Issue Information
Emergency decision support modeling for COVID‐19 based on spherical fuzzy information
Significant emergency measures should be taken until an emergency event occurs. It is understood that the emergency is characterized by limited time and information, harmfulness and uncertainty, and decision‐makers are always critically bound by ...
Uncertainty measures for probabilistic hesitant fuzzy sets in multiple criteria decision making
This contribution reviews critically the existing entropy measures for probabilistic hesitant fuzzy sets (PHFSs), and demonstrates that these entropy measures fail to effectively distinguish a variety of different PHFSs in some cases. In the ...
Discovering genomic patterns in SARS‐CoV‐2 variants
SARS‐CoV‐2 is a novel severe acute respiratory syndrome‐like coronavirus (SARS‐CoV), which is responsible of the ongoing world pandemic of COVID‐19 disease. Although many approaches are being investigated to address this issue, nowaday there are ...
Efficiently mining erasable stream patterns for intelligent systems over uncertain data
Data mining is a method for extracting useful information that is necessary for a system from a database. As the types of data processed by the system are diversified, the transformed pattern mining techniques for processing these type of data ...
IPBSM: An optimal bribery selfish mining in the presence of intelligent and pure attackers
Blockchain is a “decentralized” system, where the security heavily depends on that of the consensus protocols. For instance, attackers gain illegal revenues by leveraging the vulnerabilities of the consensus protocols. Such attacks consist of ...
Complex q‐rung orthopair fuzzy 2‐tuple linguistic Maclaurin symmetric mean operators and its application to emergency program selection
This essay designs an innovate approach to work out linguistic multiattribute group decision‐making (MAGDM) issues with complex q‐rung orthopair fuzzy 2‐tuple linguistic (Cq‐ROF2TL) evaluation information. To begin with, the conception of Cq‐...
An efficient secure k nearest neighbor classification protocol with high‐dimensional features
k Nearest neighbor (kNN) classification algorithm is a prediction model which is widely used for real‐life applications, such as healthcare, finance, computer vision, personalization recommendation and precision marketing. The arrival of data ...
A method for combining conflicting evidences with improved distance function and Tsallis entropy
For the sake of great ability of handling uncertain information, Dempster‐Shafer evidence theory is extensively used in information fusion. Nevertheless, when there exists highly inconsistent evidences, using classical Dempster's combination rule ...
Garra Rufa‐inspired optimization technique
Natural selection has inspired researchers to develop and apply several intelligent optimization techniques in the past few decades. Generally, in artificial intelligence optimization, the particles follow a local or global best particle until ...
Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm
The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital ...
