Journal of Intelligent & Fuzzy Systems - Volume 46, issue 1

Authors: Sun, Peixi | Cui, Tong | Qi, Shixin

Article Type: Research Article

Abstract: Corporate culture is an objective existence that arises with the rise and development of enterprises. It originates from enterprise practice and influences the behavior of employees. Whether it is intentional identification or unintentional avoidance, corporate culture is not a question of absence, but a question of quality; It’s not about non-existent issues, but about the magnitude of their influence. Therefore, building a corporate culture that conforms to the characteristics of the enterprise and is recognized by the majority of employees, continuously enhancing the influence of corporate culture, is a very important topic in the construction of corporate culture. The corporate …culture influence evaluation is looked as the multiple attribute group decision-making (MAGDM) problem. The intuitionistic fuzzy sets (IFSs) are easy to depict the uncertain information during the corporate culture influence evaluation. Then, intuitionistic fuzzy Combined Compromise Solution (IF-CoCoSo) method is designed under IFSs. Furthermore, IF-CoCoSo is used to cope with the MAGDM. At last, an example is supplied for corporate culture influence evaluation to prove the practicability of the IF-CoCoSo method and some comparative analysis are conducted to verify the effectiveness of IF-CoCoSo method. Thus, the main objectives of this paper are outlined as follows: (1) the CRITIC method is used to obtain the weight information; (2) intuitionistic fuzzy Combined Compromise Solution (IF-CoCoSo) method is designed under IFSs; (3) IF-CoCoSo is used to cope with the MAGDM based on CRITIC weight information and Euclidean distance; (4) At last, an example is supplied for corporate culture influence evaluation to prove the practicability of the IF-CoCoSo method and some comparative analysis are conducted to show the effectiveness of IF-CoCoSo method. Show more

Keywords: Multiple attribute group decision-making (MAGDM), intuitionistic fuzzy sets (IFSs), IF-CoCoSo method, CRITIC weight method, corporate culture influence evaluation

DOI: 10.3233/JIFS-232044

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 297-307, 2024

Authors: Moosavi, Seyyed Mohammad Reza Hashemi | Araghi, Mohammad Ali Fariborzi | Ziari, Shokrollah

Article Type: Research Article

Abstract: Mathematical modeling of many natural and physical phenomena in industry, engineering sciences and basic sciences lead to linear and non-linear devices. In many cases, the coefficients of these devices, taking into account qualitative or linguistic concepts, show their complexity in the form of Z -numbers. Since Z -number involves both fuzziness and reliability or probabilistic uncertainty, it is difficult to obtain the exact solution to the problems with Z -number. In this work, a method and an algorithm are proposed for the approximate solution of a Z -number linear system of equations as an important case of such problems. The …paper is devoted to solving linear systems where the coefficients of the variables and right hand side values are Z -numbers. An algorithm is presented based on a ranking scheme and the neural network technique to solve the obtained system. Moreover, two examples are included to describe the procedure of the method and results. Show more

Keywords: Z-numbers, fuzzy number, linear systems of equations, artificial neural networks

DOI: 10.3233/JIFS-232452

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 309-320, 2024

Authors: Wang, Yongjie | Lu, Chang-e | Cheng, Zhihong | Wang, Juan

Article Type: Research Article

Abstract: Optimizing the allocation of preschool education resources and improving the efficiency of resource allocation is of great strategic significance for the universal and inclusive development of preschool education and the realization of “education for young children". In recent years, the shift from high-speed development to high-quality development of the social economy has significantly improved the balanced development level of China’s preschool education industry. However, preschool education remains the weakest link in China’s education system and the most unfavorable aspect of educational resource allocation. Problems such as shortage of preschool education resources, insufficient investment, uneven regional development, imbalanced supply and demand …structure, low resource allocation efficiency, and “difficult to enter, expensive to enter” are still prominent. How to optimize resource allocation and improve resource utilization efficiency in the limited resources of preschool education is the key to achieving balanced, fair, coordinated, and high-quality development of preschool education. The county preschool education resource allocation level evaluation is MAGDM problems. Recently, the TODIM and TOPSIS technique was employed to cope with MAGDM issues. The interval-valued Pythagorean fuzzy sets (IVPFSs) are employed as a tool for characterizing uncertain information during the county preschool education resource allocation level evaluation. In this manuscript, the interval-valued Pythagorean fuzzy TODIM-TOPSIS (IVPF-TODIM-TOPSIS) technique is built to solve the MAGDM under IVPFSs. Finally, a numerical case study for county preschool education resource allocation level evaluation is given to validate the proposed technique. The main contribution of this paper is managed: (1) the TODIM and TOPSIS technique was extended to IVPFSs; (2) Information Entropy is employed to manage the weight values under IVPFSs. (3) the IVPF-TODIM-TOPSIS technique is founded to manage the MAGDM under IVPFSs; (4) Algorithm analysis for county preschool education resource allocation level evaluation and comparison analysis are constructed based on one numerical example to verify the feasibility and effectiveness of the IVPF-TODIM-TOPSIS technique. Show more

Keywords: Multiple attribute group decision making (MAGDM), interval-valued Pythagorean fuzzy sets (IVPFSs), TODIM technique, TOPSIS technique, education resource allocation level evaluation

DOI: 10.3233/JIFS-233742

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 321-338, 2024

Authors: Ghavidel, Motahare | Yadollahzadeh-Tabari, Meisam | GolsorkhTabariAmiri, Mehdi

Article Type: Research Article

Abstract: In this paper, we proposed classification and clustering algorithms that are proper for analyzing customer-related datasets, which are mostly high-dimensional with too many instances. For the clustering purpose, This paper presents a Cuckoo-Search-based Variable Weighting (CSVW) Clustering algorithm to obtain optimal variable weights of high-dimensional data for each cluster. This paper also proposes a deep Inferarer Classifier for categorizing customers using Bi-Directional Long Short-Term Memory (Bi-LSTM) neural network, which uses a Fuzzy Inferential Classifier on its last layer. The Insurance Company (TIC) and InstaCart datasets are utilized for the experiments and performance evaluation. Simulation results reveal that the proposed clustering …algorithm generates appropriate Silhouette and Elbow criteria scores in a few cycles of execution in comparison to ordinal clustering algorithms. Also, the proposed classification algorithm with fuzzy soft-max classifier hits the better Classification Criteria in comparison. Show more

Keywords: Customer clustering, Cuckoo optimization, variable-sensitive clustering, deep learning

DOI: 10.3233/JIFS-230675

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 339-353, 2024

Authors: Li, Weidong | Li, Zhenying | Wang, Chisheng | Zhang, Xuehai | Duan, Jinlong

Article Type: Research Article

Abstract: Accurate identification and monitoring of aircraft on the airport surface can assist managers in rational scheduling and reduce the probability of aircraft conflicts, an important application value for constructing a "smart airport." For the airport surface video monitoring, there are small aircraft targets, aircraft obscuring each other, and affected by different weather, the aircraft target clarity is low, and other complex monitoring problems. In this paper, a lightweight model network for video aircraft recognition in airport field video in complex environments is proposed based on SSD network incorporating coordinate attention mechanism. First, the model designs a lightweight feature extraction network …with five feature extraction layers. Each feature extraction layer consists of two modules, Block_A and Block_I. The Block_A module incorporates the coordinate attention mechanism and the channel attention mechanism to improve the detection of obscured aircraft and to enhance the detection of small targets. The Block_I module uses multi-scale feature fusion to extract feature information with rich semantic meaning to enhance the feature extraction capability of the network in complex environments. Then, the designed feature extraction network is applied to the improved SSD detection algorithm, which enhances the recognition accuracy of airport field aircraft in complex environments. It was tested and subjected to ablation experiments under different complex weather conditions. The results show that compared with the Faster R-CNN, SSD, and YOLOv3 models, the detection accuracy of the improved model has been increased by 3.2%, 14.3%, and 10.9%, respectively, and the model parameters have been reduced by 83.9%, 73.1%, and 78.2% respectively. Compared with the YOLOv5 model, the model parameters are reduced by 38.9% when the detection accuracy is close, and the detection speed is increased by 24.4%, reaching 38.2fps, which can well meet the demand for real-time detection of aircraft on airport surfaces. Show more

Keywords: Complex environment, airport surface, aircraft recognition, SSD network, coordinate attention

DOI: 10.3233/JIFS-231423

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 355-368, 2024

Authors: Peng, Li-Ling | Bi, Xiao-Feng | Fan, Guo-Feng | Wang, Ze-Ping | Hong, Wei-Chiang

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-231588

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 369-388, 2024

Authors: Li, Yundong | Yan, Yunlong | Wang, Xiang

Article Type: Research Article

Abstract: Timely detection of building damage after a disaster can provide support and help in saving lives and reducing losses. The emergence of transfer learning can solve the problem of difficulty in obtaining several labeled samples to train deep models. However, some degree of differences exists among different scenarios, which may affect the transfer performance. Furthermore, in reality, data can be collected from multiple historical scenarios but cannot be directly combined using single-source domain adaptation methods. Therefore, this study proposes a multi-source variational domain adaptation (MVDA) method to complete the task of post-disaster building assessment. The MVDA method consists of two …stages: first, the distributions of each pair of source and target domains in specific feature spaces are aligned separately; second, the outputs of the pre-trained classifiers are aligned using domain-specific decision boundaries. This method maximizes the relevant information in the historical scene, solves the problem of inconsistent image classification in the current scene, and improves the migration efficiency from the history to the current disaster scene. The proposed approach is validated by two challenging multi-source transfer tasks using the post-disaster hurricane datasets. The average accuracy rate of 83.3% for the two tasks is achieved, obtaining an improvement of 0.9% compared with the state-of-the-art methods. Show more

Keywords: Building damage detection, domain adaptation, multi-source domain, transfer learning, remote sensing

DOI: 10.3233/JIFS-232613

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 389-404, 2024

Authors: An, Xiaogang | Chen, Mingming

Article Type: Research Article

Abstract: This paper explores the relationship between fuzzy logic algebra and non associative groupoid. As a groupoid which can satisfy type-2 cyclic associative (T2CA) law, T2CA-groupoid is characterized by generalized symmetry. Fuzzy logic algebra is a major direction in the study of fuzzy logic. Residuated lattices are a class of fuzzy logic algebras with widespread applications. The inflationary pseudo general residuated lattice (IPGRL), a generalization of the residuated lattice, does not need to satisfy the associative law and commutative law. Moreover, the greatest element of IPGRL is no longer the identity element. In this paper, the notion of T2CA-IPGRL (IPGRL in …T2CA-groupoid) is proposed and its properties are investigated in combination with the study of IPGRL and T2CA-groupoid. In addition, the generalized symmetry and regularity of T2CA-groupoid are investigated based on the characteristics of commutative elements. Meanwhile, the decomposition of T2CA-root of band with T2CA-unipotent radical is studied as well. The result shows that every T2CA-root of band is the disjoint union of T2CA-unipotent radicals. Show more

Keywords: Semigroup, cyclic associative groupoid, generalized regular T2CA-groupoid, fuzzy logic, pseudo general residuated lattice

DOI: 10.3233/JIFS-232966

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 405-418, 2024

Authors: Wang, Tianhui | Liu, Renjing | Liu, Jiaohui | Qi, Guohua

Article Type: Research Article

Abstract: With the development of artificial intelligence technology, the assessment method based on machine learning, especially the ensemble learning method, has attracted more and more attention in the field of credit assessment. However, most of the ensemble assessment models are complex in structure and costly in time for parameter tuning, few of them break through the limitations of lightweight, universal and efficient. This paper present a new ensemble model for personal credit assessment. First, considering the conflicts and differences among multiple sources of information, a new method is proposed to correct the category prior information by using the difference measure. Then, …the revised prior information is fused with the current sample information with the help of Bayesian data fusion theory. The model can integrate the advantages of multiple benchmark classifiers to reduce the interference of uncertain information. To verify the effectiveness of the proposed model, several typical ensemble classification models are selected and empirically studied using real customer credit data from a commercial bank in China, and the results show that among various assessment criteria: the proposed model not only effectively improves the multi-class classification performance, but also outperforms other advanced multi-class classification credit assessment models in terms of parameter tuning and generalizability. This paper supports commercial banks and other financial institutions examination and approval work. Show more

Keywords: Ensemble model, multi-class credit assessment, information fusion theory

DOI: 10.3233/JIFS-233141

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 419-431, 2024

Authors: Cui, Wei | Zhang, Xuerui | Shang, Mingsheng

Article Type: Research Article

Abstract: An increasing number of fake news combining text, images and other forms of multimedia are spreading rapidly across social platforms, leading to misinformation and negative impacts. Therefore, the automatic identification of multimodal fake news has become an important research hotspot in academia and industry. The key to multimedia fake news detection is to accurately extract features of both text and visual information, as well as to mine the correlation between them. However, most of the existing methods merely fuse the features of different modal information without fully extracting intra- and inter-modal connections and complementary information. In this work, we learn …physical tampered cues for images in the frequency domain to supplement information in the image space domain, and propose a novel multimodal frequency-aware cross-attention network (MFCAN) that fuses the representations of text and image by jointly modelling intra- and inter-modal relationships between text and visual information whin a unified deep framework. In addition, we devise a new cross-modal fusion block based on the cross-attention mechanism that can leverage inter-modal relationships as well as intra-modal relationships to complement and enhance the features matching of text and image for fake news detection. We evaluated our approach on two publicly available datasets and the experimental results show that our proposed model outperforms existing baseline methods. Show more

Keywords: Fake news detection, multimoal, cross attention, frequency domain

DOI: 10.3233/JIFS-233193

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 433-455, 2024