Journal of Intelligent & Fuzzy Systems - Volume 44, issue 3

Authors: Karthiga, S. | Abirami, A.M.

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Abstract: This article has been retracted.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-220408

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4257-4272, 2023

Authors: Tang, Chao | Tang, Yong | Zeng, Zhuolin | Zhang, Linghao | Xiang, Siyu

Article Type: Research Article

Abstract: Because the traditional methods do not select the best feature collection in feature analysis, the accuracy and effectiveness of user feature clustering are not high, and the accuracy of user feature classification is not high. Therefore, this paper proposes a customer feature analysis method based on power consumption feature selection and behavior portrait of different people. The optimal feature set is obtained according to the maximum correlation and minimum redundancy criterion, and the user portrait task is described. The spatial feature domain classification method is used to classify the user portrait information, and the user label database is constructed according …to the classification results. The AP clustering algorithm is used to cluster the power user portrait information and complete the customer feature analysis. Experimental results show that this method effectively improves the accuracy and effectiveness of user feature clustering, and the accuracy of user feature classification is high, indicating that the application effect is good. Show more

Keywords: Power consumption characteristics, behavioral portraits, customer characteristics, AP clustering algorithm, information classification

DOI: 10.3233/JIFS-220615

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4273-4283, 2023

Authors: Yin, Ming | Zhou, Pan | Xu, Taige | Jiang, Jijiao

Article Type: Research Article

Abstract: Requirements are important in software development. Ambiguous requirements cause inconsistent understanding by developers, which leads to rework, delayed delivery, and other problems, and may even have devastating effects on the project. A large number of requirements text written in natural language are not concise, intuitive, and accurate. This condition increases the workload of designers and the difficulty of their tasks. An effective solution for the aforementioned problems is to extract actors and use cases from the requirement texts. This study proposes a model for extracting actors and using cases automatically, which combines bi-directional long short-term memory (BiLSTM) and conditional random …fields. BiLSTM is used to capture the contextual information of the texts, and CRF is used to calculate the tag transfer score and determine the most accurate tag sequence, which aims to extract actors and use cases. Results show that the accuracy of extraction is significantly improved compared with the baseline method, which verifies the effectiveness of the proposed method in extracting actors and use cases. Show more

Keywords: BiLSTM-CRF, software requirements, actors and use cases, context

DOI: 10.3233/JIFS-221094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4285-4299, 2023

Authors: Park, Choonkil | Rehman, Noor | Ali, Abbas

Article Type: Research Article

Abstract: The q -rung orthopair fuzzy sets accommodate more uncertainties than the Pythagorean fuzzy sets and hence their applications are much extensive. Under the q -rung orthopair fuzzy set, the objective of this paper is to develop new types of q -rung orthopair fuzzy lower and upper approximations by applying the tolerance degree on the similarity between two objects. After employing tolerance degree based q -rung orthopair fuzzy rough set approach to it any times, we can get only the six different sets at most. That is to say, every rough set in a universe can be approximated by only six …sets, where the lower and upper approximations of each set in the six sets are still lying among these six sets. The relationships among these six sets are established. Furthermore, we propose tolerance degree based multi granulation optimistic/pessimistic q -rung orthopair fuzzy rough sets and investigate some of their properties. Another main contribution of this paper is to disclose the ideas of different kinds of approximations called approximate precision, rough degree, approximate quality and their mutual relationship. Finally a technique is devloped to rank the alternatives in a q -rung orthopair fuzzy information system based on similarity relation. We find that the proposed method/technique is more efficient when compared with other existing techniques. Show more

Keywords: q-rung orthopair fuzzy set, fuzzy rough set, similarity relation, tolerance classes, multigranulation q-rung orthopair fuzzy rough sets

DOI: 10.3233/JIFS-221249

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4301-4321, 2023

Authors: Apinaya Prethi, K.N. | Sangeetha, M. | Nithya, S.

Article Type: Research Article

Abstract: Due to decentralized infrastructure in modern Internet-of-Things (IoT), the tasks should be shared around the edge devices via network resources and traffic prioritizations, which weaken the information interoperability. To solve this issue, a Minimized upgrading batch Virtual Machine (VM) Scheduling and Bandwidth Planning (MSBP) was adopted to reduce the amount of batches needed to complete the system-scale upgrade and allocate the bandwidth for VM migration matrices. But, the suboptimal use of VM and possible loss of tasks may provide inadequate Resource Allocation (RA). Hence, this article proposes an MSBP with the Priority-based Task Scheduling (MSBP-PTS) algorithm to allocate the tasks …in a prioritized way and maximize the profit by deciding which request must handle by the edge itself or send to the cloud server. At first, every incoming request in its nearest fog server is allocated and processed by the priority scheduling unit. Few requests are reallocated to other fog servers when there is an inadequate resource accessible for providing the request within its time limit. Then, the request is sent to the cloud if the fog node doesn’t have adequate resources, which reduces the response time. However, the MSBP is the heuristics solution which is complex and does not ensure the global best solutions. Therefore, the MSBP-PTS is improved by adopting an Optimization of RA (MSBP-PTS-ORA) algorithm, which utilizes the Krill Herd (KH) optimization instead of heuristic solutions for RA. The simulation outcomes also demonstrate that the MSBP-PTS-ORA achieve a sustainable network more effectively than other traditional algorithms. Show more

Keywords: Internet-of-things, edge devices, resource allocation, priority levels, task scheduling, krill herd optimization

DOI: 10.3233/JIFS-221430

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4323-4334, 2023

Authors: Wu, Nengkai | Jia, Dongyao | Zhang, Chuanwang | Li, Ziqi

Article Type: Research Article

Abstract: Cervical cancer is one of the most common causes of death in women in the world, and early screening is an effective means of diagnosis and treatment, which can greatly improve the survival rate. Cervical cell classification model is an effective means to assist screening. However, the existing single model, including CNNs and machine learning methods, still has shortcomings such as unclear feature meaning, low accuracy and insufficient supervision. To solve the shortcomings of a single model, a novel framework based on strong feature Convolutional Neural Networks (CNN)-Lagrangian Support Vector Machine (LSVM) model is proposed for the accurate classification of …cervical cells. Strong features extracted by hybrid methods are fused with the abstract ones from hidden layers of LeNet-5, then the fused features are processed with dimension reduction and fed into the LSVM classifier optimized by Adaboost for classification. Proposed model is evaluated using the augmented Herlev and private dataset with the metrics including accuracy (Acc) , sensitivity (Sn) , and specificity (Sp) , which outperformed the baselines and state-of-the-art approaches with the Acc of 99.5% and 94.2% in 2&7-class classification, respectively. Show more

Keywords: Cervical cancer, strong feature, convolutional neural networks (CNN), lagrangian support vector machine (LSVM), cancer cell classification

DOI: 10.3233/JIFS-221604

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4335-4355, 2023

Authors: Liu, Zhiyong | Jin, Ying | Bao, Hong | Zhao, Yong

Article Type: Research Article

Abstract: A novel for an integrated fault and states estimator was proposed for the generalized linear discrete-time system with disturbances. The proposed scheme was based on a Self-Organizing fuzzy Luenberger system to estimate the states and approximate the fault information simultaneously for the generalized linear discrete-time system. For this purpose, a generalized linear discrete-time system with disturbances was transformed into an equivalent standard state-space system with disturbances and faults. Then, the faults and disturbances of generalized linear discrete-time system can be separated with the coordinate transform, meanwhile the Self-Organizing fuzzy Luenberger estimator was designed to obtain the accurate fault information. Based …on the obtained fault information, the fault detection experiments were performed, and the fault feature parameters required for fault isolation were determined. Finally, the proposed strategy was applied for a direct current motor to demonstrate the effectiveness of the proposed approach. Show more

Keywords: Self-organizing fuzzy Luenberger method, coordinate transform, faults and disturbances separation, fault detection, generalized linear discrete time system

DOI: 10.3233/JIFS-222890

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4357-4370, 2023

Authors: Wu, Xiu-Yun | Niu, Yu-Jie | Zhang, Hui-Min

Article Type: Research Article

Abstract: In this paper, the notion of M -fuzzifying convex remotehood systems is introduced and characterizations of M -fuzzifying convex spaces are obtained. Further, notions of remote mappings and M -fuzzifying convex quasi-uniformities are introduced. It is proved that M -fuzzifying convex quasi-uniform space and M -fuzzifying convex space are mutually induced. In order to discuss categorical relationships among M -fuzzifying convex quasi-uniform spaces, M -fuzzifying convex remotehood spaces and M -fuzzifying convex spaces, notions of M -fuzzifying quasi-uniformizable convex structures and M -fuzzifying quasi-uniformizable convex remotehood spaces are presented. It is proved that the category of M -fuzzifying quasi-uniformizable convex …spaces and the category of M -fuzzifying quasi-uniformizable convex remotehood spaces can be embedded into the category of M -fuzzifying convex quasi-uniform spaces as subcategories. Show more

Keywords: M-fuzzifying convex space, M-fuzzifying convex remotehood space, M-fuzzifying quasi-uniformizable convex space, M-fuzzifying convex quasi-uniform space, M-fuzzifying quasi-uniform preserving mapping

DOI: 10.3233/JIFS-223036

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4371-4382, 2023

Authors: Liu, Shengyao | Lin, Jiaoqing | Xu, Xinrui

Article Type: Research Article

Abstract: The construction industry is the basic industry of the country. With the rapid development of the economy, the construction industry has grown rapidly and the competition in the construction market has become more intense. The competition in the construction market is not only between individual enterprises, but also between the whole supply chain that provides products. Therefore, it is imperative to introduce the idea of supply chain management, strengthen the cooperation with suppliers and improve competitiveness. Supplier evaluation and selection is one of the first issues to be solved for the development of supply chain management. The selection and application …of building material suppliers is a classic multiple attribute decision making (MADM). In this paper, the intuitionistic fuzzy sets (IFSs) and Hamacher operations is introduced and the induced intuitionistic fuzzy Hamacher power ordered weighted average (I-IFHPOWA) operator is built. Meanwhile, the properties of built operator are analyzed. Then, the I-IFHPOWA operator is applied to solve the MADM under IFSs. Finally, an example for building material supplier selection is utilized to proof this built model. Show more

Keywords: Multiple attribute decision making (MADM), intuitionistic fuzzy sets (IFSs), I-OWA operator, I-IFHPOWA operator, building material suppliers

DOI: 10.3233/JIFS-221437

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4383-4395, 2023

Authors: Jagadish Kumar, N. | Balasubramanian, C.

Article Type: Research Article

Abstract: In a cloud computing system, resources can be accessed at a minimal cost whenever users raise request needs. The primary goal of cloud computing is to provide cost-efficiency of service scheduling to clients fast while using the least number of resources. Cloud Service Provisioning (CSP) can match consumer needs with minimal use of resources. There are several metaheuristic optimization algorithms have been developed in the field of CSP resource minimization and adequate computing resources are required to ensure client satisfaction. However, it performs poorly under a variety of practical constraints, including a vast amount of user data, smart filtering to …boost user search, and slow service delivery. In this regard, propose a Black Widow Optimization (BWO) algorithm that reduces cloud service costs while ensuring that all resources are devoted only to end-user needs. It is a nature-inspired metaheuristic algorithm that involved a multi-criterion correlation that is used to identify the relationship between user requirements and available services and thereby, it is defined as an MS-BWO algorithm. Thus finds the most efficient virtual space allocation in a cloud environment. It uses a service provisioning dataset with metrics like energy usage, bandwidth utilization rate, computational cost, and memory consumption. In terms of data performance, the proposed MS-BWO outperforms exceed than other existing state-of-art-algorithms including Work-load aware Autonomic Resource Management Scheme(WARMS), Fuzzy Clustering Load balancer(FCL), Agent-based Automated Service Composition (A2SC) and Load Balancing Resource Clustering (LBRC), and an autonomic approach for resource provisioning (AARP ) Show more

Keywords: Cloud service provisioning, Resource utilization, Virtual machine, Metaheuristic black widow optimization

DOI: 10.3233/JIFS-222048

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4397-4417, 2023