Journal of Intelligent & Fuzzy Systems - Volume 46, issue 3

Authors: Kang, Zhonghui

Article Type: Research Article

Abstract: Intangible cultural heritage can be said to be an important component of tourism resources. With the rapid development of society in today’s era, tourism development and intangible cultural heritage protection have gradually attracted attention from Chinese society, and in recent years, it has attracted high attention from relevant departments of the Chinese government. Tourism development has a “dual” impact on the protection of intangible cultural heritage, with both positive and negative impacts. The risk assessment of intangible cultural heritage tourism development is a MAGDM problems. Recently, the TODIM and GRA technique has been employed to manage MAGDM issues. The interval-valued …Pythagorean fuzzy sets (IVPFSs) are employed as a tool for characterizing uncertain information during the risk assessment of intangible cultural heritage tourism development. In this paper, the interval-valued Pythagorean fuzzy TODIM-GRA (IVPF-TODIM-GRA) technique is construct to manage the MAGDM under IVPFSs. Finally, a numerical case study for risk assessment of intangible cultural heritage tourism development is employed to validate the proposed technique. Show more

Keywords: Multiple-attribute group decision-making (MAGDM), interval-valued pythagorean fuzzy sets (IVPFSs), TODIM technique, GRA technique, intangible cultural heritage tourism development

DOI: 10.3233/JIFS-236937

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5811-5824, 2024

Authors: Chang, Zaibin | Mao, Lingling

Article Type: Research Article

Abstract: Fuzzy complementary β-neighborhoods (FCNs) are used to find information relevant to the target in data mining. Based on FCNs, there are six types of covering-based multigranulation fuzzy rough set (CMFRS) models have been constructed, which can be used to deal with the problem of multi-criteria information systems. These CMFRS models are calculated by set representations. However, it is time-consuming and error-prone when set representations are used to compute these CMFRS models in a large multi-criteria information system. Hence, it is important to present a novel method to compute them quickly, which is our motivation for this paper. In this paper, …we present the matrix representations of six types of CMFRS models on FCNs. Firstly, some new matrices and matrix operations are given in a multi-criteria information system. Then, matrix representations of three types of optimistic CMFRSs on FCNs are proposed. Moreover, matrix approaches are also used for computing three types of pessimistic CMFRSs on FCNs. Finally, some experiments are presented to show the effectiveness of our approaches. Show more

Keywords: Fuzzy rough set, covering, matrix, multigranulation

DOI: 10.3233/JIFS-224323

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5825-5839, 2024

Authors: Wang, Yong | Jiang, Zhipeng | Wang, Yihan | Yang, Chunyu | Zou, Liang

Article Type: Research Article

Abstract: The mining belt conveyor is one of the most important modules in coal mine, whose safety always be threatened by the foreign objects. Although the traditional target detection methods achieve promising results in various computer vision tasks, the performance heavily depends on sufficient labelled data. However, in real-world production scenario, it is difficult to acquire huge number of images with foreign objects. The obtained datasets lacking of capacity and diversity are not suitable for training supervised learning-based foreign objects detection models. To address this concern, we propose a novel method for detecting the foreign objects on the surface of underground …coal conveyor belt via improved GANomaly. The proposed foreign objects detection method employs generative adversarial networks (GAN) with attention gate to capture the distribution of normality in both high-dimensional image space and low-dimensional latent vector space. Only the normal images without foreign object are utilized to adversarially train the proposed network, including a U-shape generator to reconstruct the input image and a discriminator to classify real images from reconstructed ones. Then the combination of the difference between the input and generated images as well as the difference between latent representations are utilized as the anomaly score to evaluate whether the input image contain foreign objects. Experimental results over 707 images from real-world industrial scenarios demonstrate that the proposed method achieves an area under the receiver operating characteristic curve of 0.864 and is superior to the previous GAN-based anomaly detection methods. Show more

Keywords: Generative adversarial networks, anomaly detection, attention, industrial scenarios, mining belt conveyor

DOI: 10.3233/JIFS-230647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5841-5851, 2024

Authors: Li, Keyuan | Zhang, Qinghua | Xie, Qin | Huang, Shuaishuai

Article Type: Research Article

Abstract: Medical image classification is an essential task in the fields of computer-aided diagnosis and medical image analysis. In recent years, researchers have made extensive work on medical image classification by computer vision techniques. However, most of the current work is based on deep learning methods, which still suffer from expensive hardware resources, long time consuming and a lot of parameters to be optimized. In this paper, a multi-granularity ensemble algorithm for medical image classification based on broad learning system is proposed, which is an end-to-end lightweight model. On the one hand, the proposed method is designed to address the problem …of weak image feature learning ability of broad learning system. The convolution module with fixed weights based on transfer learning is introduced as a feature extractor to extract fusion features of medical images. On the other hand, the multi-granularity ensemble framework is proposed, which learn the fusion features of medical images from fine-grained to coarse-grained respectively, and the prediction results at different granularity levels are integrated by ensemble learning. In this way, the bottom local features can be sufficiently considered, while the global features can also be taken into account. The experimental results show that on the MedMNIST dataset (containing 10 sub-datasets), the proposed method can shorten the training time by tens of times while having similar accuracy to deep convolutional neural networks. On the ChestXRay2017 dataset, the proposed method can achieve an accuracy of 92.5%, and the training time is also significantly better than other methods. Show more

Keywords: Broad learning system(BLS), multi-granularity, ensemble learning, medical image classification

DOI: 10.3233/JIFS-235725

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5853-5867, 2024

Authors: Shen, Hanhan | Zhang, Fu | Pan, Xiaodong | Sun, Xiaofei

Article Type: Research Article

Abstract: As significant carriers of the application of fuzzy set theories, fuzzy systems have been widely used in many fields. However, selecting fuzzifications, fuzzy reasoning engines, and defuzzifications is subjective for Mamdani fuzzy systems, and the fuzzy rule of Takagi-Sugeno-Kang fuzzy systems is less of a linguistic interpretation. Regarding these shortcomings, this paper proposes a fuzzy system based on vague partitions processing information directly from the fuzzy rule base, in which fuzzy rules have explicit semantics. Firstly, the n -dimensional vague partition of the n -dimensional universe is defined based on 1-dimensional vague partitions and the aggregation function, and its properties …are discussed. Based on these, we design the new fuzzy system, and investigate its approximation properties which is the theoretical guarantee for applying the fuzzy system. As an application, we combine the fuzzy system with PID control system to deal with autonomous vehicle path tracking control problems. A series of experiments are constructed, and experimental results indicate that the fuzzy system based on vague partitions makes the fuzzy PID control system strong robustness, and has obvious advantages compared with other traditional fuzzy systems for path tracking control problems. Show more

Keywords: Fuzzy systems, vague partitions, aggregation functions, fuzzy PID control, path tracking

DOI: 10.3233/JIFS-232903

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5869-5892, 2024

Authors: Wang, Chia-Hung | Ye, Qing | Cai, Jiongbiao | Suo, Yifan | Lin, Shengming | Yuan, Jinchen | Wu, Xiaojing

Article Type: Research Article

Abstract: The multi-feature and imbalanced nature of network data has always been a challenge to be overcome in the field of network intrusion detection. The redundant features in data could reduce the overall quality of network data and the accuracy of detection models, because imbalance could lead to a decrease in the detection rate for minority classes. To improve the detection accuracy for imbalanced intrusion data, we develop a data-driven integrated detection method, which utilizes Recursive Feature Elimination (RFE) for feature selection, and screens out features that are conducive to model recognition for improving the overall quality of data analysis. In …this work, we also apply the Adaptive Synthetic Sampling (ADASYN) method to generate the input data close to the original dataset, which aims to eliminate the data imbalance in the studied intrusion detection model. Besides, a novel VGG-ResNet classification algorithm is also proposed via integrating the convolutional block with the output feature map size of 128 from the Visual Geometry Group 16 (VGG16) of the deep learning algorithm and the residual block with output feature map size of 256 from the Residual Network 18 (ResNet18). Based on the numerical results conducted on the well-known NSL-KDD dataset and UNSW-NB15 dataset, it illustrates that our method can achieve the accuracy rates of 86.31% and 82.56% in those two test datasets, respectively. Moreover, it can be found that the present algorithm can achieve a better accuracy and performance in the experiments of comparing our method with several existing algorithms proposed in the recent three years. Show more

Keywords: Artificial Intelligence, Classification Algorithms, Deep Learning Algorithms, Network Intrusion Detection, Multi-class Pattern Classification

DOI: 10.3233/JIFS-234402

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5893-5910, 2024

Authors: Sundar, R. | Purushotham Reddy, M. | Sethy, Abhisek | Selvam, K. | Abidin, Shafiqul | Chakrabarti, Prasun | Nagarjuna, Valeti | Ravuri, Ananda | Selvan, P.

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-237948

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5911-5925, 2024

Authors: Wang, Kai | Bai, Yameng

Article Type: Research Article

Abstract: With the rapid development of science and technology, the flow of information has become more convenient, and society has entered the era of knowledge economy. In this era, technological innovation capability is becoming increasingly important and has become an important weapon for enterprises to survive in fierce competition, especially for technology-based small and medium-sized enterprises. Nowadays, technology-based small and medium-sized enterprises have developed many technological innovation achievements through continuous technological innovation, and have created a large number of high-tech products and services. Technological innovation has been proven to effectively improve the core competitiveness and economic benefits of technology-based small and …medium-sized enterprises. Therefore, evaluating the technological innovation capabilities of technology-based small and medium-sized enterprises has both theoretical and practical significance. The enterprise technological innovation capability evaluation from a low carbon perspective could be deemed as the multiple attribute group decision making (MAGDM) problem. Recently, the evaluation based on distance from average solution (EDAS) technique and cosine similarity measure (CSM) technique has been employed to manage MAGDM issues. The spherical fuzzy sets (SFSs) are used as an efficient tool for portraying uncertain information during the enterprise technological innovation capability evaluation from a low carbon perspective. In this paper, the spherical fuzzy number EDAS based on the CSM (SFN-CSM-EDAS) technique is cultivated to manage the MAGDM under SFSs. Finally, a numerical study for enterprise technological innovation capability evaluation from a low carbon perspective is supplied to validate the proposed technique. The main contributions of this paper are outlined: (1) the EDAS and CSM technique was extended to SFSs; (2) the CRITIC technique is used to derive weight based on CSM technique under SFSs. (3) the SFN-CSM-EDAS technique is founded to manage the MAGDM under SFSs; (4) a numerical case study for enterprise technological innovation capability evaluation from a low carbon perspective and some comparative analysis is supplied to validate the SFN-CSM-EDAS technique. Show more

Keywords: Multiple attribute group decision making (MAGDM), spherical fuzzy sets (SFSs), EDAS technique, CRITIC technique, enterprise technological innovation capability evaluation

DOI: 10.3233/JIFS-236778

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5927-5940, 2024

Authors: Yang, Guangfu | Xiao, Chunyun

Article Type: Research Article

Abstract: The employment of college graduates is related to the overall situation of China’s social development, and the difficulty of employment has become a social problem that cannot be ignored. Through the analysis of the current situation of employment, it is found that the lack of employment guidance in colleges and universities and the lack of employment concept of college students are important factors for the difficulty of college students’ employment, and college counselors play an irreplaceable role in college students’ career planning. Based on the characteristics of college counselors’ work, the paper constructs a career planning evaluation system, hoping to …provide new ideas for counselors’ employment guidance. The college students’ career planning evaluation is a multiple attributes group decision making (MAGDM). Recently, the TODIM and GRA technique has been employed to manage MAGDM. The probabilistic hesitant fuzzy sets (PHFSs) are employed as a useful tool for depicting uncertain information during the college students’ career planning evaluation. In this paper, the probabilistic hesitant fuzzy TODIM-GRA (PHF-TODIM-GRA) technique is built to manage the MAGDM under PHFSs. At last, the numerical example for college students’ career planning evaluation is employed to show the PHF-TODIM-GRA technique. The main contribution of this paper is outlined: (1) the TODIM technique based on GRA technique has been extended to PHFSs based on CRITIC technique; (2) the CRITIC technique is employed to derive weight values under PHFSs. (3) the PHF-TODIM-GRA technique is founded to manage the MAGDM under PHFSs; (4) a numerical case study for college students’ career planning evaluation and some comparative analysis is supplied to validate the proposed PHF-TODIM-GRA technique. Show more

Keywords: Multiple attributes group decision making (MAGDM), probabilistic hesitant fuzzy sets (PHFSs), TODIM technique, GRA technique, career planning evaluation

DOI: 10.3233/JIFS-232606

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5941-5956, 2024

Authors: Yin, Bingquan | Ouyang, Shaojuan | Hou, Yali | Ma, Jizhao

Article Type: Research Article

Abstract: Innovation and entrepreneurship education is an important component of cultivating the comprehensive quality of college students and an important force in promoting economic and social development. Meanwhile, due to changes in the social environment and economic structure, traditional university education is no longer able to meet the needs of contemporary society. Therefore, innovation and reform of innovation and entrepreneurship education for college students are urgent. Innovation and entrepreneurship education for college students needs to keep up with the times, constantly update concepts and techniques, in order to adapt to the ever-changing social and economic environment. The innovation and entrepreneurship education …evaluation in the application-oriented vocational colleges is a multiple-attribute decision-making (MADM) problem. Recently, the TODIM and TOPSIS technique has been used to cope with MADM issues. The Type-2 neutrosophic numbers (T2NNs) are employed as a technique for characterizing uncertain information during the innovation and entrepreneurship education evaluation in the application-oriented vocational colleges. In this paper, the Type-2 neutrosophic number TODIM-TOPSIS (T2NN-TODIM-TOPSIS) technique is implemented to solve the MADM under T2NNs. Finally, a numerical case study for innovation and entrepreneurship education evaluation in the application-oriented vocational colleges and several comparative analysis is implemented to validate the proposed T2NN-TODIM-TOPSIS technique. The main research contribution of this paper is managed: (1) the TODIM and TOPSIS technique was enhanced with T2NNs; (2) Entropy technique is enhanced to manage the weight values with T2NNs. (3) the T2NN-TODIM-TOPSIS technique is founded to manage the MADM with T2NNs; (4) Algorithm framework for innovation and entrepreneurship education evaluation in the application-oriented vocational colleges and several comparative analysis are constructed based on one numerical example to verify the effectiveness of the T2NN-TODIM-TOPSIS technique. Show more

Keywords: Multiple-attribute decision-making (MADM), Type-2 neutrosophic numbers (T2NNs), TODIM technique, TOPSIS technique, innovation and entrepreneurship education evaluation

DOI: 10.3233/JIFS-233811

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 3, pp. 5957-5973, 2024