Journal of Intelligent & Fuzzy Systems - Volume 45, issue 6

Authors: Nguyen, Vy Duong Kim | Do, Phuc

Article Type: Research Article

Abstract: People will increasingly get expedited and diverse means of accessing news as societies progress. Furthermore, there is a noticeable increase in the prevalence of incorrect and misleading information. Our research is motivated by the significant concerns regarding the detrimental impacts of disinformation on the general public, political stability, and trust in the media. The scarcity of Vietnamese-language datasets can be attributed to the predominant focus of false news detection studies on datasets only in English. Detection investigations of fake news have predominantly relied on supervised machine learning algorithms, which possess notable limitations when confronted with unclassified news articles that are …either authentic or untrue. The utilization of Knowledge Graphs (KG) and Graph Convolutional Networks (GCN) holds promise in addressing the constraints of supervised machine learning algorithms. To address these problems, we propose an approach that integrates KG)into the procedure for detecting fake news. We utilize the Vietnamese Fake News Detection dataset (VFND-vietnamese-fake-news), comprising authentic and deceptive news articles from reputable Vietnamese newspapers such as vnexpress, tuoitre, and have been collected from 2018 to 2023. News articles are only labeled as real or fake after experiencing independent verification. The Glove embedding (Global Vectors for Word Representation) is employed to establish a knowledge network for the given dataset. This knowledge graph’s construction is accomplished using the Word Mover’s Distance (WMD) algorithm in conjunction with the K-nearest neighbor approach; GCN approach and the input KG train models to discern between real and fake news. With labeling half of the input dataset, the experimental findings indicate a notable level of accuracy, reaching up to 85%. Our research holds significant importance in identifying fake news, particularly within the context of the Vietnamese language. Show more

Keywords: Fake news detection, graph convolutional network, semi-supervised, K-nearest neighbor, word mover’s distance

DOI: 10.3233/JIFS-233260

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11107-11119, 2023

Authors: Bo, Lina

Article Type: Research Article

Abstract: In college education, English is a required course for every college student, and undergraduate colleges have certain requirements for college English proficiency. At the same time, English is directly related to its learning, so improving the quality of college English teaching (CET) is very important. Teaching quality is a key indicator for measuring the effectiveness of English teaching. Learning quality evaluation is a very complex process that involves many factors, such as evaluation indicators, evaluation methods, etc. Therefore, establishing an objective and scientific English quality evaluation system is a challenging issue. The CET quality evaluation is a MAGDM. Then, the …TODIM and VIKOR was used to set up MAGDM. The interval-valued intuitionistic fuzzy sets (IVIFSs) are employed as a tool for depicting uncertain information during the CET quality evaluation. In this study, the entropy and score values are employed to establish the objective weights. Then, an integrated interval-valued intuitionistic fuzzy TODIM-VIKOR (IVIF-TODIM-VIKOR) is developed to cope with the MAGDM problem. An illustrative example for CET quality evaluation and some comparative analysis are developed to demonstrate the validity and reliability of IVIF-TODIM-VIKOR method. Show more

Keywords: Multiple attribute group decision making (MAGDM), 2 interval-valued intuitionistic fuzzy sets (IVIFSs), TODIM, VIKOR, CET quality evaluation

DOI: 10.3233/JIFS-234149

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11121-11133, 2023

Authors: Sreelatha, Tammineni | Maheswari, M. | Ravi, G. | Manikanda Devarajan, N. | Arun, M.

Article Type: Research Article

Abstract: Data compression is the ancestor of image compression, which uses fewer bits to represent the same picture. It is categorised as lossy or lossless depending on the quality required. In a lossless compression situation, no information is lost during the decompression process. Data loss is possible with the lossy technique since it is not reversible. In an effort to boost compression efficiency while maintaining a high xiv reconstruction quality of picture, near lossless approaches have evolved. The medical pictures consist of a large number of items, each of which may be described in detail and utilised for a variety of …purposes. The clinically relevant item in 2D medical pictures is referred to as the Region of Interest (ROI), whereas in 3D images, it is referred to as the Volume of Interest (VOI). Saving energy is crucial since it is one of the most limited resources in these networks. However, DTN has an additional difficulty since communication between nodes is maintained so long as they are in physical proximity to one another. However, because to the nodes’ mobility, this may not be long enough to provide the necessary multimedia data transmission. Wireless networks are susceptible to security assaults, and traditional security solutions are computationally demanding, making them unsuitable for networks that constantly need to recharge their batteries. All of these are reasons for tackling the problems of multimedia data processing and transmission via wireless networks in this dissertation. With this in mind, it has been attempted to investigate low-overhead and safe multimedia data compression as a solution to the issue that energy-constrained nodes in these networks limit complex multimedia processing while keeping at least basic security features. LZW-OMCA compression using the Octagonal Multimedia Compression Algorithm is part of the suggested method. The purpose of this is to improve the compression ratio. The proposed approach uses a little bit of crypt to compress data, which makes the data unreadable to anybody except the intended receiver, hence providing network security. The previous proposed works analysed the performance of several compression algorithms applied to multimedia material. Performance assessment utilising MSE, SSIM, and other metrics are used to show the pros and cons of each segment. Show more

Keywords: Octagonal multimedia compression algorithm, data compression, LZW-OMCA compression, MSE, SSIM

DOI: 10.3233/JIFS-234314

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11135-11147, 2023

Authors: Shi, Jianzhong

Article Type: Research Article

Abstract: Compared with type-2 fuzzy sets, the secondary membership degree of interval type-3 fuzzy sets is an interval rather than crisp value, which makes interval type-3 fuzzy sets can obtain more degree of freedoms. This article studies an interval type-3 fuzzy PID controller based on interval type-3 fuzz sets. The framework of interval type-3 fuzzy PID controller is identical with type-2 fuzzy PID controller, but it contains more adjustment controller parameters and its type reduction procedure is more complex. In this paper, type reduction of interval type-3 fuzzy sets is derived from general type-2 fuzzy sets represented by α-plane and a …direct NT type reduction algorithm is applied. The control effects of interval type-3 fuzzy PID controller are firstly tested by 2 nonlinear plants, the simulation results show that interval type-3 fuzzy PID controller has better control performance indexes than PID controller, type-1 fuzzy PID controller, interval type-2 fuzzy PID controller and general type-2 fuzzy PID controller. Furthermore, the interval type-3 fuzzy PID controller will be applied in rated voltage control of solid oxide fuel cells (SOFC) power plant. The output voltage control of SOFC is quite challenging because of the strong nonlinearity, limited fuel flow, and rapid variation of the load disturbance. The simulation results demonstrate the advantages and robustness of proposed interval type-3 fuzzy PID controller. Show more

Keywords: Type-2 fuzzy sets, interval type-3 fuzzy sets, interval type-3 fuzzy control system, type reduction, solid oxide fuel cells

DOI: 10.3233/JIFS-231460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11149-11162, 2023

Authors: Chandra, Harshit | Bajpai, Shrish | Alam, Monauwer | Chandel, Vishal Singh | Pandey, Amit Kumar | Pandey, Digvijay

Article Type: Research Article

Abstract: Hyperspectral (HS) images contain rich spatial and spectral information. Due to its large size, it is difficult to store, process, analyze, or transmit the critical information contained in it. The compression of hyperspectral images is inevitable. Many transform based Hyper Spectral Image Compression Algorithms (HSICAs) have been proposed in the past that work for both lossy and lossless compression processes. The transform based HSICA uses linked lists or dedicated markers or array structure to keep track of significant and insignificant sets or coefficients of a transformed HS image. However, these algorithms either suffered from low coding efficiency, high memory requirements, …or high coding complexity. This work proposes a transform based HSICA using a curvelet transform to improve the directional elements and the ability to represent edges and other singularities along curves. The proposed HSICA aims to provide superior quality compressed HS images by representing HS images at different scales and directions and to achieve a high compression ratio. Experimental results show that the proposed algorithm has a low coding memory requirement with a 2% to 5% increase in coding gain compared to the other state of art compression algorithms. Show more

Keywords: Complexity theory, curvelet transform, hyperspectral image, hyperspectral image compression, transform coding

DOI: 10.3233/JIFS-231684

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11163-11187, 2023

Authors: Yang, Lei | Gao, Ge

Article Type: Research Article

Abstract: As China’s economic and social development enters a new stage, the role of innovation and entrepreneurship is becoming increasingly prominent, and its importance is also being emphasized. As the main force for future employment and national economic construction, college students naturally become the new force for innovation and entrepreneurship. Therefore, it is imperative for universities to carry out in-depth innovation and entrepreneurship education (IEE) for college students. Then, with the continuous development of social development needs and the professional growth needs of college students, the “innovation and entrepreneurship” education for college students should also be adjusted in a timely manner …in terms of educational concepts, models, and methods. The IEE environment evaluation in universities under the background of “ Double Innovation” is looked as multiple attribute decision-making (MADM). In this paper, the information entropy model is employed to calculate the objective weight of the evaluation attribute. Then, interval-valued intuitionistic fuzzy Combined Compromise Solution (IVIF-CoCoSo) is built based on the Hamming distance and Euclid distance to cope with MADM under interval-valued intuitionistic fuzzy sets (IVIFSs). The new MADM method is proposed for IEE environment evaluation in universities under the background of “ Double Innovation”. Finally, the IVIF-CoCoSo approach is compared with existing methods to verify the effectiveness of IVIF-CoCoSo algorithm. The main contributions of this constructed paper are: (1) the IVIF-CoCoSo method is built based on the Hamming distance and Euclid distance. (2) the information entropy model is employed to calculate the objective weight of the evaluation attribute. (3) The new MADM method is proposed for IEE environment evaluation in universities under the background of “ Double Innovation” based on IVIF-CoCoSo. (4) The IVIF-CoCoSo model is compared with existing methods to verify the effectiveness of the IVIF-CoCoSo algorithm. Show more

Keywords: Multi-attribute decision making (MADM), interval-valued intuitionistic fuzzy sets (IVIFSs), IVIF-CoCoSo method, information entropy method; IEE environment

DOI: 10.3233/JIFS-232151

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11189-11201, 2023

Authors: Abiyev, Rahib H. | Aliev, Rafik | Kaynak, Okyay

Article Type: Research Article

Abstract: In this paper, a novel Z-number based Fuzzy Neural Network (Z-FNN) based on the integration of Z-valued fuzzy logic and neural networks is proposed. Z-valued fuzzy rule base is presented and its inference process is described using interpolative approximate reasoning. Accordingly, the structure of the Z-FNN is proposed using a distance measure and interpolative approximate reasoning scheme. Based on presented architecture the learning algorithm of Z-FNN is designed. The updating of the unknown parameters of the network is carried out using Genetic Algorithms (GA). The proposed Z-FNN system is utilized for dynamic plant identification. The effectiveness of Z-FNN has been …tested by comparing its performance with the performances of other fuzzy systems available in the literature. The proposed approach has been proven to be a suitable alternative for the identification of nonlinear systems characterized by uncertain and imprecise information. Show more

Keywords: Fuzzy neural networks, Z-number, fuzzy rule, learning

DOI: 10.3233/JIFS-232741

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11203-11216, 2023

Authors: Ashwin Shenoy, M. | Thillaiarasu, N.

Article Type: Research Article

Abstract: Automated identification of human activities remains a complex endeavor, particularly in unique settings like temple environments. This study focuses on employing machine learning and deep learning techniques to analyze human activities for intelligent temple surveillance. However, due to the scarcity of standardized datasets tailored for temple surveillance, there is a need for specialized data. In response, this research introduces a pioneering dataset featuring Eight distinct classes of human activities, predominantly centered on hand gestures and body postures. To identify the most effective solution for Human Activity Recognition (HAR), a comprehensive ablation study is conducted, involving a variety of conventional machine …learning and deep learning models. By integrating YOLOv4’s robust object detection capabilities with ConvLSTM’s ability to model both spatial and temporal dependencies in spatio-temporal data, the approach becomes capable of recognizing and understanding human activities in sequences of images or video frames. Notably, the proposed YOLOv4-ConvLSTM approach emerges as the optimal choice, showcasing a remarkable accuracy of 93.68%. This outcome underscores the suitability of the outlined methodology for diverse HAR applications in temple environments. Show more

Keywords: Dataset, machine learning, deep learning, YOLOv4, ConvLSTM, Human Activity Recognition

DOI: 10.3233/JIFS-233919

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11217-11232, 2023

Authors: Zhou, Jiwen

Article Type: Research Article

Abstract: With the proposal of the “Double First Class” construction concept in Chinese universities, cultivating high-quality talents has become the main direction of university education. At present, local universities in China are actively adapting to the changes of the times, taking the construction of the Double First Class as an opportunity, continuously adjusting and deepening the reform of the double innovation and innovation talent cultivation mode, further improving the curriculum system, increasing investment in professional practical teaching, stimulating students’ enthusiasm for innovation and entrepreneurship (IAE), and focusing on improving students’ comprehensive abilities, achieving significant results in talent cultivation. The “Entrepreneurship and …Entrepreneurship” career ability evaluation of local college students could be considered as multiple attribute decision-making (MADM). Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method was employed to deal with MADM. The triangular fuzzy neutrosophic sets (TFNSs) are employed as a better tool for expressing uncertain information during the “Entrepreneurship and Entrepreneurship” career ability evaluation of local college students. In this paper, the triangular fuzzy neutrosophic number CoCoSo (TFNN-CoCoSo) based on the Hamming distance and Euclid distance is constructed to cope with the MADM under TFNSs. The information entropy method is employed to compute the weight values based on the Hamming distance and Euclid distance under TFNSs. Finally, a numerical example of “Entrepreneurship and Entrepreneurship” career ability evaluation of local college students is constructed and some decision comparisons are constructed to verify the TFNN-CoCoSo method. Show more

Keywords: Multiple attribute decision making (MADM), TFNSs, CoCoSo model, information entropy, career education quality evaluation

DOI: 10.3233/JIFS-234138

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11233-11246, 2023

Authors: Tan, Ruipu | Chen, Chong | Zhang, Wende | Yang, Lehua | Ma, Hangfei

Article Type: Research Article

Abstract: With the rising incidences of emergencies, it is both challenging and meaningful to study how to make decisions quickly and take appropriate measures to control the spread and evolution of the situation. However, most current emergency decision-making focuses on mathematical model construction, whereas fuzzy decision-making is biased towards subjective assumptions, which are both insufficient for practicability. We studied the intelligent acquisition of single-valued neutrosophic numbers based on emotional tendency analysis and applied them to emergency decision-making. First, Python programming technology was used to crawl, preprocess, and statistically analyse the network comment data of emergencies, and a quantised single-value neutrosophic number …was obtained. Second, the attribute values, represented as neutrosophic numbers, were uniformly converted into cloud droplets, and the weight of the attribute values was objectively determined according to the digital feature entropy in the cloud droplets. Subsequently, a case-based reasoning approach was used to calculate the combined weighted similarity between the alternatives and ideal solution (target case) to obtain a ranking of the alternatives and historical cases in the case base that best matches the target case. Finally, a typhoon disaster assessment was considered as an example to verify the feasibility and effectiveness of the proposed method, and the advantages of the proposed method were emphasised through multi-aspect and multi-angle comparative analyses. The relevant research can be used for public opinion monitoring during emergencies and emergency handling. Show more

Keywords: Emergency decision-making, intelligent acquisition of single-valued neutrosophic numbers, emotional tendency analysis, cloud model, case-based reasoning (CBR)

DOI: 10.3233/JIFS-231039

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 6, pp. 11247-11268, 2023