Journal of Intelligent & Fuzzy Systems - Volume 40, issue 6

Authors: Li, Hongyan | Wu, Peng | Zhou, Ligang | Chen, Huayou

Article Type: Research Article

Abstract: The consensus problem is a very important aspect of group decision making (GDM). In order to deal with the multiple criteria group decision consensus problem in the interval type-2 fuzzy environment, a consensus measure based on similarity measurement is proposed in this paper. In this paper, first, a new similarity measure of two interval type-2 fuzzy sets (IT2FSs) is defined and the consensus measure is defined by the similarity measure between two IT2FSs. Then, a new consensus feedback mechanism is proposed. In the stage of alternatives selection, the entropy of IT2FSs is defined, and the entropy weight method is used …to determine the weights of the criteria. Finally, the feasibility of the method proposed in this paper is illustrated by a comprehensive evaluation of old-age institutions. Show more

Keywords: IT2FSs, similarity measure, consensus, MCGDM

DOI: 10.3233/JIFS-201979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10935-10953, 2021

Authors: Ayidzoe, Mighty Abra | Yu, Yongbin | Mensah, Patrick Kwabena | Cai, Jingye | Kwabena, Adu | Tashi, Nyima

Article Type: Research Article

Abstract: Availability of massive amounts of data is a key contributing factor that influences the performance of deep learning models. Convolutional Neural Networks for instance, require large amounts of data in different variations to enable them generalize well to viewpoints. However, in health and other application domains, data generation and processing tasks are time-consuming and requires annotation by experts. Capsule Network (CapsNet) have been proposed to curtail the limitations of Convolutional Neural Networks (CNNs). Due to the problem of crowding, capsule Networks perform badly on complex and real-life images such as CIFAR 10 and some medical images. In this study, a …variant of a capsule network with a new algorithm referred to as the amplifier and a new squash function termed exponential squash is proposed. The amplifier is implemented in the encoder network to improve the texture of the images and has the ability to assign low relevance to irrelevant features and high relevance to vital features. The exponential squash function reduces the coupling strength of unrelated capsules in the lower and upper capsule layer. The proposed algorithm was evaluated on four datasets; CIFAR 10, fashion-MNIST, eye disease dataset and ODIR dataset achieving accuracies of 84.56% 93.76%, 89.02% and 87.27% respectively. This work sheds light on the possibility of applying CapsNet on complex real-world tasks. The proposed model can serve as an intelligent tool to aid medical personnel to diagnose eye disease and apply the necessary treatments. Show more

Keywords: Capsule network, convolutional neural network, squash function, feature amplification

DOI: 10.3233/JIFS-202080

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10955-10968, 2021

Authors: Zhou, Wang | Yang, Yujun | Du, Yajun | Haq, Amin Ul

Article Type: Research Article

Abstract: Recent researches indicate that pairwise learning to rank methods could achieve high performance in dealing with data sparsity and long tail distribution in item recommendation, although suffering from problems such as high computational complexity and insufficient samples, which may cause low convergence and inaccuracy. To further improve the performance in computational capability and recommendation accuracy, in this article, a novel deep neural network based recommender architecture referred to as PDLR is proposed, in which the item corpus will be partitioned into two collections of positive instances and negative items respectively, and pairwise comparison will be performed between the positive instances …and negative samples to learn the preference degree for each user. With the powerful capability of neural network, PDLR could capture rich interactions between each user and items as well as the intricate relations between items. As a result, PDLR could minimize the ranking loss, and achieve significant improvement in ranking accuracy. In practice, experimental results over four real world datasets also demonstrate the superiority of PDLR in contrast to state-of-the-art recommender approaches, in terms of Rec@N, Prec@N, AUC and NDCG@N. Show more

Keywords: Pairwise comparison, neural network, learning to rank, item recommendation

DOI: 10.3233/JIFS-202092

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10969-10980, 2021

Authors: Recal, Füsun | Demirel, Tufan

Article Type: Research Article

Abstract: Although Machine Learning (ML) is widely used to examine hidden patterns in complex databases and learn from them to predict future events in many fields, utilization of it for predicting the outcome of occupational accidents is relatively sparse. This study utilized diversified ML algorithms; Multinomial Logistic Regression (MLR), Support Vector Machines (SVM), Single C5.0 Tree (C5), Stochastic Gradient Boosting (SGB), and Neural Network (NN) in classifying the severity of occupational accidents in binary (Fatal/NonFatal) and multi-class (Fatal/Major/Minor) outcomes. Comparison of the performance of models showed Balanced Accuracy to be the best for SVM and SGB methods in 2-Class and SGB …in 3-Class. Algorithms performed better at predicting fatal accidents compared to major and minor accidents. Results obtained revealed that, ML unveils factors contributing to severity to better address the corrective actions. Furthermore, taking action related to even some of the most significant factors in complex accidents database with many attributes can prevent majority of severe accidents. Interpretation of most significant factors identified for accident prediction suggest the following corrective measures: taking fall prevention actions, prioritizing workplace inspections based on the number of employees, and supplementing safety actions according to worker’s age and experience. Show more

Keywords: Accidents severity, classification, data mining, feature selection; machine learning

DOI: 10.3233/JIFS-202099

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10981-10998, 2021

Authors: Li, Sizhao | Han, Xinyu | Bi, Lvqing | Hu, Bo | Dai, Songsong

Article Type: Research Article

Abstract: Complex fuzzy aggregation operation (CFAO) is a formalized definition of combining several complex fuzzy sets into a single complex fuzzy set. It extends classical fuzzy aggregation operation (FAO) to the complex-valued domain retaining classical real-valued weight. CFAO was initially defined with complex weight by Ramot et al. However, there has been virtually no progress in developing CFAO with complex weight. In this paper, we study the CFAOs with complex weight. We first discuss how to define complex weights meeting the restriction that the sum of weights is equal to 1. We give a new natural type of complex weight which …is different from Ramot et al.’s complex weight. Then we study various properties which include idempotency, homogeneity, rotational invariance and shift invariance for CFAOs with both types of complex weights. Show more

Keywords: Complex fuzzy sets, complex fuzzy aggregation, complex weight, invariance properties

DOI: 10.3233/JIFS-202100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10999-11005, 2021

Authors: Yu, Xiaobing | Yu, Xianrui | Zhang, Xueying

Article Type: Research Article

Abstract: Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined …based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications. Show more

Keywords: Emergency plan, case-based reasoning, adaptation, gravitational search algorithm

DOI: 10.3233/JIFS-202132

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11007-11022, 2021

Authors: Alansari, Monairah | Mohammed, Shehu Shagari | Azam, Akbar

Article Type: Research Article

Abstract: As an improvement of fuzzy set theory, the notion of soft set was initiated as a general mathematical tool for handling phenomena with nonstatistical uncertainties. Recently, a novel idea of set-valued maps whose range set lies in a family of soft sets was inaugurated as a significant refinement of fuzzy mappings and classical multifunctions as well as their corresponding fixed point theorems. Following this new development, in this paper, the concepts of e -continuity and E -continuity of soft set-valued maps and α e -admissibility for a pair of such maps are introduced. Thereafter, we present some generalized quasi-contractions …and prove the existence of e -soft fixed points of a pair of the newly defined non-crisp multivalued maps. The hypotheses and usability of these results are supported by nontrivial examples and applications to a system of integral inclusions. The established concepts herein complement several fixed point theorems in the framework of point-to-set-valued maps in the comparable literature. A few of these special cases of our results are highlighted and discussed. Show more

Keywords: 46S40, 47H10, 54H25, e-soft fixed point, e-continuous, F-contraction, soft set-valued map, αe-admissible, integral inclusion

DOI: 10.3233/JIFS-202154

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11023-11037, 2021

Authors: Nazra, Admi | Asdi, Yudiantri | Wahyuni, Sisri | Ramadhani, Hafizah | Zulvera,

Article Type: Research Article

Abstract: This paper aims to extend the Interval-valued Intuitionistic Hesitant Fuzzy Set to a Generalized Interval-valued Hesitant Intuitionistic Fuzzy Soft Set (GIVHIFSS). Definition of a GIVHIFSS and some of their operations are defined, and some of their properties are studied. In these GIVHIFSSs, the authors have defined complement, null, and absolute. Soft binary operations like operations union, intersection, a subset are also defined. Here is also verified De Morgan’s laws and the algebraic structure of GIVHIFSSs. Finally, by using the comparison table, a different approach to GIVHIFSS based decision-making is presented.

Keywords: Soft sets, intuitionistic fuzzy soft sets, hesitant fuzzy soft sets, interval-valued fuzzy soft sets

DOI: 10.3233/JIFS-202185

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11039-11050, 2021

Authors: Zhang, Yang | Ye, Jianmu

Article Type: Research Article

Abstract: This paper takes the listed pharmaceutical manufacturing firms in China’s A-share market from 2011 to 2017 as the research sample, from the perspective of top managers’ pay gap, employs principal component analysis and general least square method to empirically investigate the effect of risk preference of top management team(TMT) on the re-innovation behavior after the failure of innovation. The study found that the risk preference of TMT is positively correlated with the re-innovation input and brand-new innovation after the failure of innovation, but not with the supplementary innovation. Besides, the pay gap not only has a positive moderating effect on …the positive correlation between the risk preference of TMT and the re-innovation input, but also on the positive correlation between the risk preference of TMT and the brand-new innovation after the failure of innovation. The findings of this study contribute to: (1) through empirical research on the impact of TMT risk preference on re-innovation behavior after innovation failure, expand the relevant research content and research methods of TMT and innovation failure to make the research results more convincing; (2) by setting a reasonable executive compensation gap, TMT can avoid blindly choosing brand-new innovation behavior after innovation failure with the increase of risk preference innovation, ignoring the potential value of innovation failure projects without supplementary innovation, improving the re-innovation behavior of TMT after innovation failure and improving the re innovation success rate after innovation failure. Show more

Keywords: TMT risk preference, re-innovation after the failure, brand-new innovation, supplementary innovation, pay gap

DOI: 10.3233/JIFS-202186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11051-11061, 2021

Authors: Khan, Vakeel A. | Esi, Ayhan | Ahmad, Mobeen | Daud Khan, Mohammad

Article Type: Research Article

Abstract: In this article, we show that the addition and scalar multiplication in neutrosophic normed spaces are continuous. The neutrosophic boundedness and continuity of linear operators between neutrosophic normed spaces are examined. Moreover, we analyzed that the set of all neutrosophic continuous linear operators and the set of all neutrosophic bounded linear operators from neutrosophic normed spaces into another are vector spaces.

Keywords: Bounded linear operator, continuity, neutrosophic normed space

DOI: 10.3233/JIFS-202189

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11063-11070, 2021