Information Sciences: an International Journal

Since its first introduction, ordinary fuzzy sets have been extended to new types of fuzzy sets as a tool of artificial intelligence techniques. One of the recently introduced fuzzy sets, “Circular Intuitionistic Fuzzy (CIF)” sets ...

In D-S evidence theory, belief and commonality functions are well-defined and deeply researched. However, these concepts have not been extended to Random Permutation Set (RPS) because of the difficulties in giving a suitable definition ...

The current study addresses the issue of global dynamic event-triggered control based on reduced-order observer for a class of nonstrict-feedback stochastic systems in the presence of time-varying delay. Firstly, a lemma about the ...

Electronic healthcare (e-healthcare) system has brought great convenience for people to seek medical treatment. However, data security, user privacy and online diagnosis efficiency have also aroused widespread public concern. In this ...

Hypergraph generation has found wide applications in data analysis, social networks, and communication networks. Although various hypergraph generation methods have been proposed, many challenges remain. On the one hand, traditional ...

Images are frequently corrupted by various sorts of mixed or unrecognized noise, including mixed Poisson-Gaussian noise, rather than just a single kind of noise. In this work, we propose a time-space fractional differential equation to ...

Generalized Zero-Shot Learning (GZSL) aims to classify samples from seen and unseen classes using class-level features. Although existing GZSL methods have achieved remarkable progress, GZSL assumes a closed-set scenario, where both ...

In this paper, we propose two new group decision making (GDM) approaches based on the proposed linguistic intuitionistic fuzzy Yager weighted arithmetic (LIYFWA) aggregation operator (AO) of linguistic intuitionistic fuzzy numbers (...

Time series forecasting is crucial for several fields, such as disaster warning, weather prediction, and energy consumption. Transformer-based models are considered to have revolutionized the field of time series forecasting. However, ...

• A hierarchical and decomposable forecasting framework called Probabilistic Decomposition Transformer is proposed.

Due to the remarkable representation ability of Nonnegative matrix factorization (NMF), its multiview variants have become a crucial kind of multiview representation learning methods. However, the majority of existing methods fail to ...

Existing incomplete multi-view learning models focus on reconstructing the latent variables of multiple views by exploring complementary and consistent information among diverse views. However, filling the missing information for views ...

Functional encryption for inner product (FE-IP) allows an authorized user to obtain the inner product of the vectors embedded in his/her secret key and a ciphertext, respectively. Therefore, it is an elegant tool to implement secure ...

• A delegator is allowed to delegate his/her decryption power to a delegatee.
• The ...

The concept of hesitant set was introduced by Hu, which purpose is to unify hesitant fuzzy sets, interval-valued hesitant fuzzy sets, shadowed sets etc. This paper discusses the construction of decision evaluation functions and three-...

• Using chaotic systems to realize non-interactive integrity audit.
• Building ...

With the widespread adoption of Internet of Things (IoT) technology, a large amount of private data has been generated. Due to the limited computing and storage resources of IoT devices, enterprises and individuals choose to use a ...

Optimal controls receive much attention owing to their remarkable performance for nonlinear systems. However, unknown time-delay disturbances in the optimal control process make it difficult to find high-quality optimal set points. To ...

More and more studies have demonstrated that circRNAs can be used as markers of various diseases due to their inherent stability. Numerous computational methods, especially artificial intelligence approaches, have been applied to the ...

The flexible paradigm of Resource Description Framework (RDF) has accelerated the raw data published on the web. Therefore, the volume of generated RDF data has increased impressively in the last decade promoting compression to manage ...

The study of complex-valued evidence theory has become an interesting topic, particularly in the context of information fusion techniques. These studies mainly focus on its geometric interpretation and application. Moreover, little ...

This paper develops model-free optimal tracking policies for Markov jump systems by solving non-zero-sum games (NZSGs). First, coupled action and mode-dependent value functions (CAMDVFs) are built for solving a two-player NZSG and ...

The consensus tracking of multi-agent systems (MASs) with process and sensor faults is investigated in this paper. First, process faults are taken into account, and an intermediate estimator is designed to estimate the system states ...

Echo State Network (ESN) is widely applied in sequence prediction, physics, and economics. Moore-Penrose inversion is a typical solving process of ESN. However, in the era of big data, the traditional inversion is computationally ...

Federated Learning (FL) is a distributed learning paradigm in which clients collaboratively train a global model with shared gradients while preserving the privacy of local data. Recent researches found that an adversary can reveal ...

• The neurons activated by one data point in a fully connected layer will leak private training data.

In this paper, we propose a new multiattribute decision making (MADM) method based on the proposed nonlinear programming (NLP) model, the Gini coefficient, and the proposed score function (SF) of interval-valued intuitionistic fuzzy ...

Sensor–cloud system, as one of the vital components of the Internet of Everything, has increasingly gained popularity since it bridges the physical and cyber worlds. In the smart city, sensing devices are deployed to monitor the ...

Multi-phase batch processes (MPBP) have the characteristics of nonlinearity and various cases of switching, where the switching between two adjacent phases can be divided into synchronous vs asynchronous cases. The present study ...

• A novel mentioned-word representation learning model is proposed to generate location-enhanced word representations.

Twitter user geolocation has been garnering considerable attention from academia. Due to the complexity of the Twitter data, the user geolocation performance is limited for some user geolocation methods. Previous works on Twitter user ...

The quality of the acquisition data in the energy system of steel industry is the basis of prediction analysis and scheduling operation. Facing with its multi-dimensional and high-noise characteristics, in this study, an anomaly ...

Density peaks clustering (DPC) has had an impact in many fields, as it can quickly select centers and effectively process complex data. However, it also has low operational efficiency and a “Domino” effect. To solve these defects, we ...

In quantum theory, Bell locality of quantum states (generally, of correlations, or boxes) is characterized by local hidden variable models (LHVMs) given by integrals and sums. We call these models continuous and discrete LHVMs (C-LHVMs ...