The natural gas pipeline construction project possesses different kinds of highly risky occupational hazards because of its complex and dynamic surrounding environments. Occupational risk evaluation is one of the most effective techniques to reduce and manage these risks and hazards. There are various kinds of techniques to address the problem of occupational risk evaluation, however, most of these

High-utility itemsets mining (HUIM) has attracted considerable attention due to its superior performance in discovering the profitable itemsets from databases. Generally, an itemset is discovered as a high-utility itemset (HUI) by HUIM only if its utility (such as profit) is higher than a predefined utility threshold. The previous HUIM methods cannot address the sharp boundary problem and the efficiency

A new stabilization problem for Takagi–Sugeno (T–S) fuzzy systems involving time-varying delay and interval uncertainties is investigated in this paper. Firstly, a new stabilization condition on dynamic output feedback control for T–S fuzzy systems is proposed. Meanwhile, a robust H∞-γ stabilization criterion for T–S fuzzy systems is presented based on Lyapunov–Krasovskii function. In addition, an

After the epidemic, all enterprises are faced with the difficult decision about whether the enterprise should resume work and production immediately, which is related to the safety and development of enterprises. The three-way decisions offer a novel study perspective to solve this problem. Firstly, we describe some relevant attributes of the enterprise with double hierarchy hesitant fuzzy linguistic

A novel distributed fuzzy adaptive control approach is studied for a class of heterogeneous uncertain nonlinear multi-agent systems with different dimensions. Similar definition and property of each agent are introduced, and similar parameters among each agent can be obtained using the proposed properties, then the feedback distributed fuzzy adaptive control based on similar matrices and vectors is

In the design phase of a new smart product, production costs are unpredictable due to location, transport, and engineering design. In these situations, consequently, cost optimization becomes ambiguous. This paper presents a methodology to obtain optimization through a fuzzy linear programming problem (FLPP) in which fuzzy numbers signify the right-side parameters. The comparative investigation of

This paper investigates the multiobjective supplier selection problem (SSP) with type-2 fuzzy parameters. All the involved parameters such as aggregate demand, budget allocation, quota flexibility, rating values, are depicted as type-2 triangular fuzzy (T-2TF) parameters. To tackle the T-2TF, first, critical values (CV)-based reduction method is introduced, and then chance-constrained programming is

Automatic detection of crop yield ripeness is a tedious task because of the presence of various intensities of color in crops. One of the solutions to this problem is the monitoring of those crops by performing segmentation operations. This operation can help to distinguish the ripe and non-ripe regions among the crop images. For this purpose, this study presents a new hybrid crop image segmentation

The steady-state operation and controlled position tracking in ball balancer applications are largely affected due to their nonlinear and underactuated behavior. To overcome these drawbacks, this paper develops a wavelet-based fuzzy controller which operates in closed loop with the system by measuring the ball position and the plate angle. The proposed approach adapts discrete wavelet transform for

This paper proposes an adaptive fuzzy finite-time dynamic surface control method for permanent magnet synchronous motors (PMSMs) with full-state constraints. By combining with the finite-time stability theory, the \(\log \)-type barrier Lyapunov function is constructed to constrain the angular speed, stator current and other state variables of PMSMs in the predefined compact sets. Then, the first-order

An adaptive fuzzy formation control problem is investigated for a nonlinear nonstrict-feedback multi-agent system with unmeasurable state in this paper. Fuzzy logic systems (FLSs) are employed to approximate the unknown nonlinear functions of the nonlinear multi-agent system. A distributed fuzzy state observer is constructed to estimate unmeasurable states. The repeated differentiations problem of

Interval-valued intuitionistic fuzzy sets and vague sets are two sets that are commonly used in expressing vague and uncertain information. Despite their commonality, these two sets are characterized by different memberships. Interval-valued intuitionistic fuzzy sets are characterized by membership and non-membership with the sum of these memberships being less or equal than one. On the other hand

An improved Fuzzy C-Means (FCM) algorithm, which is called Reliability-based Spatial context Fuzzy C-Means (RSFCM), is proposed for image segmentation in this paper. Aiming to improve the robustness and accuracy of the clustering algorithm, RSFCM integrates neighborhood correlation model with the reliability measurement to describe the spatial relationship of the target. It can make up for the shortcomings

The fuzzy aggregation information plays an important role in the group decision support system under the interval-valued hesitant fuzzy information and interval-valued probabilistic hesitant fuzzy information. Therefore, in this paper, we develop a new approach of the interval-valued hesitant fuzzy Frank aggregation (IVHFFA) and interval-valued probabilistic hesitant fuzzy aggregation (IVPHFFA) operators

Traditionally, researchers have focused on network level intrusion detection and program level intrusion detection to improve computer security. However, neither approach is foolproof. Typically, a successful attacker manifests in the form of the attacker becoming a user on the host either with elevated or normal user privileges. The reason for this situation is that current research and technology

This paper addresses the stability and stabilization problems of uncertain Takagi–Sugeno (T-S) fuzzy system with control packet dropout. The process of packet loss is proposed, which is modeled according to some white noise sequences of Bernoulli distribution. Then, under the zero-input strategy, a newly stochastic switched sampled-data controller is introduced. Based on the Lyapunov function method

Optimization is used to find the maximum or minimum of a function. In this research, optimization is applied to the objective function of the FCM algorithm. FCM is an effective algorithm for grouping data, but it is often trapped in local optimum solutions. Therefore, the similarity measure in the clustering process using FCM is very important. This study uses a new method, which combines the Minkowski

The required control force vector is distributed by the thrusters in marine dynamic positioning system (DPS) to obtain the desired thrust and angle of each thruster. The thrust of the thruster is mapped to the speed of the thruster, and the low-level thrust controller adjusts the speed of the thruster to achieve the vessel’s dynamic position. Based on the previous research, the permanent magnet synchronous

In this research, the problem of direct adaptive fuzzy control based on state feedback for a class of non-affine stochastic nonlinear systems with time delay is considered. Fuzzy logic systems (FLSs) and mean value theorem are utilized to overcome the design difficulties appeared in the unknown nonlinearities and non-affine structure, respectively. With the utilization of adaptive control and backstepping

This paper presents a comparative study between the firefly algorithm (FA) and the galactic swarm optimization (GSO) method, where the performance of both methods is observed and tested in the optimization of a fuzzy controller for path tracking of an autonomous mobile robot. The main contribution of this work is finding the best method that generates an optimal vector of values for the membership

Membrane fouling is a widespread problem that restricts the stable operation of membrane bioreactor (MBR) in wastewater treatment process (WWTP). However, it is difficult to avoid the occurrence of membrane fouling due to the lack of effective early warning methods. To deal with this problem, an intelligent early warning method, using a knowledge-based fuzzy broad learning (K-FBL) algorithm, is proposed

With increasing profit in securities investment, portfolio analysis has become a major topic for investors. We propose a fuzzy portfolio model as it is an efficient portfolio selection method associated with uncertain or vague returns. Although many researchers focus on studying the fuzzy portfolio model, they do not consider excess investment based on the selected guaranteed rates of return for some

The purpose of this study is to design a supervisory two-level controller for an autonomous underwater vehicle path following problem despite the underwater uncertain operation conditions and external measurement noises. For the controller description, the surge degree of freedom dynamic model is linearized using feedback linearization technique and then a fuzzy PID tracking control law is sketched

To overcome the insufficiencies of existing information expression and operations of single-valued neutrosophic multisets (SVNMs) and multi-valued/hesitant neutrosophic sets (MVNSs), this study first introduces neutrosophic multi-valued sets (NMVSs), including SVNMs and MVNSs, as a general concept. Then, we propose a method that transforms NMVSs into consistency single-valued neutrosophic sets (CSVNSs)

The fusion of highly conflicting evidence in the Dempster–Shafer evidence theory has been an important research topic. To solve this issue, many existing methods depicted the conflicts between evidence by various distance measures. Although the distances between evidence can reflect the conflicts of evidence to some extent, they only represent one aspect of the conflicts. In this study, we propose

Skills acquisition can be performed using virtual simulators. The issue about assessment of the skills acquired in those environments is a problem not solved since each simulator can collect different interaction data. Data types and distribution can demand specific approaches, i.e, the multiples interaction possibilities between users and virtual simulators do not allow a unified solution. Several

The Internet has provided many platforms for tourists to spread tourism-related information, resulting in a large amount of online review data on tourist attractions. Mining and analyzing online reviews by using modern information technology are of great importance. They affect tourists’ travel decisions and ensure the effective management of tourism attraction managers. We establish a multi-dimensional

Flexible manipulators are widely used in aerospace industry and precision instrument manufacturing industry. However, due to the mechanism flexibility, the system dynamics have high nonlinearity and complexity, which make controller design pretty challenging. Moreover, in real production, electromechanical systems, including flexible manipulators, usually suffer from nonlinear input dead-zones and

To model and deal with complex decision-making problems, many methods have been proposed in the past decades. However, how to deal with probabilistic uncertainty is still an open question. In this regard, this paper introduces a prospect theory-based evidential reasoning (ER) approach to process such uncertainty in multi-expert multi-criteria decision-making. Firstly, we introduce a novel way to model

Solar Photovoltaic (PV) systems are playing a major role in the present electrical energy systems. The solar PV gives nonlinear I–V and P–V characteristics. As a result, it is difficult to extract the maximum power of the solar PV. Under Partial Shading Conditions (PSCs), the solar PV characteristics consist of multiple local Maximum Power Points (MPPs) and one global MPP. The classical Maximum Power

Data envelopment analysis is a useful model for efficiency evaluation. In order to improve the haze pollution in China, it is particularly essential to allocate the PM2.5 emission rights of various provinces according to the actual situation reasonably. However, the expressions of input and output information are often limited or incomplete. Probabilistic linguistic term sets are employed to increase

In the fuzzy clustering process, the clustering number for image or text data to be classified is not easy to determine or unknown. The competitive learning algorithm can automatically determine the optimal clustering number to avoid the problem of inappropriate artificial selection. In this paper, based on the clustering by competitive agglomeration (CA), the idea of the “Competitive Learning Mechanism”

Traditionally in supply chain management suppliers and customers are evaluated independently. This is in spite of the fact that supplier performance has direct impact on the performance of the customer. This research develops a mechanism for simultaneous evaluation and prioritization of supplier and customer using the sustainability metrics comprising economic, environment and social measures. In order

Assessment of the lecturer’s research capacity plays an important role in improving their knowledge and determining each lecturer’s contribution to the universities. To assess the lecturers’ research capacity, many quantitative and qualitative criteria are needed in the evaluation process. Therefore, lecturer’s research capacity evaluation can be viewed as a multi-criteria decision-making (MCDM) problem

Under the background of vigorously promoting the construction of ecological civilization, the importance of constructing the “non-waste cities” becomes increasingly prominent. Taking 39 cities in the Yangtze River Economic Zone as the research objects, this paper establishes a new evaluation index system for “non-waste cities,” and proposes a multi-source, heterogeneous and multi-attribute decision-making

The preference values in group decision-making (GDM) process can differ significantly between different experts, which may yield a low level of group consensus. Therefore, different consensus models have been developed for the modification of preference values to assist experts in improving their consensus degrees. However, most consensus models do not consider collective intelligence (CI) that may

Risk evaluation is a primary but important task for technological innovation projects and this task is a multiple criteria group decision-making (MCGDM) process with probabilistic uncertainty and fuzzy uncertainty. Compromise programming decision-making methods with probabilistic linguistic term sets (PLTSs) are more appropriate for risk evaluation of technological innovation projects. This paper proposes

Ever since the 1970s when the idea of fuzzy linguistic variable was introduced by L. Zadeh, it has been heatedly discussed and widely used in engineering, information science, and many other research fields. With the rapid development and use, thousands of papers have been published on fuzzy linguistic, detailing both theoretical development and application-oriented studies, being a very important

This paper addresses the admissibility analysis and the polynomial fuzzy controller design for a class of singular polynomial fuzzy systems with time-varying delay. Firstly, according to Lyapunov stability theory, a sufficient condition is obtained by means of sum-of-squares (SOS) to ensure that the closed-loop singular polynomial fuzzy system is admissible. Secondly, by the help of the two equivalent

As autonomous ships become the future trend for maritime transportation, it is of importance to develop intelligent autonomous navigation systems to ensure the navigation safety of ships. Among the three core components (sensing, planning and control modules) of the system, an accurate detection of target ships’ navigation information is critical. Within a typical maritime environment, the existence

Underwater walking robot (UWR) is a kind of autonomous underwater vehicles which can walk underwater. In this work, the fixed-time tracking control problem of UWR with external disturbances, error constraints, and actuator faults is investigated. An interval type-2 fuzzy neural network approximator is designed to tackle nonlinear uncertainties, and a novel prescribed performance terminal sliding-mode

In this paper, we propose a novel Interval Type-2 (IT2) Fuzzy Cognitive Map (FCM)-based flight control system to solve the altitude, attitude and position control problems of quadcopters. The proposed IT2-FCM encompasses all concepts related to drone for a satisfactory path-tracking and stabilizing control performance. The degree of mutual influences of the concepts is designed with opinions of three

Business systems are considered as complex systems and consist of several sub-models such as procurement market, supply process, assembly, distribution and sales market. In these systems, it is important to analyze strength and weakness of each sub-model over other parts in order to obtain information for enhancing the business system performance. To fulfill this aim, in this paper we utilize differential

This article considers the cooperative path-following control problem for a cluster of networked autonomous underwater vehicles (AUVs) suffering from unknown dynamics and ocean disturbances. By virtue of light-of-sight guidance and undirected graph, a synchronized guidance approach is created for underactuated AUVs, where multiple geometry curves are taken into account and information exchanges-related

Medical images may be corrupted by noise. This noise affects the image quality and can obscure important information required for accurate diagnosis. Effectively apply filtering techniques can facilitate diagnosis or reduce radiation exposure. In this paper, we introduce a parallel method designed to reduce mixed Gaussian-impulse noise from digital images. The method uses fuzzy logic and the fuzzy

This paper addresses the leader–follower formation control strategy for unmanned surface vehicles with model uncertainties. First, to achieve the desired formation configuration, the line-of-sight (LOS) scheme is incorporated in the guidance design. The constraints of LOS range and angle are required to meet the connectivity maintenance and collision avoidance. Tan-type time-varying Barrier Lyapunov

As a useful aggregation technique, the Bonferroni mean can capture the interrelationship between input arguments and has been a hot research topic, especially, in intuitionistic fuzzy environment. In this paper, it is pointed out by an example that the existing intuitionistic fuzzy Bonferroni mean (IFBM) operators fail to satisfy the need in group decision making with intuitionistic fuzzy preference

Granular computing (GrC) is an essential tool to solve human real problem since the information granules is close to human perception schemes. In GrC, both classification accuracy and interpretability play significant roles. Fuzzy rule (FR) based classification systems are effective methods solving this problem. However, the accuracy of FR may be decreased when solving some complex application. In

Evolutionary multitasking is an emerging subject in the field of evolutionary computation. By adopting methods to effectively discover and implicitly transfer useful genetic materials from one task to another, it can process multiple optimization tasks simultaneously using one evolutionary calculation. Inspired by the idea of evolutionary multitasking, it can be also used in optimization problems of

This study provides a novel quad-function-link network to adjust the lower and upper weights of a wavelet interval type-2 fuzzy brain emotional structure to increase the response and performance for the synchronization of 3D nonlinear chaotic systems. The proposed control system is a hybrid method that comprises a new wavelet interval type-2 fuzzy quad-function-link brain emotional controller and a

This paper focuses on the new model for the classification of railhead defects, through images acquired by a rail inspection vehicle. In this regard, we discuss the use of set-membership concept, derived from the adaptive filter theory, into the training procedure of an upper and lower singleton type-2 fuzzy logic system, aiming to reduce computational complexity and to increase the convergence speed

Uncertainty appearing in datasets (stochastic, linguistic, of measurements, etc.), if not handled properly, may negatively affect information analysis or retrieval procedures. One of possible methods of dealing with uncertain (rare, strange, unexampled) data is to treat them as “outliers” or “exceptions”. Among different definitions and algorithms for detecting outliers, we are especially interested

In this paper, an observer-based adaptive fuzzy tracking control is considered for a class of strict-feedback nonlinear systems. The nonlinear functions and unmeasured states in the system are estimated by means of fuzzy logic systems and fuzzy state observers, respectively. In addition, the tan-type barrier Lyapunov specifies that the tracking error is limited to a given area. An improved event-triggered

This paper presents a path-following-based design for guaranteed cost control of a class of nonlinear systems represented by polynomial fuzzy systems. First, this paper proposes a polynomial Lyapunov function approach to guaranteed cost control for the feedback system consisting of a polynomial fuzzy system and a polynomial fuzzy controller. In particular, we introduce a new type of polynomial fuzzy

As a complex process, wireless optical communication of autonomous underwater vehicles (AUVs) is particularly challenging in the complex communication environment. Therefore, the existing control or denoise systems show some limitations for communication system of multi-AUV. It is still difficult to balance between the complexity of underwater environment and the performance of reality or estimation

In this paper, the synchronization problem of complex networks using fuzzy-based impulsive control is discussed. Synchronization problem is considered for networks with switching topologies. Also, each node of the networks has a time-varying chaotic dynamic. Based on the Takagi–Sugeno fuzzy model, a new representation of a complex network is presented. Using impulsive control theory, a new controller

Autonomous underwater vehicle (AUV) plays an important role in ocean research and exploration. The underwater environment has a great influence on AUV control and human–robot interaction, since underwater environment is highly dynamic with unpredictable fluctuation of water flow, high pressure and light attenuation. The traditional control model contains a large number of parameters, which is not effective

This paper considers the leader-following consensus problem for linear multi-agent systems (MASs) with actuator faults, matched unknown nonlinearity and non-identifiable uncertainty under switching network topology for studying. A novel distributed switching fault-tolerant controller is established by approximating the nonlinear dynamics using a fuzzy logic system and by developing adaptive update

Fuzzy addition is one of the operations widely used in the application of fuzzy systems. The analytical and closed form expressions of the fuzzy additions of the generalized fuzzy numbers and the interval type 2 fuzzy numbers (IT2FS) are developed. The generalized fuzzy numbers is a non-flat and subnormal fuzzy number with different left and right shape functions. Classical fuzzy operations based on

In view of the fact that most clustering algorithms cannot solve the clustering problem about samples with uncertain information, according to the theory of fuzzy sets and probability, we define the fuzzy-probability binary measure space and triangular fuzzy normal random variables firstly, and then combine the advantages of k-means algorithm, such as simple principle, few parameters, fast convergence