International Journal of Intelligent Systems

The compromise solution of the multi‐criteria decision‐making (MCDM) problem by the existing VIKOR method for Pythagorean fuzzy sets (PyFSs) is not closest to the positive ideal solution. This is because the defining function for VIKOR does not ...

In the recent past, the fusion of various unimodal biometrics has gained increasing attention from researchers dedicated to the use of practical biometrics. In this paper, a Chaos Integrated Deep Neural Networks (Chaos‐DNN) using Sandpiper ...

Community detection can exhibit the aggregation behavior of complex networks. Network motifs are the fundamental building blocks which can reveal the higher‐order structure of complex networks. Label propagation algorithm has the advantage of ...

As a new extended form of intuitionistic fuzzy sets, Fermatean fuzzy sets are powerful tools for describing vagueness and uncertainty in complex problems. In the method of handling Fermatean fuzzy information, the distance measure is an essential ...

The selection and evaluation of fresh food suppliers is the primary problem for supermarkets. This problem is solved by a new multiattribute group decision‐making method with multigranular unbalanced hesitant fuzzy linguistic term set, which is ...

In an uncertain context of T‐spherical fuzzy (T‐SF) sets, the purpose of this study is to propound an efficacious multiple criteria choice model, named a T‐SF REGIME method, predicated on a dominance analysis and a prioritization analysis. The ...

Knowledge tracing (KT) is a fundamental personalized‐tutoring technique for learners in online learning systems. Recent KT methods employ flexible deep neural network‐based models that excel at this task. However, the adequacy of KT is still ...

In this study, inequality distance hyperplane multiclass support vector machines (IDH‐MSVM) algorithm is proposed on the basis of multiclassification support vector machine (MSVM) which was proposed by J. Weston and C. Watkins in 1999. It only ...

Demand response acts as an effectual tool to better balance electricity demand and supply in the smart grid. The response to prices and incentives is described as “changes on electricity usage from conventional consumption patterns to end‐use ...

The aim of the paper is to present the concept of a multiplicative preference relation (MPR) with the features of the single‐valued neutrosophic (SVN) set and named as SVN multiplicative preference relation (SVNMPR). The SVN set (SVNS) handles ...

The selection of optimal subset of features from high‐dimensional data sets still remains a major challenge during breast cancer detection and categorization. There exist several research works regarding optimal feature subset selection from high‐...

Image compression is the most important image processing method extensively deployed in different appliances. “Discrete wavelet transform (DWT)” is one of the well‐adopted transforming methods exploited for compressing images. The extremely ...

Real‐world applications often involve multifaceted data with several reasonable interpretations. To cluster this data, we need methods that are able to produce multiple clustering solutions. To this purpose, it is interesting to learn a finite ...

Seamless positioning services are of a critical concern in building smart cities. In a multisource fusion indoor positioning system, providing the guidance information for the deployment of positioning sources is a key technology, which can ...

In recent years, spiking neural networks (SNNs), which originated from the theoretical basis of neuroscience, have attracted neuromorphic computing and brain‐like computing due to their advantages, such as neural dynamics and coding mechanism, ...

Support Vector Data Description (SVDD) is an extremely hot topic issue in One‐Class Classification (OCC), which has displayed outstanding performance in dealing with many novelty detection problems. However, SVDD just takes the data description by ...

The defect detection is an important activity in quality analysis and control in the fabric industry. The presented work gives a comparative analysis of artificial neural network and deep learning architectures. The MobileNet and deep residual ...

Fine‐grained classification tasks are challenging because fine‐grained data sets are quite scarce. Thus, we utilized the domain adaptation method to migrate knowledge from large, labeled data sets to fine‐grained target data sets. We employed the ...

Existing data acquisition technologies desire further improvement to meet the increasing need for big, accurate, and high‐quality data collection. Most of the collected data have redundant information such as noise. To improve the classification ...

The coronavirus of 2019 (COVID‐19) was declared a global pandemic by World Health Organization in March 2020. Effective testing is crucial to slow the spread of the pandemic. Artificial intelligence and machine learning techniques can help COVID‐...

Developing efficient motion policies for multiagents is a challenge in a decentralized dynamic situation, where each agent plans its own paths without knowing the policies of the other agents involved. This paper presents an efficient learning‐...

The main aim of the proposed work is to develop the new technique based on decision‐theoretical rough sets (DTRSs) and their applications in three‐way decision‐making problems. This study first develop a fractional fuzzy set (FFS) and their ...

Decision‐making under uncertainty is consistently an essential fear and the most challenging circle of exploration. To manage the uncertainty, the intuitionistic fuzzy set (IFS) assumes a critical part in taking care of the conditions wherein ...

With the increasing popularity of Extensible Markup Language (XML) for data representation, there is a lot of interest in searching XML data. Due to the structural heterogeneity of XML, it is daunting for users to formulate exact queries and ...

The increasing desire for distributed computing systems has attracted huge interest in memory and computing resources. The cloud provides on‐demand access to provide a flexible allocation of resources for reliable services. Therefore, there should ...

Secure data‐sharing technology is a bridge for various collaborative operations among intelligent terminals in the edge‐cloud collaborative application scenario. For the shared data involves different levels of confidentiality, intelligent ...

Machine learning has made tremendous progress and applied to various critical practical applications. However, recent studies have shown that machine learning models are vulnerable to malicious attackers, such as neural network backdoor ...

Information cascade size prediction is one of the primary challenges for understanding the diffusion of information. Traditional feature‐based methods heavily rely on the quality of handcrafted features, requiring extensive domain knowledge and ...

Uncertainty is often occurred in real‐life decision‐making problems due to the lack of complete information, imprecise data, and the vagueness of decision making experts in qualitative judgment, thus, the crisp values of criteria may be ...