Recently, new methods have been recommended to solve fully fuzzy linear programming (FFLP) issues. Likewise, the present study examines a new approach to solve FFLP issues through fuzzy decision parameters and variables using triangular fuzzy numbers...
Nowadays, because of the energy crisis, combined heat and power systems have notable benefits. One of the best devices is SOFC (Solid Oxide Fuel Cell) which joins heat and power frameworks. Some considerable failure modes arise that can affect these...
Sylvester Matrix Equations (SME) play a central role in applied mathematics, particularly in systems and control theory. A fuzzy theory is normally applied to represent the uncertainty of real problems where the classical SME is extended to Fully Fuz...
Fully connected (FC) layers are used in almost all neural network architectures ranging from multilayer perceptrons to deep neural networks. FC layers allow any kind of symmetric/asymmetric interaction between features without making any assumption a...
This paper presents a new approach for solving FFLP problems using a double parametric form (DPF), which is critical in decision-making scenarios characterized by uncertainty and imprecision. Traditional linear programming methods often fall short in...
High noise resistance and high boundary fitting accuracy have always been the goals of image classification. However, the two mutually constrain each other, making it extremely difficult to reach equilibrium. To deal with this problem, the unsupervis...
There are numerous models for solving the efficiency evaluation in data envelopment analysis (DEA) with fuzzy input and output data. However, because of the limitation of those strategies, they cannot be implemented for solving fully fuzzy DEA (FFDEA...
The problem of bilevel decision-making under multi-expert uncertain information is addressed in this paper. Traditional fuzzy bilevel models are unable to accurately quantify expert consensus and capture evaluation hesitation. To overcome these limit...
Uncertainty is the biggest issue when modeling real-world multi-level fractional optimization problems. In this paper, a fully intuitionistic fuzzy multi-level multi-objective fractional programming problem (FIF-MLMOFPP) is tackled via two different...
In this paper, the fixed-time and preassigned-time synchronization issues of fully quaternion-valued fuzzy memristive neural networks are studied based on the dynamic event-triggered control mechanism. Initially, the fuzzy rules are defined within th...
An investigation is conducted in this paper into a performance analysis of fully intuitionistic fuzzy multi-objective multi-item solid fractional transport model (FIF-MMSFTM). It is to be anticipated that the parameters of the conveyance model will b...
To address the challenge of effective roof support in fully mechanized excavation roadways, this paper proposes an adaptive control method for the initial support force of self-shifting temporary supports based on pressure sensors. First, the mechani...
The adaptive fuzzy fault-tolerant formation control of nonlinear high-order fully actuated multi-agent systems is studied in this paper, which contains time-varying delays and nonlinear non-affine faults. In contrast to the state-space approach, the...
Most textile manufacturing companies in the world heavily rely on manual labor, particularly in the fabric inspection section, especially for cotton fabric. Establishing smart manufacturing systems like industrial automation in the textile industry f...
This paper studies Jaccard similarity under a fully coupled one-factor scoring policy in which all coordinates of an interval-valued fuzzy soft profile are governed by the same parameter. Each interval runs from confidence-discounted evidence to the...
The primary objective of the research presented in this article is to introduce an artificial neural network that demands less computational power than a conventional deep neural network. The development of this ANN was achieved through the applicati...
Fuzzy Linear Programming (FLP) has addressed the increasing complexity of real-world decision-making problems that arise in uncertain and ever-changing environments since its introduction in the 1970s. Built upon the Fuzzy Sets theory and classical L...
In this study, a typical transportation problem involving intuitionistic fuzzy-type variables and parameters is focused on. The approaches proposed in the literature for such transportation problems have many shortcomings, such as the use of ranking...
This study proposes a two-stage MCDM model that combines Delphi and decision-making trial and evaluation laboratory methods based on spherical fuzzy sets (SF-Delphi and SF-DEMATEL) to analyze the motivation and demotivation factors affecting employee...
This work introduces a fuzzy optimization model, which solves in an integrated way the berth allocation problem (BAP) and the quay crane allocation problem (QCAP). The problem is solved for multiple quays, considering vessels’ imprecise arrival times...
In this paper, a novel approach combining fuzzy data envelopment analysis (DEA) and the analytical hierarchical process (AHP) is proposed to rank units with multiple fuzzy criteria. The hybrid fuzzy DEA/AHP approach derives the AHP pairwise compariso...
Ordered fuzzy numbers are defined by Kosiński. In this way, he was going to supplement a fuzzy number by orientation. A significant drawback of Kosiński’s theory is that there exist such ordered fuzzy numbers which, in fact, are not fuzzy numbers. Fo...
Intuitionistic fuzzy entropy is an important concept to describe the uncertainty of intuitionistic fuzzy sets (IFSs). To fully measure the fuzziness of IFSs, this paper comprehensively considers the deviation between membership and non-membership and...
The article portrays an adaptive control paradigm for the swift response of a solid-oxide fuel cell (SOFC) in a grid-connected microgrid. The control scheme is based on an adaptive feedback-linearization-embedded fully recurrent NeuroFuzzy Laguerre w...
The classes in fuzzy classification schemes are defined as fuzzy sets, partitioning the feature space through fuzzy rules, defined by fuzzy membership functions. Applying fuzzy classification schemes in remote sensing allows each pixel or segment to...
In fuzzy set theory, t-norms and t-conorms are fundamental binary operators. Yager proposed respective parametric families of both t-norms and t-conorms. In this paper, we apply these operators for the analysis of Pythagorean fuzzy sets. For this pur...
Through a combination of overlap functions (which have symmetry and continuity) and a fuzzy
Naïve Geography, intelligent geographical information systems (GIS), and spatial data mining especially from social media all rely on natural-language spatial relations (NLSR) terms to incorporate commonsense spatial knowledge into conventional GIS a...
In order to meet the requirements of high precision and fast response of permanent magnet direct drive (PMDD) wind turbines, this paper proposes a fuzzy proportional integral (PI) controller associated with a new control strategy for wind turbine con...
Modern general system theory proposed a holistic integrative approach based on input-state-output dynamics as opposed to the traditional reductionist detail based approach. Information complexity and uncertainty required a fuzzy system theory, based...
In order to solve the problem that the existing low-carbon vehicle scheduling model ignores the economic benefits of enterprises and cannot fully reflect the fuzzy needs of customers, the green simultaneous pick-up and delivery vehicle scheduling pro...
The river ecosystem has the characteristics of the coexistence of clarity and ambiguity. The starting point of eco-friendly reservoir operation is to fully consider the ecological water requirements of the lower reaches of the reservoir, so it also h...
The transition toward renewable energy in agricultural pumping requires robust decision-making tools capable of addressing multiple, often conflicting criteria. This study investigates the respective contributions of fuzzy weighting and fuzzy ranking...
In this paper, a new method for the solution of distribution problem in a fuzzy setting is presented. It consists of two phases. In the first of them, the problem is formulated as the classical, fully fuzzy transportation problem. A new, straightforw...
The mathematical structure of some natural phenomena of nonlinear physical and engineering systems can be described by a combination of fuzzy differential equations that often behave in a way that cannot be fully understood. In this work, an accurate...
This paper proposes a framework for generating symmetric two-branched copulas directly from fuzzy implications via monotone function composition. The proposed approach is based on a two-branched composition principle induced by fuzzy implications and...
The selection of a pharmaceutical e-commerce platform is a typical multi-attribute group decision-making (MAGDM) problem. MAGDM is a common problem in the field of decision-making, which is full of uncertainty and fuzziness. A probabilistic hesitant...
Fuzzy time series forecasting has gained significant attention for its accuracy, robustness, and interpretability, making it widely applicable in practical prediction tasks. In classical fuzzy time series models, the lag order plays a crucial role, w...
In this paper, a MIMO (Multi-Input Multi-Output) fuzzy sliding mode control method is proposed for a three-axis inertially stabilized platform. This method is based on the MIMO coupling model of the three-axis inertially stabilized platform in which...
The air suspension system’s superior variable stiffness, low vibration frequency, and resistance to road impacts significantly elevate both the comfort of vehicle occupants and the overall ride quality. By effectively controlling the air suspen...
With the development of service-based and cloud-based architectures, the number of web services is rapidly increasing, and when users use these services, they expect reliability, security, and performance. However, existing trust evaluation approache...
The numerous interconnected biochemical pathways that make up the metabolism of a living cell comprise a fuzzy logic system because of its high level of complexity and our inability to fully understand, predict, and model the many activities, how the...
Trapezoidal positive/negative fuzzy numbers have no single definition; instead, various authors define them in relation to different concepts. This means that arithmetic operations for trapezoidal fuzzy numbers also differ. For the operations of addi...
The advent of Industry 4.0 has ushered in a new era of technological advancements, particularly in integrating information technology with physical devices. This convergence has given rise to smart devices and the Internet of Things (IoT), revolution...
The model of interval-valued intuitionistic fuzzy soft sets is a novel excellent solution which can manage the uncertainty and fuzziness of data. However, when we apply this model into practical applications, it is an indisputable fact that there are...
This study presents a method of controlling robots based on fuzzy logic to eliminate the effect of uncertainties that are generated by the cutting forces in milling process. The common method to control industrial robots is based on the robot dynamic...
The main goal of the approach proposed in this study, which is dedicated to the extraction of bone structures of the knee joint (femoral head, tibia, and patella), was to show a fully automated method of extracting these structures based on atlas seg...
Aiming at the problem that existing intuitionistic fuzzy entropy measures fail to fully balance the interaction between intuition (determined by hesitation degree) and fuzziness (characterized by the difference between membership degree and non-membe...
With the continuous development of the shipping industry, suction dredgers play a crucial role as functional vessels for channel dredging. The reamer, as the core component of a cutter suction dredger, significantly impacts the energy consumption of...
Network public opinion is a mirror reflecting people’s will, and evaluating its urgency can help to find hidden social crises. Research on public opinion in the field of machine learning usually focuses on micro-sentiment judgment, which is una...
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