Journal of Intelligent & Fuzzy Systems - Volume 42, issue 6

Authors: Tavares, Thiago Henrique Barbosa de Carvalho | Ferreira, Bruno Pérez | Mendes, Eduardo Mazoni Andrade Marçal

Article Type: Research Article

Abstract: In this work the relationship between the Selic rate and some bank parameters defined by the so-called Basel Accords is studied. The cross-correlation between the Selic rate and the parameters is used to explain how these parameters affect the Selic rate and vice-versa so as to define the predictability of the Selic rate using (some of) these parameters as inputs. A model is then proposed for predicting the Selic rate based on some specific parameters using fuzzy logic ideas, which dealt with a partitioning of the universe of discourse using clusters related to the output data distribution. The proposed model …is compared to four other known models in the literature and showed to have better performance in average compared to all other models. Show more

Keywords: Finance, basel, statistics, fuzzy logic

DOI: 10.3233/JIFS-212128

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5681-5694, 2022

Authors: Xie, Rongjian | Jia, Yucai | Wu, Yuanmei | Zhang, Peiyun

Article Type: Research Article

Abstract: During major epidemics, monitoring vaccine quality can ensure the public health and social stability. Considering that social media has become an important way for the public to obtain external information during the epidemic. We developed a dual regulatory system of vaccine quality with the government in the leading role and the participation of We Media, and constructed a four-party evolutionary game model (government regulatory agency, We Media, vaccine industry groups, and the public) and analyzed the stability of each game player’s strategy choice. The system’s possible equilibrium points are identified using Lyapunov’s first law. Then the game trajectory between stakeholders …is simulated by MATLAB, the effects of initial intention and parameters on the evolution process and results are analyzed. The results show that to ensure the quality and safety of vaccines and stabilize network public opinion during epidemics, the government should invest in an effective supervision mechanism. By strengthening responsibility, increasing penalties, and reducing supervision costs, the probability of vaccine industry groups providing high-quality vaccines is effectively enhanced. Restricting the behavior of We Media and supervising vaccine industry groups to reduce speculation reduces the cost of government supervision and improves its efficiency. Show more

Keywords: Major epidemics, vaccine quality, dual regulatory system, four-party evolutionary game

DOI: 10.3233/JIFS-212146

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5695-5714, 2022

Authors: Wang, Haolun | Zhang, Faming

Article Type: Research Article

Abstract: The interaction operation laws (IOLs) between membership functions can effectively avoid the emergence of counterintuitive situations. The power average (PA) operator can eliminate the negative effect of extremely or improperly assessments on the decision results. The Heronian mean (HM) operator is capable of examining the interrelationship between the two attributes. To synthesize the powers of the IOLs, PA and HM operators in this paper, the PA and HM operators are extended to process T-spherical fuzzy evaluation information perfectly based on the IOLs, and the T-spherical fuzzy interaction power Heronian mean (T-SFIPHM) operator and its weighted form are proposed. We further …present some properties of these proposed AOs and discuss several special cases. Moreover, a novel method to T-spherical fuzzy multiple attribute decision making (MADM) problems applying the proposed AO is developed. Lastly, we present a numerical example to validate its feasibility and reasonableness, and the superiority of the developed method is further illustrated by sensitivity analysis of parameters and comparison with existing methods. The results show that proposed AOs not only can capture the interactivity among membership degree (MD), abstinence degree (AD) and non-membership degree (NMD) of T-spherical fuzzy numbers (T-SFNs), bust also ensure the overall balance of variable values in the process of information fusion and realize the interrelationship between attribute variables, so the decision results can be closer to reality and more reliable. Show more

Keywords: Multiple attribute decision making, T-spherical fuzzy sets, Heronian mean operator, interaction operation laws, power average operator

DOI: 10.3233/JIFS-212149

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5715-5739, 2022

Authors: Khan, Faiz Muhammad | Bibi, Naila | Xin, Xiao Long | Muhsina, | Alam, Aftab

Article Type: Research Article

Abstract: In multiple criteria decision making (MCDM) problem, the decision maker deal with a situation where the sum of membership and non-membership grade of an attributes does not belongs to [0, 1]. To avoid such a situation, we proposed a new type of fuzzy system known as fermatean fuzzy system. More precisely, we presented the notion of fermatean fuzzy ideal theory and rough fermatean fuzzy sets in semigroups. The idea of lower and upper approximation in fermatean fuzzy sets has been initiated. The study has been further extended to rough fermatean fuzzy left(resp. right, interior) ideals in semigroup. Several results related …to this notion are determined. Show more

Keywords: Intuitionistic fuzzy set, pythagorean fuzzy sets, rough sets, rough fermatean fuzzy sets in semigroups, rough fermatean fuzzy ideals in semigroups

DOI: 10.3233/JIFS-212162

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5741-5752, 2022

Authors: Meng, Mengjun | Lin, Qiuyun | Wang, Yingming

Article Type: Research Article

Abstract: The great changes in the external environment of the manufacturing supply chain make its demand more complex and difficult to control. This paper takes China as an example. According to questionnaire survey and principal component analysis, the risk indicators caused by uncertain demand are screened and classified to construct evaluation system and complete risk identification. The Bayesian network integrating fuzzy set theory and left and right fuzzy ranking is used to explore the relationship between risk indicators and supply chain to achieve risk evaluation. In view of the highest risk factors, an incentive mechanism model based on information sharing is …put forward to prove theoretically that information sharing is an important strategy to reduce risk. The results are as follows: The uncertain demand will lead to a high level of risk in China’s manufacturing supply chain, in which the level of information technology is the biggest cause. Only when manufacturing enterprises are willing to share information and other node enterprises join the information sharing team, can demand uncertainty be fundamentally reduced. The proposed risk assessment model realizes the method innovation and theoretical innovation. It can practical and effectively help relevant enterprises to determine and control risks. Show more

Keywords: Uncertainty of demand, manufacturing supply chain, Bayesian networks, model simulation, risk assessment

DOI: 10.3233/JIFS-212207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5753-5771, 2022

Authors: Zhai, Longzhen | Feng, Shaohong

Article Type: Research Article

Abstract: The optimal evacuation route in emergency evacuation can further reduce casualties. Therefore, path planning is of great significance to emergency evacuation. Aiming at the blindness and relatively slow convergence speed of ant colony algorithm path planning search, an improved ant colony algorithm is proposed by combining artificial potential field and quantum evolution theory. On the one hand, the evacuation environment of pedestrians is modeled by the grid method. Use the potential field force in the artificial potential field, the influence coefficient of the potential field force heuristic information, and the distance between the person and the target position in the …ant colony algorithm to construct comprehensive heuristic information. On the other hand, the introduction of quantum evolutionary theory. The pheromone is represented by quantum bits, and the pheromone is updated by quantum revolving door feedback control. In this way, it can not only reflect the high efficiency of quantum parallel computing, but also have the better optimization ability of ant colony algorithm. A large number of simulation experiments show that the improved ant colony algorithm has a faster convergence rate and is more effective in evacuation path planning. Show more

Keywords: Emergency evacuation, path planning, ant colony algorithm (ACO), quantum evolution theory

DOI: 10.3233/JIFS-212220

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5773-5788, 2022

Authors: Cao, Rui | Jiang, Feng | Wu, Zhao | Ren, Jia

Article Type: Research Article

Abstract: With the advancement of computer performance, deep learning is playing a vital role on hardware platforms. Indoor scene segmentation is a challenging deep learning task because indoor objects tend to obscure each other, and the dense layout increases the difficulty of segmentation. Still, current networks pursue accuracy improvement, sacrifice speed, and augment memory resource usage. To solve this problem, achieve a compromise between accuracy, speed, and model size. This paper proposes Multichannel Fusion Network (MFNet) for indoor scene segmentation, which mainly consists of Dense Residual Module(DRM) and Multi-scale Feature Extraction Module(MFEM). MFEM uses depthwise separable convolution to cut the number …of parameters, matches different sizes of convolution kernels and dilation rates to achieve optimal receptive field; DRM fuses feature maps at several levels of resolution to optimize segmentation details. Experimental results on the NYU V2 dataset show that the proposed method achieves very competitive results compared with other advanced algorithms, with a segmentation speed of 38.47 fps, nearly twice that of Deeplab v3+, but only 1/5 of the number of parameters of Deeplab v3 + . Its segmentation results were close to those of advanced segmentation networks, making it beneficial for the real-time processing of images. Show more

Keywords: Deep learning, indoor scene segmentation, neural network, image processing, receptive field

DOI: 10.3233/JIFS-212275

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5789-5798, 2022

Authors: Muhiuddin, G. | Catherine Grace John, J. | Elavarasan, B. | Porselvi, K. | Al-Kadi, D.

Article Type: Research Article

Abstract:  The notions of hybrid ideals and k -hybrid ideals in a ternary semiring are introduced in this paper, and a substantial amount of effort has been made to study some of their features. In terms of characteristic function, we show some properties of k -hybrid ideals and give some characterizations of hybrid intersection with respect to these k -hybrid ideals. Finally, results based on a k -hybrid ideal’s homomorphic hybrid preimage are provided. With respect to k-hybrid ideals, we give certain characterizations of hybrid intersection.

Keywords: Semirings, Ternary semirings, k-hybrid ideals, Homomorphism, ψ-invariant

DOI: 10.3233/JIFS-212311

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5799-5807, 2022

Authors: Xiao, Qingjiang | Du, Shiqiang | Yu, Yao | Huang, Yixuan | Song, Jinmei

Article Type: Research Article

Abstract: In recent years, tensor-Singular Value Decomposition (t-SVD) based tensor nuclear norm has achieved remarkable progress in multi-view subspace clustering. However, most existing clustering methods still have the following shortcomings: (a) It has no meaning in practical applications for singular values to be treated equally. (b) They often ignore that data samples in the real world usually exist in multiple nonlinear subspaces. In order to solve the above shortcomings, we propose a hyper-Laplacian regularized multi-view subspace clustering model that joints representation learning and weighted tensor nuclear norm constraint, namely JWHMSC. Specifically, in the JWHMSC model, firstly, in order to capture the …global structure between different views, the subspace representation matrices of all views are stacked into a low-rank constrained tensor. Secondly, hyper-Laplace graph regularization is adopted to preserve the local geometric structure embedded in the high-dimensional ambient space. Thirdly, considering the prior information of singular values, the weighted tensor nuclear norm (WTNN) based on t-SVD is introduced to treat singular values differently, which makes the JWHMSC more accurately obtain the sample distribution of classification information. Finally, representation learning, WTNN constraint and hyper-Laplacian graph regularization constraint are integrated into a framework to obtain the overall optimal solution of the algorithm. Compared with the state-of-the-art method, the experimental results on eight benchmark datasets show the good performance of the proposed method JWHMSC in multi-view clustering. Show more

Keywords: Multi-view subspace clustering, representation learning, hyper-Laplacian regularization, weighted tensor nuclear norm

DOI: 10.3233/JIFS-212316

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5809-5822, 2022

Authors: Sha, Gang | Wu, Junsheng | Yu, Bin

Article Type: Research Article

Abstract: Purpose: Reading spinal CT (Computed Tomography) images is very important in the diagnosis of spondylosis, which is time-consuming and prones to make biases. In this paper, we propose a framework based on Faster-RCNN to improve detection performances of three spinal fracture lesions: cfracture (cervical fracture), tfracture (thoracic fracture) and lfracture (lumbar fracture). Methods: First, we use ResNet50 to replace VGG16 in backbone network in Faster-RCNN to increase depth of training network. Second, we utilize soft-NMS (Non-Maximum Suppression) instead of NMS to avoid missed detection of overlapped lesions. Third, we simplify RPN (Region Proposal Network) to accelerate training speed …and reduce missed detection. Finally, we modify the classifier layer in Faster-RCNN and choose appropriate length-width ratio by changing anchor sizes in sliding window, then adopt multi-scale strategy in training to improve efficiency and accuracy. Results: The experimental results show that the proposed scheme has a good performance, mAP (mean average precision) is 90.6%, IOU (Intersection of Union) is 88.5 and detection time is 0.053 second per CT image, which means our proposed method can accurately detect spinal fracture lesions. Conclusion: Our proposed method can provide assistance and scientific references for both doctors and patients in clinically. Show more

Keywords: Faster-RCNN, Detection, ResNet50, soft-NMS

DOI: 10.3233/JIFS-212389

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5823-5837, 2022