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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Feng, Kan | Yang, Ke | Shi, Haopeng | Jia, Najuan | Zhang, Pingjuan
Article Type: Research Article
Abstract: Overload service in the communication network of smart substation will cause congestion, resulting in low overload service throughput, high congestion rate and long congestion control time in the average smart substation. A congestion control method for overloaded services in smart substations with high concurrent users is proposed. According to the characteristics of overload service request of smart substation, the mathematical model of the algorithm is defined by describing the overload service request of smart substation on the basis of network topology model. Combined with the wavelength rotation strategy, the congestion rate of overloaded services in smart substations is reduced, and …the throughput rate of overloaded services in smart substations is improved. Considering the factors of high concurrent users, by judging and feeding back the congestion of the overloaded services of smart substations, the congestion control of overloaded services of smart substations under high concurrent users is realized. The experimental results show that the proposed method has better effect and scalability in the congestion control of the overloaded service of the smart substation, and can effectively shorten the congestion control time of the overloaded service of the smart substation. Show more
Keywords: High concurrent users, smart substation, wavelength rotation strategy, overload service, congestion control, D_WA algorithm, overload service congestion model, congestion degree value, interest packet forwarding rate
DOI: 10.3233/JIFS-224276
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3895-3906, 2024
Authors: Wu, Zhongyi | Liu, Weidong | Zheng, Weijie
Article Type: Research Article
Abstract: This research presents a novel model for optimizing process information in manufacturing steps through the utilization of Process Constituent Elements (PCE), with the aim of enhancing the effectiveness of product process information design. To achieve this objective, a systematic analysis is conducted on six dimensions: input, output, resources, value-adding activities, environment, and process control and inspection content. In addition, specific attributes of PCE are investigated, and an improved FP-growth algorithm is employed to extract the optimized structural expressions of typical PCE, thus determining specific expression requirements. The PCE and their attribute relationships are organized into modular mapping rules, resulting in …an optimized representation structure based on a polychromatic set approach. The effectiveness of this approach is quantitatively assessed by developing a comprehensive quality indicator evaluation system for process information and using a fuzzy comprehensive evaluation model for analysis. Show more
Keywords: Process constituent elements, process design, optimization, data mining, process quality, fuzzy evaluation
DOI: 10.3233/JIFS-231198
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3907-3932, 2024
Authors: Siva Senthil, D. | Sivarani, T.S.
Article Type: Research Article
Abstract: Detecting abnormal events in surveillance involves identifying unexpected behavior through video analysis. This involves recognizing patterns or deviations from normal behavior and taking actions to mitigate potential risks. However, the distribution of data can change over time, leading to concept drift, which can make it challenging to accurately detect abnormal events. To address this issue, a new approach using a global density network (GDN) has been proposed. The GDN allows for more efficient identification of object distributions in surveillance videos, leading to improved accuracy in abnormal event detection. The proposed method combines features extracted by a backbone network with a …global density joined network (GDJN), which refines density features using dilated convolutional networks. A multistage long short-term memory (LSTM) network is then used to classify abnormal events. The experimental results are conducted on two datasets, UMN and UCSD Ped2. The achieved F1 scores were 93.42 and 94.46 respectively, with corresponding AUC values of 93.5 and 94.8. Show more
Keywords: Keywords:Video analysis, abnormal event detection, GDN, GDJN, LSTM, deep learning
DOI: 10.3233/JIFS-232177
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3933-3944, 2024
Authors: Li, Weidong | Fan, Jinsheng | Li, Zhenying | Wang, Chisheng | Zhang, Xuehai | Duan, Jinlong
Article Type: Research Article
Abstract: The accuracy of predicting river-suspended sediment concentration (SSC) is crucial for evaluating the functional lifespan of reservoirs, analyzing river geomorphological evolution, and assessing riverbed stability. In this study, we aim to develop new models for SSC prediction at two hydrological stations near Puerto Rico, USA, by integrating the bacterial foraging optimization algorithm and adaptive neural fuzzy inference network (ANFIS). The models comprise ANFIS with grid partition (ANFIS-GP), ANFIS with subtractive clustering (ANFIS-SC), and ANFIS with fuzzy c-means clustering (ANFIS-FCM). Additionally, we employ an artificial neural network (ANN) and the sediment rating curve (SRC) for predicting daily series data of flow …discharge-suspended sediment concentration (SSC). Different scenarios are considered based on varying input and output variables, leading to predictions for four distinct scenarios. At the Rio Valenciano Station, the MRSE values for ANFIS-BFO, ANFIS-FCM, ANFIS-GP, ANFIS-SC, ANN, and SRC are 2.2172, 2.5389, 2.6627, 2.7549, 2.7994, and 3.7882, respectively. For the Quebrada Blanca Station, the MRSE values for ANFIS-BFO, ANFIS-FCM, ANFIS-SC, ANFIS-GP, ANN, and SRC are 0.8295, 0.8664, 0.8964, 0.9110, 0.9684, and 1.6742, respectively. It can be inferred that ANFIS-BFO exhibits superior prediction results compared to all other models. Furthermore, ANFIS-SC and ANFIS-FCM demonstrate slightly better prediction performance than ANFIS-GP. In comparison to ANN, ANFIS-GP, ANFIS-SC, and ANFIS-FCM exhibit slightly superior prediction performance. Show more
Keywords: ANFIS, ANN, bacterial foraging optimization algorithm, modeling, suspended sediment
DOI: 10.3233/JIFS-232277
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3945-3961, 2024
Authors: Sahapudeen, Farjana Farvin | Krishna Mohan, S.
Article Type: Research Article
Abstract: Patients with lung cancer can only be diagnosed and treated surgically. Early detection of lung cancer through medical imaging could save numerous lives. Adding advanced techniques to conventional tests that offer high accuracy in diagnosing lung cancer is essential. U-Net has excelled in diversified tasks involving the segmentation of medical image datasets. A significant challenge remains in determining the ideal combination of hyper parameters for designing an optimized U-Net for detailed image segmentation. In our work, we suggested a technique for automatically generating evolutionary U-Nets to detect and segregate lung cancer anomalies. We used three distinct datasets, namely the LIDC-IRDC …Dataset, Luna 16 Dataset, and Kaggle Dataset, for training the proposed work on lung images. Our results, examined with six distinct evaluation criteria used for medical image segmentation, consistently demonstrated the highest performance. More specifically, the GA-UNet outperforms conventional approaches in terms of an impressive accuracy rate of 97.5% and a Dice similarity coefficient (DSC) of 92.3%. Show more
Keywords: Genetic programming, deep learning, attention blocks, residual network, UNets, optimized U-Net
DOI: 10.3233/JIFS-233006
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3963-3974, 2024
Authors: Demirtaş, Naime | Dalkılıç, Orhan | Riaz, Muhammad | Al-Quran, Ashraf
Article Type: Research Article
Abstract: Introduction: The soft set theory has drawn the attention of many researchers, particularly for dealing with uncertainty in decision-making problems. Despite its remarkable advantages, the soft set theory has only been used to tackle decision-making problems that aim to choose the best option. However, there exist different forms of decision-making problems that involve different forms of uncertainty. Methods: In this study, we present various algorithms based on the soft set theory in order to handle the cases where one has different uncertainty forms in decision-making problems. Some new concepts such as object code, personal object code, parameter significance …weight and new distance measures have been introduced to the literature for the construction of these algorithms. Furthermore, we show the application results of those algorithms and provide several examples. Results and Conclusions: As a result, a comparison among the application results of the algorithms implies that the best objects might not always yield the most efficient outcomes. Show more
Keywords: Soft set, D-metric space, parametric distance, algorithm, decision making
DOI: 10.3233/JIFS-234481
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3975-3985, 2024
Authors: Li, Zhixin | Liu, Hao | Huan, Zhan | Liang, Jiuzhen
Article Type: Research Article
Abstract: Human activity recognition (HAR) plays a crucial role in remotely monitoring the health of the elderly. Human annotation is time-consuming and expensive, especially for abstract sensor data. Contrastive learning can extract robust features from weakly annotated data to promote the development of sensor-based HAR. However, current research mainly focuses on the exploration of data augmentation methods and pre-trained models, disregarding the impact of data quality on label effort for fine-tuning. This paper proposes a novel active contrastive coding model that focuses on using an active query strategy to evenly select small, high-quality samples in downstream tasks to complete the update …of the pre-trained model. The proposed uncertainty-based balanced query strategy mines the most indistinguishable hard samples according to the data posterior probability in the unlabeled sample pool, and imposes class balance constraints to ensure equilibrium in the labeled sample pool. Extensive experiments have shown that the proposed method consistently outperforms several state-of-the-art baselines on four mainstream HAR benchmark datasets (UCI, WISDM, MotionSense, and USCHAD). With approximately only 10% labeled samples, our method achieves impressive F1-scores of 98.54%, 99.34%, 98.46%, and 87.74%, respectively. Show more
Keywords: Contrastive learning, active learning, human activity recognition, hard sample mining, mobile medical system
DOI: 10.3233/JIFS-234804
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 3987-3999, 2024
Authors: Zeng, Zengpei
Article Type: Research Article
Abstract: Visual communication design, as a type of artistic and three-dimensional design behavior, helps to spread visual behavior by designing it. The rapid development of new media technology has provided rich channels and vast space for visual communication design, and the elements and modes of visual communication design are constantly being updated, better promoting the development of visual communication technology. The Teaching quality evaluation of visual communication design based on the cultivation of innovative and creative abilities based on the cultivation of innovative and creative abilities is a multiple-attribute decision-making (MADM). In this paper, some calculating laws on IVIFSs, Hamacher sum, …Hamacher product are introduced, and the induced interval-valued intuitionistic fuzzy Hamacher interactive hybrid weighted averaging (I-IVIFHIHWA) operator is proposed based on the interval-valued intuitionistic fuzzy Hamacher interactive hybrid weighted averaging (IVIFHIHWA) operator and induced ordered weighted averaging (I-OWA) operator. Meanwhile, some ideal properties of I-IVIFHIHWA operator are studied. Then, the I-IVIFHIHWA operator is employed to cope with the MADM under IVIFSs. Finally, an example for Teaching quality evaluation of visual communication design based on the cultivation of innovative and creative abilities is employed to test the I-IVIFHIHWA operator. Thus, the main research aim of this paper is concluded as follows: [1 ] the I-IVIFHIHWA operator is constructed based on classical IOWA operator; [2 ] the I-IVIFHIHWA operator is put forward to cope with the MADM under IVIFSs; [3 ] an empirical example for Teaching quality evaluation of visual communication design based on the cultivation of innovative and creative abilities has been put forward to show the I-IVIFHIHWA operator. Show more
Keywords: Multiple-attribute decision-making (madm), interval-valued intuitionistic fuzzy sets (ivifss), i-ivifhihwa operator, quality evaluation
DOI: 10.3233/JIFS-235960
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 4001-4013, 2024
Authors: Li, Fang | Li, Pengfei
Article Type: Research Article
Abstract: Currently, the digital economy continues to deepen its development, and it has become a consensus among all sectors as the direction of global future development. Digital finance, as a fleet in the wave of digital economy, is rapidly heading towards the sunny shore of benefiting the public and serving entities driven by the digital technology engine. Xinwang Bank is a fast boat in the digital finance fleet, always adhering to the principle of technology, building an open platform, and actively promoting the construction of an open, shared, and secure digital credit ecosystem from three levels: institutional, industry, and ecological, to …assist in the development of the digital economy. The digital commercial bank security evaluation is a classical multiple attribute group decision making (MAGDM) problems. Recently, the Evaluation based on Distance from Average Solution (EDAS) method has been employed to manage MAGDM issues. The intuitionistic fuzzy sets (IFSs) are used as a tool for portraying uncertain information during the digital commercial bank security evaluation. In this paper, the intuitionistic fuzzy nunmber EDAS (IFN-EDAS) method is cultivated to manage the MAGDM based on Hamming distance and Euclidean distance under IFSs. In the end, a numerical case study for digital commercial bank security evaluation is supplied to validate the proposed method. The main contributions of this paper are outlined: (1) the EDAS method has been extended to IFSs based on Hamming distance and Euclidean distance; (2) the CRITIC method is used to derive weight based on Hamming distance and Euclidean distance under IFSs. (3) the IFN-EDAS method based on Hamming distance and Euclidean distance is founded to manage the MAGDM based on the Hamming distance and Euclidean distance under IFSs; (4) a numerical case study for digital commercial bank security evaluation and some comparative analysis is supplied to validate the proposed method. Show more
Keywords: Multiple attribute group decision making (MAGDM), intuitionistic fuzzy sets (IFSs), EDAS method, CRITIC method, digital commercial bank security evaluation
DOI: 10.3233/JIFS-236058
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 4015-4027, 2024
Authors: Zhang, Bin
Article Type: Research Article
Abstract: In recent years, e-commerce live streaming and short video marketing supported by big data and artificial intelligence technology have flourished, adding new sales models for e-commerce products to mass consumption, promoting the multimodal development of the e-commerce industry, giving new impetus and connotation to economic and social development, and being an effective means to achieve high-quality development in the new era. The effectiveness evaluation of short video marketing strategies is a multiple-attribute group decision-making (MAGDM) problem. Recently, the Exponential TODIM technique and Combined Compromise Solution (CoCoSo) technique has been employed to cope with MAGDM issues. The interval-valued Pythagorean fuzzy sets …(IVPFSs) are employed as a tool for characterizing uncertain information during the effectiveness evaluation of short video marketing strategies. In this paper, the interval-valued Pythagorean fuzzy Exponential TODIM (ExpTODIM) (IVPF-ExpTODIM-CoCoSo) technique is constructed to solve the MAGDM under IVPFSs. In the end, a numerical case study for effectiveness evaluation of short video marketing strategies is given to validate the proposed technique. The main contributions of this paper are outlined: (1) the Exp-TODIM and CoCoSo technique has been extended to IVPFSs; (2) Information Entropy is employed to manage the weight values under IVPFSs. (3) the IVPF-ExpTODIM-CoCoSo technique is founded to implement the MAGDM under IVPFSs; (4) a numerical case study for effectiveness evaluation of short video marketing strategies and some comparative analysis is supplied to verify the IVPF-ExpTODIM-CoCoSo technique. Show more
Keywords: Multiple attribute group decision making (MAGDM), interval-valued Pythagorean fuzzy sets (IVPFSs), Exponential TODIM (ExpTODIM) technique, CoCoSo technique, effectiveness evaluation
DOI: 10.3233/JIFS-236767
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 2, pp. 4029-4042, 2024
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