Recommender systems have been exhaustively implemented in the e-commerce industry for providing accurate, efficient, and effective personalized recommendations to candidate users. The variants of matrix factorization (MF) techniques incorporating the stochastic gradient descent (SGD) are exploited to improve the efficacy of recommender systems through effectively dealing the fuzzy behavior. The iterative

Probabilistic linguistic Z number (PLZN) is considered as an effective information representation model. It not only describes the decision-making information, but also demonstrates its reliability. To handle the increasing problems of complexity and uncertainty in real-life, PLZN is widely used to indicate qualitative information. In this paper, a novel decision-making method with PLZNs is proposed

This paper proposes an adaptive Pareto optimal control scheme for a general class of multi-objective T–S fuzzy systems subject to input constraints. Firstly, the fuzzy state feedback controller is employed to close the augmented system. Then, based on linear matrix inequality (LMI), a novel multi-objective optimizer is proposed for pre-regulation of the control gains to simultaneously minimize H2/H∞

This paper addresses the finite-time adaptive fuzzy control for multi-input and multi-output (MIMO) nonstrict-feedback nonlinear systems with fuzzy dead zones. Combining the semi-global practical finite-time stability criterion with the condition of variable partition, a feasible finite-time adaptive fuzzy control scheme is proposed for the developed MIMO system. The designed control algorithm guarantees

In this paper, a novel asymmetric Lyapunov–Krasovskii functional (LKF) method for the stability of Takagi–Sugeno (T–S) fuzzy systems with time-varying delay is proposed. This asymmetric LKF method is shown to effectively reduce conservatism compared with symmetric LKF method. For further improving the stability criterion, the method is combined with the improved membership-function-dependent technique

Analytical hierarchy process (AHP) has been prevailing in multicriteria decision-making (MCDM) problems. Meanwhile, the fuzzy sets family has shown great power in representing vagueness and advancing the decision quality under uncertainties. The literature well documented the foundation and advantages of their integration, such as Fuzzy AHP. However, under what conditions do such integrations surely

Counter deception is one of the main content in data fusion. The existence of deceptive data may cause great hidden dangers to the generation of correct decisions. While among previous studies, whether evidence should aggregate is still virgin and may become a fascinating question. In this paper, a new counter deception model based on the Shapley value methodology is proposed, which provides a perspective

In this paper, the problem of adaptive fuzzy proportional-integral output feedback tracking control is investigated for a class of uncertain switched nonlinear systems with dead-zone output, unknown control coefficients, and unmodeled dynamics. The unknown parameter of the dead-zone output is processed using adaptive estimation technique. A set of switched filters are developed to estimate unmeasurable

In this paper, a robust and enhanced evolutionary computing assisted Takagi Sugeno (T–S) fuzzy controller was developed for automotive fuel injection control. To augment the rule generation and fuzzy parameter estimation, we propose an enhanced evolutionary computing algorithm named Hierarchical Adaptive Genetic Algorithm (HAGA). The proposed HAGA model was applied to augment T–S fuzzy controller that

In view of the high dynamic, uncertain and time-varying characteristics of unmanned combat aerial vehicle (UCAV) air combat situation, a maneuver decision method based on fuzzy reasoning is proposed. Firstly, four advantage factors of angle, distance, speed, and height are established from the air combat scene. Secondly, the fuzzy rules are used to evaluate the air combat situation. The advantage factors

This study proposes an efficient estimator and uses it to estimate the health of a lithium-ion battery and a supercapacitor in the hybrid energy storage system (HESS). A new type of online health estimator that uses a fuzzy brain emotional learning neural network (FBELNN) is proposed. This neural network is different to a conventional brain emotional learning neural network where the fuzzy inference

This paper addresses the fuzzy adaptive containment control problem for nonlinear multi-agent systems with unknown external disturbance and input quantization under a directed graph. Firstly, the quantized input signal and unknown external disturbance are simultaneously considered in the pure-feedback multi-agent systems. Fuzzy logic systems and disturbance observers are used to deal with unknown nonlinear

This paper proposed an assistive robot design for lower limbs rehabilitation using fuzzy control. A robot is developed to rejuvenate stroke patients’ nervous system of motor function by exercising their lower limb appropriately, to slow down motor function degradation, rebuild or strengthen the patient's motor function. Thus, the motion of robot must be driven from the sole of the patient and the shank

In this investigation, a fuzzy-based micrometer level control design with a guaranteed trajectory tracking performance for piezoelectric actuators which naturally have hysteresis effects is proposed. Nominal dynamics of the controlled piezoelectric actuators are described by adopting Takagi and Sugeno fuzzy models initially. Via interpolating Takagi and Sugeno local fuzzy model, a robust fuzzy-based

Although in line with the resource-based view (RBV), the impact of different HPWS practices on the innovation success of SMEs has been approved by researchers, investigating the previous studies indicates that the relation between these two areas has been more widely considered and less attention has been paid to the impact mechanism. Lack of real data and focus of analysis on respondents’ opinions

Compensatory Fuzzy Logic is a transdisciplinary axiomatic theory, different from the Classical Norm and Conorm approach to improving interpretability by natural language. Archimedean Compensatory Fuzzy Logic (ACFL), introduced recently, uses different properties and interpretations of involved truth values. Membership functions involved are not studied explicitly in fuzzy theories, even though it is

The aggregation of fuzzy information is a key process of MCDM methods used to deal with uncertainties. A class of aggregation methods for fuzzy information is fuzzy distance aggregation operators in which distance values are argument variables. This class of aggregation operators permits us to consider an ideal alternative in the aggregation process. But these operators fall in dealing with situations

This paper focuses on the adaptive fuzzy tracking control problem for a class of stochastic nonlinear systems with nonstrict-feedback structure and dead zone input. By introducing fuzzy logic system, the difficulties caused by unknown nonlinear functions and nonstrict-feedback are overcome. Considering the asymmetric dead zone input, an adaptive tracking controller is constructed by integrating the

Robustness is a major concern when engineers design lateral stability controllers for intelligent vehicles. The system uncertainty derives from the internal parametric perturbation and the external disturbance. The fuzzy set theory is adopted to describe the bound of the uncertainty. Hence the vehicle lateral dynamical system becomes a fuzzy dynamical system. An explicit robust optimal control law

The aim of this paper is to develop the calculus of hesitant fuzzy numbers (HFNs), have been recently proposed as the newest extension of hesitant fuzzy sets. At first, based on the willingness of decision maker to each part of HFNs, a new method has been proposed to compare them. Then, several t-norm and t-conorm-based aggregation operators of HFNs, i.e., algebraic t-norm and t-conorm, Einstein t-norm

This paper designs an event-triggered \({H_\infty }\) filter for interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy nonlinear networked systems with parameter uncertainties and delays. First, an IT2 T–S fuzzy model is used to describe the nonlinear plant and the filter subject to parameter uncertainties, which can be captured with the lower and upper membership functions. Then, an event-triggered scheme

This study proposes the multiobjective \(H_{2}/H_{{\infty }}\) fuzzy control design for a nonlinear stochastic chaotic system via concurrently optimizing \(H_{2}\) and \(H_{{\infty }}\) performance indices in a Pareto optimal sense. Using the Takagi–Sugeno fuzzy model to approximate the nonlinear stochastic chaotic system, the multiobjective \(H_{2}/H_{{\infty}}\) fuzzy control design problem can be

This paper focuses on the finite-time synchronization for fuzzy delayed neutral-type inertial BAM neural networks. Without making the variable transformation, the inertial system was analyzed directly. By applying integral inequality techniques and the figure analysis approach, some novel criteria are achieved to assure the finite-time synchronization between the drive system and the response system

This paper studies the cost consensus model by considering the uncertain initial opinions and uncertain unit adjustment cost in group decision making. In the past consensus model based on optimization, the initial opinion and unit adjustment cost are usually assumed to be a crisp number for each expert. However, the speed of knowledge updating is often faster than people’s cognitive speed, it is difficult

In this paper, a fault-tolerant control scheme is presented for a boiler-turbine unit of a thermal power plant covering a wide range of operations: at low, medium, and high loads. The approach is based on the use of an observer-based actuator fault estimation system to detect and estimate the fault magnitude for a posteriori compensation via a fault-tolerant control scheme. The performance of both

Let us have a population of objects that are subjected to a given event. Each object can be assigned a degree of membership to the population. Assume that for a set of objects, a continuous parameter is measured before and after the given event. We can now form two paired fuzzy samples from the population—Z1 and Z2. We then measure the change ΔZ of Z from Z2 to Z1 and form the fuzzy sample of change

Probabilistic linguistic preference relation (PLPR) is an effective tool for decision-makers (DMs) to express their preferences in the decision-making process. However, the preferences provided by DMs may be inconsistent, which may lead to unreasonable decision-making results. Therefore, this paper proposes a group decision-making (GDM) method with PLPRs based on a consistency improvement algorithm

This paper studies the fuzzy output feedback event-triggered control design method for the uncertain nonlinear systems with the unavailable states. First, an interval type-2 Takagi–Sugeno fuzzy system is utilized to model the nonlinear system, on which a fuzzy state observer is designed to estimate the unmeasured states. Second, via using the estimated states, a event-triggered mechanism is given,

Since the α-planes expression theory of general type-2 fuzzy sets (GT2 FSs) was put forward, the computational complexity of general type-2 fuzzy logic systems (GT2 FLSs) has been greatly reduced. Calculating the centroids of GT2 FSs is an important block for theoretical research of GT2 FLSs. Noniterative algorithms can overcome the disadvantages of being computationally intensive and time consuming

Permanent magnet synchronous motor (PMSM) is one of the most viable motion control products due to the inherent benefits of low rotor inertia, high efficiency and high-power density in industrial applications. The speed control for PMSM is a significant task. Many researchers carried out their research for improving performance of PMSM through speed control. But, the performance and efficiency of PMSM

Oil spills on the ground cause significant damage to the geological environment, including groundwater, contaminating it and making it uninhabitable. Therefore, it is necessary to predict the scale of the oil spill and the consequences of contamination of the geological environment to minimize the damage. In the literature, there are plenty of approaches for oil spill prediction on the water. However

The spread of COVID-19 has triggered one of the largest pandemics in modern human history. Humanity is still in the incomplete information period for this infectious disease, and how to effectively deal with such a major public crisis is a crucial problem. Although there are divergences in human natural semantics, the incomplete information increases it. Therefore, this study integrates the neutrosophic

The data are not always real numbers due to the complexity and uncertainty of the real-world decision environment. This requires us to use probability-based expressions to describe the complex decision-making data in reality. In order to understand the probability-based decision-making information more comprehensively, this paper reviews and summarizes the current development of probability-based decision-making

The vendor managed inventory (VMI) is the most commonly known marketing and distribution methodology among the service provider and the retailer in a supply chain environment. The VMI framework's critical feature is to satisfy the demand of the products or items by the supplier rapidly generated from the retailers with the number of orders (order quantities). Due to the business's changing conditions

In this paper, we propose a fuzzy adaptive lasso (least absolute shrinkage and selection operator) estimate for fuzzy linear regression with crisp inputs and fuzzy outputs. The proposed estimate is obtained by imposing an \(L_1\) penalty on the least-squares error. Compared with fuzzy lasso estimate proposed by Hesamian and Akbari (Int J Approx Reason 115:290–300, 2019), the estimate we proposed assigns

This work focuses on the problem of fault-tolerant control for nonlinear persistent dwell-time (PDT) switched singularly perturbed systems (SPSs) with time-varying delays. The persistent dwell-time switching mechanism is employed to describe the fast and slow switching among several subsystems in the investigated systems alternatively. In order to reduce the influence of actuator faults on system stability

The arithmetic operations given between the Interval Type-2 Trapezoidal Fuzzy Numbers (IT2TrFN)s should satisfy the closeness property. Otherwise, the result encountered when the operations are used may be meaningless and not suitable for the purpose. The aim of this note is to show errors in the definitions using a non-closed division operation given by paper Pan and Wang (Int J Fuzzy Syst 144:1–15

This paper presents a descriptor form design methodology for polynomial fuzzy-model-based (FMB) control systems. To begin with, the closed-loop polynomial fuzzy system is cast into the descriptor form representation. Applying the commonly used Lyapunov function of the polynomial fuzzy model, the first sum-of-squares (SOS) based stabilization control design approach is proposed. Through the redundancy

The warning of membrane fouling is of great important to maintain the stable operation of membrane bioreactor (MBR). However, traditional methods are so error-prone that probably do not acquire reliable solutions of membrane fouling due to its uncertainties. To overcome this problem, an intelligent warning method is proposed to monitor the status of MBR in this paper. The main advantages in this paper

The problem of hotel selection involves lots of uncertain information and multiple factors and can be identified as a multi-criteria decision-making problem. Aiming at the information description, measure, and fusion of hotel selection problems, this study develops multi-criteria decision-making methods based on Z-numbers and their projection measure and fusion techniques. To manage the three-dimensional

Probabilistic linguistic term set (PLTS), an efficient tool to describe decision information, can sufficiently express decision makers’ hesitation and preference. Probabilistic linguistic preference relation (PLPR) is based on PLTSs to describe the preference information of experts for paired alternatives. However, in practice, due to the complexity of the problem, the incompleteness of information

The decision-making process is always associated with uncertainty and vagueness because of the incomplete decision data and unpredictable decision-making behavior. The concurrence of the epistemic uncertainty and the aleatory uncertainty, especially when only the qualitative data are accessible, poses more challenges to the decision-making. The probabilistic linguistic term set provides a flexible

In the era of Internet of Everything (IoE), we are faced with complex patterns of connectivity between people, processes, data, and things. The IoE industry decision making is all important for enterprises or countries to heighten the efficacy of leadership, which can tremendously expedite the large-scale development and industrialization. When considering the IoE companies’ assessment in the IoE industry

In the era of uncertain information everywhere, the Probabilistic Hesitant Fuzzy sets (PHFs), utilizing the possible numbers and its possible membership degrees to descript decision-makers’ behavior, has been brought about widespread attention. Scholars from all over the world applied numerous approaches in this environment since Probabilistic Hesitant Fuzzy sets (PHFs) has been come up with, and there

In the paper, we study the swarm control problem for a high-order self-organized system with unknown nonlinear dynamics and unmeasured states. In previous work, swarm control, which can change the distance between agents when swarm moves, is discussed. However, in practical applications, the high-order states of agents are not easy to be measured, and the unknown nonlinear dynamics in the system are

Developing a sustainable healthcare system directly depends on the level of maturity in environmental, social, and economic practices. Although there are huge number of researches considering environmental, social, and economic aspects, to the best of our knowledge, no approach was found which unifies these dimensions as an integrated method to assess the current status of sustainable development in

Smartphones are essential personal belongings today. However, smartphone buyers (SBs) are often hesitant in deciding what the best smartphone and rate plan to choose offered by telecom providers. Among many new smartphones, it is often difficult for users to choose the most suitable one in consideration of reaching the salient success aspiration level (SSAL) as close as possible, e.g., large battery

In a motor imagery-based brain–computer interface system, an effective classifier is required. However, the effectiveness of classifier is substantially influenced by the individual differences among electroencephalography (EEG) signals and artifacts. Therefore, in this study, we adopted an ensemble method by combining various classifiers, including a fuzzy classifier that can reduce the influence

This study proposed the application of a nanofluid/ultrasonic atomization minimum quantity lubrication (MQL) method to grind Inconel 718 alloys. This is a grinding manufacturing innovation on lubrication technology. Multiwall carbon nanotubes (MWCNTs) and molybdenum disulfide (MoS2) nanoparticles were used as the nanofluid additives. Specifically, MWCNTs exhibit excellent thermophysical properties

This article describes the application of a variant of the shark smell optimization (VSSO) biological inspired algorithm in the optimal design of a type-2 fuzzy controller. We show how the performance of VSSO is based on the frontal and rotational movement of the shark when navigating a dimensional search domain, which is based on the food-seeking behavior of sharks. The optimization of the design

Electrically stimulated lower limb systems contain higher order nonlinearities and uncertainties in their physical parameters. Takagi-Sugeno (TS) fuzzy models are used to model nonlinear systems. Techniques such as parallel distributed compensation (PDC) are dependent on the membership functions that constitute the TS fuzzy model. When the exact representation approach is used to electrical stimulation

The close combination of internet technology and traditional industrial control system (ICS) is a double-edged sword, which not only improves the accuracy of the control system, but also brings great danger. According to the statistics of the authoritative industrial security incident information database, Repository of Industrial Security Incidents (RISI), as of October 2011, there have been more

A certain flexibility of decision makers (DMs) is usually requisite for reaching the consensus in group decision making (GDM). When the judgments of DMs are expressed as fuzzy-valued quantities, the required flexibility has been shown. In this paper, we report a quantification approach to flexibility degrees (FDs) of fuzzy numbers and a consensus model in GDM with fuzzy-valued judgments. First, an

In the classical EOQ model, acquiring cost of an order would be usually paid while receiving its receipt. Sometimes, the supplier may offer the retailer to pay the entire amount or the fraction of acquiring cost in advance as equal number of payments. The present research discusses the EOQ model with substandard products under fuzzy situation. This model deals with the advance payment on acquiring

Online tourist reviews are the real feeling of tourists after the journey, which have a strong reference value for potential tourists to make travel decisions. However, it is almost impossible for a potential tourist to look through the massive online reviews related to tourist attractions (TAs) so that he/she can make the most appropriate decision. To this end, this paper proposes a recommender system

Since social and environmental conditions have changed dramatically in recent years, the spectrum of diseases caused by infections is also evolving rapidly. The outspread of COVID-19 has resulted in an emergency situation across the globe with significant effects on the population’s lives, families, and societies, leading to concerns the World Health Organization. Accordingly, the virus has substantially

The 2019–2020 COVID-19 pandemic has caused an economic turndown and high volatility in the global financial markets. Determining the factors that influence services to high-net-worth customers who typically have large investments in the financial markets is important for wealth management banks. This study constructs a hybrid approach by integrating the fuzzy logic and Decision-making Trial and Evaluation

This paper studies the adaptive fuzzy control issue for a category of stochastic nonlinear multi-agent systems with input hysteresis and saturations in non-affine form. Fuzzy logic systems are employed to approximate the unknown nonlinear functions. By introducing a Nussbaum function, the unknown gain problem caused by input hysteresis and saturation hybrid term can be solved effectively. Based on

In order to reach the free moving requirements of blind man, dogs are usually trained to guide, also as known as guide dogs. However, the number of guide dogs is much lower than actually requirements significantly. In order to improve this issue, the robot guide dogs are proposed. The quadruped design provides good movement for robot guide dogs. On the other hand, the architecture of four legs also

When an emergency occurs, there’s a massive challenge for experts to select the optimal emergency plan for disaster relief, because the decision-making process is full of uncertainty and fuzziness. This paper develops an emergency group decision-making method to help decision-makers choose the optimal emergency plan under probabilistic hesitant fuzzy environment. In the beginning, we offer a novel