This paper considers the yaw-moment control issue for uncertain electric vehicle systems with sensor failures and actuator saturation. By employing the interval type-2 (IT2) fuzzy approach, the uncertain electric vehicle systems are constructed as an IT2 fuzzy model. In this model, the parameter uncertainties are described through the membership functions (MFs) with lower and upper bounds. Then, an

The aim of this study is to propose a novel multi-criteria group decision-making method using analytic hierarchy process and hesitant probabilistic fuzzy linguistic set to model uncertainties due to both fuzziness and randomness. The proposed multi-criteria group decision-making method first uses analytic hierarchy process to construct decision preference matrix. Then, it uses hesitant probabilistic

This article introduced a new multi-attribute information classification method by employing intuitionistic fuzzy set (IFS) approach. The proposed method was referred as four-way intuitionistic decision space (4WIDS). In the 4WIDS, IFS theory was used to model the inherent uncertainty of multi-attribute information. For generating more precise level of decision-rules, granular computing (GrC) approach

Bimatrix games are reconsidered under assumption that players are loss averse and payoffs are fuzzy, where reference points are given exogenously. The impact of loss aversion on bimatrix game is investigated by applying credibility theory. Three solution concepts of credibilistic loss aversion Nash equilibria (i.e., expected loss aversion Nash equilibrium, optimistic loss aversion Nash equilibrium

Air pollution is one of the main environmental issues faced by most countries around the world. Forecasting air pollution occurrences is an essential topic in air quality research due to the increase in awareness of its association with public health effects, and its development is vital to managing air quality. However, most previous studies have focused on enhancing accuracy, while very few have

As a typical multiple criteria comprehensive evaluation (MCCE) problem, healthcare insurance audits (HIA) play a vital role in governmental audits. To handle the HIA in an autonomous region in China, a systematic methodology in the framework of MCCE is presented. An evaluation system is constructed at first based on the specific auditing objective. The group of individual preferences is collected by

Adaptive neuro-fuzzy inference systems (ANFISs) deriving from big data bring us the perspective in many fields. However, online performing both processing noisy and massive databases (NMDs) and training ANFISs is a challenge. Inspired by this aim, we propose a strategy with two phases, offline and online. The offline discovers an optimal data screening threshold (ODST) which is interpreted as an index

Various researches have been performed with video abstraction with the constant development of multimedia technology. However, there are some deficiencies that have been encountered in the pre-processing of video frames before attaining classified video archives. To overcome the drawbacks in pre-processing, feature extraction and classification approaches are considered. Here, video indexing has been

In multi-attribute two-sided matching (MATSM) problems, the attribute weights play an important role. The existing methods usually neglect the interaction and the effect among multiple attributes, resulting in irrational matching results. This paper takes this interaction into consideration. With the complexity of the matching environment, the uncertainties of agents should be considered. The probabilistic

Some aggregation operators with distance measures have been proposed, but distance measure values play the role of argument variables. In this paper, the induced ordered weighted averaging (IOWA) operator with the Hamming distance is proposed, termed as the distance induced ordered weighted averaging (DIOWA) operator. The most distinctive characteristic of the DIOWA operator is that the distance measure

This research is mainly focused on the accurate estimation of the confinement effect for the concrete-filled steel tubular (CFST) that makes it possible to evaluate the interaction between various parameters that affect the confinement effect. To do that, the CFST is analyzed with concrete and steel properties using ANFIS method. With respect to the shape of the CFST, both the circular and rectangle

To achieve better trajectory tracking of the autonomous ground vehicle (AGV), a dual-motor autonomous steering structure and control method are proposed. The model predictive control (MPC) algorithm is utilized to calculate the optimal front wheel angle in real time based on the vehicle information, and dual-motor steering system follows the target angle to achieve trajectory tracking. In this process

This paper presents a novel design for the kinematic control structure of the wheeled mobile robot (WMR) path planning and path-following. The proposed system is focused on the implementation of practical real-time model-free algorithms based on visual servoing. The mainframe of this study is to implement a novel kinematic control structure based on visual sevoing and hybrid algorithms in real-time

In this paper, an improved Type2-NPCM clustering algorithm based on improved adaptive particle swarm optimization called Type2-NPCM-IAPSO is proposed. First, a new clustering algorithm called Type2-NPCM is proposed. The Type2-NPCM algorithm can solve the problems encountered by the algorithms FCM, G-K, PCM and NPCM (sensitivity to noise or aberrant points and local minimal sensitivity), etc. Second

This paper studies the adaptive tracking control problem for a class of nonstrict feedback nonlinear systems with quantized inputs and actuator faults. Compared with existing works on quantized control problem, the asymmetric hysteresis quantizer is considered in the actuator failure problem in this paper. To resolve the control challenge caused by the quantization effect, a nonlinear decomposition

Interval rough numbers play an important role in dealing with complex fuzzy relationships. In this paper, a group decision-making (GDM) model based on interval rough multiplicative reciprocal (IRMR) matrix is proposed. Firstly, the inconsistency, satisfactory consistency and complete consistency of the IRMR matrix are defined from the perspective of set theory. Secondly, an improved method for the

A variable-fuzzy-predictor-based predictive control approach is presented to solve the dynamic trajectory tracking problem of an autonomous underwater vehicle (AUV) in a three-dimensional underwater environment. To adapt to the characteristics of AUV’s motion such as nonlinearity and time-varying dynamics, a predictive controller framework is proposed based on a variable fuzzy predictor whose structure

In this paper, the design problem of intelligent ship autopilot with unmeasured yaw rate and input saturation is investigated based on adaptive fuzzy control. First, an adaptive fuzzy output feedback controller is proposed, then, to improve the convergence speed of the tracking error in the sense of finite time, a finite-time adaptive fuzzy output feedback controller is also designed to improve the

This paper proposes a novel cooperative control method based on cyclic pursuit algorithm and fuzzy control idea, to accomplish reconfiguration of multi-agent formation in 3D space. The idea is to use nonlinear cyclic pursuit control within the formation’s longitudinal motion plane, and use fuzzy control-based piecewise proportional derivative (PD) controller for cooperative control in the normal direction

In this paper, a Pythagorean fuzzy decision-making method based on overall entropy is presented. First, a new definition is proposed for fuzzy entropy for any given Pythagorean fuzzy set (PFS). The proposed definition is based on the relationship between the fuzziness contained in the given PFS and the distance from a point to a line on a projection plane. Some related properties are introduced. Second

This paper develops an adaptive robust control scheme combined with optimal design for the unmanned helicopter tail reduction (UHTR) system. The dynamical model of the UHTR system with uncertainties is established. The uncertainties are assumed to be bounded and expressed by fuzzy set theory. With this prerequisite, an adaptive robust controller is proposed to drive the system to meet the trajectory

In this paper, the issues about weighted \(H_\infty\) performance analysis and \(H_\infty\) control for the stochastic switched nonlinear systems (SSNSs) with multiplicative noise are investigated. The mode-dependent average dwell time (MDADT) method is used to deal with the switching in different modes. Firstly, we get a sufficient condition to show that the considered system with all stable subsystems

The present paper proposes a number of models for calculating the average efficiency of two-stage networks using DEA and DEA-R with fuzzy data. If the input, intermediate, and output parameters are available in a two-stage network, DEA and DEA-R models can be used to compute the efficiency. When evaluating decision-making units (DMUs) in two-stage network DEA, the respective programming models are

This paper has proposed a classification rule base mining algorithm combining the genetic algorithm and intuitionistic fuzzy-rough set for large-scale intuitionistic fuzzy information system. The algorithm has proposed innovatively the definitions and measurement metrics of completeness, interaction and compatibility describing the whole rule base, and constructed a multi-objective optimization model

Mitotic counts are widely used as a metric for cellular proliferation for prognosis and to determine the aggressiveness of individual cancers. This study presents a less labor-intensive method to count mitotic cells in breast cell sections. The proposed algorithm involves two phases: candidate segmentation and detection. During candidate segmentation, images are filtered through a blue ratio threshold

In the magnetically coupled resonant wireless power transfer (MCR-WPT) system, parameter variations of the resonant network will cause the resonant frequency drift, which will make the system in the detuning state. The detuning will increase the required capacity of the power supply and reduce the transfer efficiency of the system. To solve this problem, this paper analyzes the relation between the

In this paper, we propose some developments in fuzzy graph theory. An original notion of a T-spherical fuzzy graph is presented as a commonality of fuzzy graph, an intuitionistic fuzzy graph and a picture fuzzy graph. The originality, the imperativeness and the importance of this notion are discussed by showing some results, giving examples and graphical analysis. Some theoretical terms of graphs such

Marine ranching can increase the harvesting capacity of many species and help achieve planned and purposeful production of marine resources. However, marine ranching ecological security (MRES) has received limited attention, which has affected the management of marine ranching. To provide decision support for the management of MRES in China, we obtained the influence paths of MRES in China using probabilistic

In the causal relationship, a mediator variable is a variable that causes mediation in the dependent and the independent variables. If x is a predictor and y is a response variable, then w is a moderator variable that influences the causal relationship of x and y. A moderator variable is a variable that affects the strength of the relationship between a dependent and independent variable. When there

This paper proposes a new kinematic controller (KC) when designing an autonomous mobile robot with type of differential-drive model in trajectory tracking control. The KC is responsible for creating the reference values of velocities transmitted to the robot dynamics. To design the KC, we present a simple and effective way of actualizing the KC based on the extended nonlinear kinematic model of the

The polygonal fuzzy set is an effective tool to approximate the general fuzzy set by means of a finite number of ordered real numbers. It not only overcomes the shortcomings (which does not satisfy the closeness) of arithmetic operations of fuzzy sets based on Zadeh extension principle, but also realizes the non-linear operation of general fuzzy sets by an ordered representation of the polygonal fuzzy

In this paper, the problem of event-triggered adaptive fuzzy tracking control for nonlinear systems with external disturbance is explored. The fuzzy logic system method is utilized to design the event-triggered adaptive controller under two different event-triggered mechanisms to ensure that the tracking error converges to zero in any small neighborhood, and all the signals in the closed loop systems

In the field of information fusion and decision making, integral is very common and important for aggregating a large variety of information. The integral to be used is usually nonlinear due to the nonadditive measure determined by the real world. In this study, we put forward a new nonlinear integral, which is first expressed as an interval, containing the infimum and supremum of the integrand on

In hospital operation management, the medical supplier selection is a significant problem in which experts’ domain knowledge plays a critical role in selecting medical suppliers. The probabilistic linguistic preference relation (PLPR) whose elements are probabilistic linguistic term sets (PLTSs) is an effective tool to express experts’ preferences on alternatives based on pairwise comparisons. Due

The nature of supply chains presents a variety of issues related to uncertainties. Under various uncertainties, risk management plays a crucial role in an effective supply chain decision-making. The uncertainty involved in the risk assessment process can be divided into two types: random uncertainty and epistemic uncertainty. Fuzzy theory has been applied to deal with uncertainties. The purpose of

The selection of appropriate renewable energy sources (RESs) for a region is a complex multi-criteria decision-making problem because the RES selection process involves many factors, such as economic, environmental, technological and societal. Hence, to address this problem, this paper proposes a multistage framework for selecting a suitable RES alternative by integrating picture linguistic fuzzy numbers

Nowadays the use of fuzzy logic has been increasing in popularity, and this is mainly due to the inference mechanism that allows simulating human reasoning in knowledge-based systems. The main contribution of this work is using the concepts of fuzzy logic in a method for dynamically adapting the main parameters of the harmony search algorithm during execution. Dynamical adaptation of parameters in

This document presents a proposal of structuring the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) twice normalized. Instead of using Euclidean distances, TOPSIS was reckoned by the ellipse length because it was necessary to observe a distance without the basic assumption about to know the way where the “pulse” might go it. The dataset was observed by other works without

The statistic of global laptop shipment showed that 161.6 million laptops were sold, 65.23% more than desktop-PCs, and almost the same quantity as tablets in 2017. So, laptop demand is quite high and needs to be researched on what kind of criteria (properties) are crucial. Since there are more than one criteria, this study focuses on multi-criteria decision-making (MCDM) methods in selecting laptops

Nowadays innovation is a key issue in all business sectors, maintaining a positive correlation with the countries’ economic development. The banking sector stands out among the different economic sectors, as globalization has pushed banks into tough competition. Hence, banks within this competitive framework must innovate by developing new products to be competitive and survive. The innovation in banking

Ontology-based similarity measures have received much importance in recent years. In many real-world cases, the domain considered in the ontological similarity assessment consists of uncertainty or incomplete information. Such vagueness has led to the successful implementation of fuzzy ontology (FO)-based similarity measures. Despite various applications of FO-based similarity measures, limited methods

This paper focuses on Bayesian inference for the parameters of the generalized exponential model under asymmetric and symmetric loss functions when the observations are described in terms of fuzzy numbers. First, a generalized likelihood function based on fuzzy data is derived. Then, considering general entropy, linear exponential and squared error loss functions, the Bayes estimates of the parameters

In powered ankle–foot prostheses, multilevel hierarchical control systems are usually used with predetermined parameters (tuned during the prosthesis trial). Therefore, control systems cannot adaptively interact with terrains variation where control systems is most effective for ground level walking and less effective for ascending or descending stair/slop. In order to address the control system performance

The study proposes a novel, convenient and dimensionless model of multi-criteria decision-making (MCDM), hereby referred to as Grey Absolute Decision Analysis (GADA) method. The foundation of the GADA method rests upon the Absolute Grey Relational Analysis (Absolute GRA) model and the system that the method follows to produce GADA Indexes and GADA Weights. The GADA Weights represent the relative weights

Data envelopment analysis (DEA) is a prominent technique to make decisions and improve alternatives based on non-parameter modeling and ratio calculation. However, an obvious difficulty to use this method is how to obtain accurate input and output data in the real application. To address this issue, the fuzzy DEAs (FDEAs) are proposed which have been successfully applied in many real fields. The FDEAs

The magnetic shape memory alloy (MSMA)-based actuator, as a new type of actuator, has a great application prospect in the micro-precision positioning field. However, the input-to-output hysteresis nonlinearity largely hinders its wide application. In this paper, a Takagi–Sugeno fuzzy neural network (TSFNN) model based on the modified bacteria foraging algorithm (MBFA) is innovatively utilized to describe

Deep neural network (DNN) has been applied in many fields and achieved great successes. However, DNN suffers from poor robustness for uncertainties because of its characteristic of the deterministic representation. To overcome this problem, a novel robust DNN (RDNN) is designed in this paper. First, a fuzzy denoising autoencoder (FDA) is developed to replace the general base-building unit in DNN. Then

This paper investigates the stabilization problem of a class of singular fractional order fuzzy systems with order \(0<\alpha <1\). Firstly, by the method of full rank decomposition of matrix, equality constraint of admissibility criterion in most existing literature is eliminated. Next, we present a stabilization criterion for singular fractional order Takagi–Sugeno (T–S) fuzzy systems by designing

Under unbalanced grid conditions, the DC side voltage of pulse width modulation (PWM) rectifier will overshoot during start-up and reference voltage transients, which may lead to system instability. In this paper, a deadbeat predictive power control (DPPC) with fuzzy PI compound controller (FPCC) and power predictive corrector (PPC) is proposed to solve that problem. Firstly, the parameters of the

Data envelopment analysis (DEA) is a non-parametric methodology for efficiency assessment. This paper proposes a new radial, input-oriented and fully fuzzy DEA approach, based on an LU-fuzzy partial order (L for lower, U for upper), for assessing the relative efficiency of a set of Decision-Making Units (DMUs). The proposed approach involves a radial input contraction, Phase I, and an additive slacks

In risk investment, investors have to rely on uncertain information when it is difficult to obtain enough precise data. Dual hesitant fuzzy set (DHFS) is more applicable to deal with uncertain information because it involves membership degrees and non-membership degrees, which can validly describe positive and negative information, respectively. Although there has been research on decision-making based

Nowadays, the research for chaotic dynamics in the social science has been interested by many researchers. This paper proposes a fuzzy controlling method for dynamic confliction model between certain group A and group B based upon love affairs model. In order to control the confliction between group A and group B, we apply control input with the symmetry triangular fuzzy numbers, which are special

This article proposes a framework to deal with incomplete information in multiple criteria group decision making with intuitionistic fuzzy soft set. To do that, the weighted sum method for choice values and simple mathematical expectation method are extended to the case of obtained fuzzy soft set, and they are proved to have the same result in estimating the incomplete information. In order to reduce

In this paper, a novel adaptive fuzzy controller is developed for the uncertain fractional-order switched nonlinear systems whose output is quantized by a class of sector-bounded quantizers. Since the states are not completely measurable, an observer with quantized output signal is designed to estimate the unknown system states. Meanwhile, based on the fractional Lyapunov stability criterion, the Lyapunov

Today’s modern decision-making problem is designated by not being the most effective fuzziness; however, additionally partial reliability also plays a crucial role. The incomplete and unreliable information may also affect the selection maker to earn inaccurate decisions, ensuing in monetary losses and wastes of resources. Thus, it is vital to describe the reliability of the facts. To cope with it

Online customer reviews (OCRs) provide much information about products or service, but the mass of information increases the difficulty for customers to make decisions. Thus, we establish a multi-criteria decision making (MCDM) model to evaluate products or service. To analyze OCRs, the sentiment analysis (SA) is introduced to identify the sentiment orientation of reviews. Considering that the textual

In this paper, a T–S (Takagi–Sugeno) adaptive tracking algorithm control based on small gain theorem is proposed for an uncertain robot system with \(n\)-link manipulators. A nonzero time-varying parameter is introduced in the common T–S fuzzy logic system, the T–S type fuzzy logic system with updated parameters laws is build, then the new and original universal approximation with parameter is introduced

In this paper, Decomposed Fuzzy Systems (DFS) structure is applied to design single intersection signal fuzzy controller. The DFS structure is to decompose each fuzzy variable into layers of fuzzy systems and each layer is to characterize one traditional fuzzy set. DFS adjusts the fuzzy membership function, the leading part, and enriches the fuzzy rule base through structural changes, thus provides

In this paper, we consider interval multi-objective linear programming (IMOLP) models which are used to deal with uncertainties of real-world problems. So far, a variety of approaches for obtaining efficient solutions (ESs) of these problems have been developed. In this paper, we propose a new and two generalized methods. In the new method, converting IMOLP into an interval linear programming (ILP)

This paper deals with the problem of the fault-tolerant fuzzy master–slave systems synchronization through an adaptive event-triggered scheme (AETS). First, a Takagi–Sugeno (T–S) fuzzy model is employed to represent the master–slave system dynamics. Second, an AETS is introduced to judge whether the newly sampled controller’s signals should be released to the slave system or not. Consequently, the