannot work effectively on natural scene images where the text is not only subject to different orientations, lightning, and background but can be of multiple scripts as well. The paper, proposes a state of the art algorithm to detect texts of different dialects and orientations in an image. The whole text detection pipeline is divided into two parts. First, extraction of probable text regions in an image is performed based on a combination of statistical filters, which results in …a high recall. These regions are then fed to an Artificial Neural Networks (ANN) based classifier which classifies whether the proposed regions are text or non-text, which increases the overall precision. The validity of the algorithm is verified on the most challenging bilingual text detection dataset MSRA-TD500 and a promising F1 score of 0.67 is reported. Show more

Keywords: Text detection, entropy and variance filters, invariant moments, artificial neural networks, bilingual text detector

DOI: 10.3233/JIFS-190339

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Ziari, Shokrollah | Bica, Alexandru Mihai

Article Type: Research Article

Abstract: In this paper, an iterative numerical method has been developed to solve nonlinear fuzzy Volterra integral equations based on three-point quadrature formula. The error estimation of the method is obtained based on Lipschitz condition and in order to confirm the yielded theoretical results, we perform the iterative method on some numerical examples.

Keywords: Nonlinear fuzzy Volterra-Hammerstein integral equations, Iterative numerical method, L-Lipschitz fuzzy functions

DOI: 10.3233/JIFS-190149

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2019

Authors: M, Parimala | M, Karthika | Jafari, Saeid | Smarandache, Florentin | El-Atik, A.A.

Article Type: Research Article

Abstract:  Neutrosophic topological space is an extension of intuitionistic topological space and each triplet set in neutrosophic topological space contains membership, indeterminacy and non-membership values. Connected set in intuitionistic topological set contains membership and non-membership values and inderterminacy have not discussed in that set. This motivates the authors to propose this novel concept called neutrosophic αψ -connectedness. So we introduce the new notion of neutrosophic αψ -connectedness in neutrosophic topological spaces and investigate some properties of neutrosophic αψ -connectedness between sets and subsets of two sets. Some properties of this concept presented with numerical quantities to prove the non-existence.

Keywords: Neutrosophic closed set, Neutrosophic αψ-closed set, Neutrosophic αψ-connectedness between neutrosophic sets

DOI: 10.3233/JIFS-179453

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-, 2019

Authors: Rashid, Junaid | Adnan Shah, Syed Muhammad | Irtaza, Aun

Article Type: Research Article

Abstract: Medical and health text documents pose a challenge for data handling and retrieving the relevant and meaningful documents. Automatically retrieval of significant knowledge with a better understanding of medical and health documents is a challenging task. One popular approach for thematically understand the medical and health text documents and finding the topics from these documents is topic modeling. In this research, we propose a novel topic modeling approach Fuzzy k-means latent semantic analysis (FKLSA) by using the fuzzy clustering. Our method generates local and global term frequencies through the bag of words (BOW) model. Principal component analysis is used for …removing high dimensionality negative impact on global term weighting. Previous work shows that in medical and health documents redundancy issue has a negative impact on the quality of text mining. Therefore, the main achievement of FKLSA is the handling of the redundancy issue in medical and text documents and discover semantically more precise topics. FKLSA is socially utilized for finding the themes from medical and health text corpus. These topics are further used for text classification and clustering tasks in text mining. Experimental results show that FKLSA performs better than LDA and RedLDA for redundant corpora. FKLSA’s time performance is also stable with an increase in number of topics and thus better than LDA and LSA on a big twitter heath dataset. Quantitative evaluations of the real-world dataset for health and medical documents show that FKLSA gives a higher performance as compared to state-of-the-art topic models like Latent Dirichlet allocation and Latent semantic analysis. Show more

Keywords: Topic modeling, bag-of-words, term weighting, fuzzy k-means, principal component analysis

DOI: 10.3233/JIFS-182776

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2019

Authors: Oztaysi, Başar | Cevik Onar, Sezi | Kahraman, Cengiz

Article Type: Research Article

Abstract: The education system is very important for the society. In this study, we try to define and prioritize the requirements of an n online platform which can be used as a source for collecting feedback from stakeholders of an educating system. The involved stakeholders are the course content generators, teachers, students and families of the students. In the application three experts used linguistic terms to evaluate the performance indicators and the weights are calculated using Pythagorean Fuzzy Analytic Hierarch Process (AHP) Method.

Keywords: System design, fuzzy sets, pythagorean fuzzy sets, analytic hierarchy process

DOI: 10.3233/JIFS-179450

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: de Jesús Rubio, José | Garcia, Enrique | Ochoa, Genaro | Elias, Israel | Cruz, David Ricardo | Balcazar, Ricardo | Lopez, Jesus | Novoa, Juan Francisco

Article Type: Research Article

Abstract:  An unscented Kalman filter can be applied for the experimental learning of the solar dryer for oranges drying and the greenhouse for crop growth to know better the processes and to improve their performances. The contributions of this document are: a) an unscented Kalman filter is designed for the learning of nonlinear functions, b) the unscented Kalman filter is applied for the experimental learning of the two mentioned processes.

Keywords: Unscented Kalman filter, greenhouse, solar dryer, experimental learning

DOI: 10.3233/JIFS-190216

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Pei, Xinjun | Yu, Long | Tian, Shengwei | Wang, Huanhuan | Peng, Yongfang

Article Type: Research Article

Abstract: Combining natural language processing technology, image analysis technology and malware detection technology, a novel Android malware detection method, named BIHAD (an improved IndRNN and attention-treated DenseNet-based pipeline model), is proposed in this paper. First, in order to describe the behavior of Android malware, multiple features are used to construct a more stable discriminant method. Second, the embedding technology is introduced to map all behavior information into a vector space, which implements the extraction of the joint embedded information of semantics and images. Third, an improved Independently Recurrent Neural Network (IndRNN) is used to extract valuable texture information from the original …values of the gray image, and effectively utilized the long distance information contained in the gray image. Finally, Hierarchical Attention Dense Convolutional Network (HADenseNet) is used to ensure the maximization of information flow between layers in the network, improving the utilization of semantic distribution and spatial context information. Especially, Hierarchical Attention can enhance the representational ability for key features. The comparison of the BIHAD model with several existing malware detection methods indicated a significant improvement in F-score achieved by the BIHAD. Show more

Keywords: Dense convolutional network, Independently Recurrent Neural Network, hierarchical attention, neural joint model, android malware detection

DOI: 10.3233/JIFS-190888

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019