Journal of Intelligent & Fuzzy Systems - Volume 43, issue 1

Authors: Jia, Zhifu | Liu, Xinsheng

Article Type: Research Article

Abstract: Uncertain delay differential system is an important mathematical model. Stability is a basic problem of uncertain delay differential system. Delay and uncertain interference often lead to changes in the stability of the system. Establishing the judgment of the stability of uncertain delay differential system conditions is very important. Based on the strong Lipschitz condition, the judgment of p -th moment stability for uncertain delay differential equations (UDDEs) has been investigated. Actually, the strong Lipschitz condition is assumed that it only relates to the current state, it is difficult to be employed to determine the stability in p -th moment for …the UDDEs. In this paper, we consider two kinds of new Lipschitz conditions containing the current state and the past state, which are more weaker than the strong Lipschitz condition. Meanwhile, new sufficient theorems and corollaries under the new Lipschitz conditions as the tools to judge the p -th moment stability for the UDDEs are proved. Some examples explain the rationality of the corresponding theorems and corollaries. Show more

Keywords: Liu process, stability in p-th moment, new Lipschitz conditions, uncertain delay differential equations

DOI: 10.3233/JIFS-212288

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 451-461, 2022

Authors: Shuang, Chen | Tao, Ren | Yuntai, Ding

Article Type: Research Article

Abstract: Automatic Text Summarization(ATS) is distinctly beneficial due to a vast amount of textual data and time-consuming manual summarization. In order to enhance ATS for single document in huge datasets, a new extractive graph framework - text extractive SUMmarization framework based on EDge information with COreference resolution EDCOSUM is proposed in this paper that relies on coreference resolution, adding edge information in word-level graph and a sentence-ranking strategy. EDCOSUM combines the graph-based and statistical-based extractive summarization methods. It is a general method for any document (not limited to a specific domain). Moreover, two ranking strategies(sentence and LSA ranking strategy) are proposed …for sentence selection. A set of extensive experiments on CNN/Daily Mail and NEWSROOM are conducted for investigating the proposed method. The widely used automatic evaluation tool: Recall-Oriented Understudy for Gisting Evaluation(ROUGE) is utilized to evaluate EDCOSUM. Compared to the state-of-the-art ATS methods, EDCOSUM achieves a competitive result by improvements of over the highest scores in the literature for metrics ROUGE-1, ROUGE-2 and ROUGE-L respectively. Show more

Keywords: Text extractive summarization, Graph theory, Coreference resolution, Word-level graph, Ranking strategy

DOI: 10.3233/JIFS-212289

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 463-475, 2022

Authors: Heim, Isaac | Fonseca, Daniel J. | Houser, Rick | Cook, Ryan | O’Donnell, John

Article Type: Research Article

Abstract: This paper deals with the design and development of a novel approach, centered on the creation and development of a fuzzy controller to analyze electroencephalogram (EEG) data. The fuzzy controller makes use of the functions associated with the different regions of the brain to correlate multiple Brodmann areas to several outputs, where a normal analysis would associate only one region to one output. This controller was designed to quickly adapt to any data imported into it. The current implemented framework supports a math study. The math subjects’ outputs were attuned to their related study which involved transcranial direct current stimulation …(tDCS), which is a form of neurostimulation. Anode affinity, cathode affinity, calculation, memory, and decision making were the outputs focused on for the math study. This task is best suited to a fuzzy controller since interactions between Brodmann areas can be analyzed and the contributions of each area accounted for by indicating which regions have stronger and weaker effects on any given output. Show more

Keywords: Neurological activation, transcranial direct current stimulation, EEG, fuzzy controller, math enhancement

DOI: 10.3233/JIFS-212315

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 477-494, 2022

Authors: Wang, Ya-na | Zhou, Guo-hua

Article Type: Research Article

Abstract:  The aim of this paper is to investigate pricing and production decisions of a monopoly firm that operates a co-product technology with two grades. A novel mathematical model that embeds a utility-maximizing customer choice model is developed to solve this problem. The closed-form expressions for the optimal solutions are derived and the results suggest that the distribution of customer valuations, yield rate and demand uncertainties have a vital influence on the firm’s optimal prices and profits. We then extend our study by allowing stockout-based substitution where a customer may be willing to purchase a substitute if his most preferred product …is not available but the substitute provides him with non-negative utility. The results indicate that disregarding stockout-based substitution (i) results in severe supply-demand mismatches for the product line in two directions; (ii) leads to higher or lower profit margins for both products; (iii) may not cause profit loss when the prices of both products are exogenous; however, this result does not hold when the prices are endogenous. Show more

Keywords: Random yield, utility-maximizing customers, customer substitution, product line

DOI: 10.3233/JIFS-212317

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 495-507, 2022

Authors: Zhang, Qiang | Liu, Jianping | Hu, Junhua | Yao, Zhihai | Yang, Jian

Article Type: Research Article

Abstract: With the increasing complexity of decision making (DM) problems, powerful mathematical tools are needed to represent and process fuzzy and uncertain DM information, and Pythagorean fuzzy set (PFS) is such a mathematical tool. PFS has been successfully applied in the field of fuzzy multiple criteria decision making (MCDM). Correlation coefficient is an information measure of PFS, and plays an important role in the application of PFS. At present, there is a problem that the existing correlation coefficients cannot moderately measure the correlation degree between PFSs, so this paper proposes the new correlation coefficients of PFS. The TODIM method has been …proved to be effective in dealing with MCDM problems that consider the psychological behavior of decision makers. This paper extends the TODIM method with the new correlation coefficients of PFS, and the extended TODIM method is called Pythagorean fuzzy CC-TODIM method. By numerical examples, it is verified that the new correlation coefficients of PFS are more reasonable and valid. By case analysis, it is verified that the Pythagorean fuzzy CC-TODIM method can effectively solve the MCDM problems, and the Pythagorean fuzzy CC-TODIM method based on the new correlation coefficients is more accurate and reliable. Show more

Keywords: Pythagorean fuzzy set, correlation coefficient, TODIM method, multiple criteria decision making

DOI: 10.3233/JIFS-212323

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 509-523, 2022

Authors: Wang, Huidong | Zhang, Yao | Bai, Chuanzheng

Article Type: Research Article

Abstract: As an effective tool for three-way decisions (3WD) problems, decision-theoretic rough sets (DTRSs) have raised increasing attention recently. In view of the advantages of q-rung orthopair uncertain linguistic variables (q-ROULVs) in depicting uncertain information, a new DTRSs model based on q-ROULVs is proposed to solve three-way group decision-making (3WGDM) problems. Firstly, the loss function of DTRSs is depicted by q-ROULVs and a q-rung orthopair uncertain linguistic DTRSs model is constructed subsequently. Secondly, to aggregate different experts’ evaluation results on loss function in group decision-making (GDM) scenario, the q-rung orthopair uncertain linguistic geometric Heronian mean (q-ROULGHM) operator and the q-rung orthopair …uncertain linguistic weighted geometric Heronian mean (q-ROULWGHM) operator are presented. Related properties of the proposed operators are investigated. Thirdly, to compare the expected loss of each alternative, a new score function of q-ROULVs is defined and the corresponding decision rules for 3WGDM are deduced. Finally, an illustrative example of venture capital in high-tech projects is provided to verify the rationality and effectiveness of our method. The influence of different conditional probabilities and parameter values on decision results is comprehensively discussed. Show more

Keywords: q-rung orthopair uncertain linguistic variable, decision-theoretic rough set, three-way group decision-making, geometric Heronian mean operator

DOI: 10.3233/JIFS-212327

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 525-544, 2022

Authors: Kumar, Arvind | Sodhi, Sartaj Singh

Article Type: Research Article

Abstract: We increase the power of the Artificial Neural Networks with the help of the Activation Function (AF). The tansig and logsig are widely used AF. But there is still requires some improvement in the AF. So, in this paper, we have proposed a NewSigmoid AF in the neural network. NewSigmoid is also as powerful as tansig and logsig. In multiple cases, the NewSigmoid function gives a better or equivalent performance as compared with both these AF. Like these AF, NewSigmoid is also a smooth S-shape, bounded, continuously differentiable, and zero-centered function. Therefore the NewSigmoid is also suitable for solving non-linear …problems. We have tested this AF on iris, cancer, glass, chemical, bodyfat, wine, and ovarian datasets. We use Scaled Conjugate Gradient (SCG), Levenberg-Marquardt (LM), and Bayesian Regularization (BR) algorithms during the optimization of the neural network. Maximum 100% accuracy in the iris dataset while using LM, and BR; 99.9% accuracy in the cancer dataset using BR; 100% accuracy in the glass dataset using BR; 100% accuracy in the chemical and bodyfat dataset using SCG, LM, and BR; 100% accuracy in the wine dataset using LM, and BR; and 99.1% accuracy in the ovarian dataset using BR has been found while working with multilayer neural networks. The NewSigmoid also achieves 100% training and validation accuracy on the mathework-cap image dataset using SCG. Show more

Keywords: Logsigmoid, tanigmoid, neural network, activation function, multilayer network.

DOI: 10.3233/JIFS-212333

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 545-559, 2022

Authors: Anoop, P.S. | Sugumaran, V.

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-212336

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 561-573, 2022

Authors: Zhou, Qin | Su, Zuqiang | Liu, Lanhui | Hu, Xiaolin | Yu, Jianhang

Article Type: Research Article

Abstract: This study presents a fault diagnosis method for rolling bearing based on multi-scale deep subdomain adaptation network (MSDSAN). The proposed MSDSAN, as improvement of deep subdomain adaptation network (DSAN), is an unsupervised transfer learning method. MSDSAN reduces the subdomain distribution discrepancy between domains rather than marginal distribution discrepancy, and so better domain invariant fault features are derived to avoid misalignment between domains. Aiming at avoiding fault information loss by fixed receptive fields feature extraction, selective kernel convolution module is introduced into feature extraction of MSDSAN, by which multiple receptive fields are applied to ensure an optimal receptive field for each …working condition. Moreover, contribution rates are adaptively assigned to all receptive fields, and the disturbing information extracted by inappropriate receptive fields is further eliminated. As a result, more comprehensive and effective fault information is derived for bearing fault diagnosis. Fault diagnosis experiment of bearings is performed to verify the superiority of the proposed method, and the experimental results demonstrate that MSDSAN achieves better transfer effects and higher accuracy than SOTA methods under varying working conditions. Show more

Keywords: Rolling bearing, fault diagnosis, transfer learning, subdomain adaptation

DOI: 10.3233/JIFS-212343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 575-585, 2022

Authors: Hao, Bing | Zhang, Tianwei

Article Type: Research Article

Abstract: Exponential Euler differences for semi-linear differential equations of first order have got rapid development in the past few years and a variety of exponential Euler difference methods have become very significant researching topics. In allusion to fuzzy genetic regulatory networks of fractional order, this paper firstly establishes a novel difference method called Mittag-Leffler Euler difference, which includes the exponential Euler difference. In the second place, the existence of a unique global bounded solution and equilibrium point, global exponential stability and synchronization of the derived difference models are investigated. Compared with the classical fractional Euler differences, fuzzy Mittag-Leffler discrete-time genetic regulatory …networks can better depict and retain the dynamic characteristics of the corresponding continuous-time models. What’s more important is that it starts a new avenue for studying discrete-time fractional-order systems and a set of theories and methods is constructed in studying Mittag-Leffler discrete models. Show more

Keywords: Genetic regulatory, Caputo, Mittag-Leffler Euler difference, exponential stability, exponential synchronization

DOI: 10.3233/JIFS-212361

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 587-613, 2022