Fuzzy Dynamic Model Research Articles

Selection and Promotion of Rural Revitalization Path Mode Incorporating Fuzzy Dynamic Planning

Rural revitalization refers to efforts aimed at renewing and invigorating rural communities to enhance their economic, social, and environmental well-being. To promote the appropriate development in rural revitalization it is necessary to select and promote the appropriate scheme with effective planning, this paper presented effective rural revitalization strategies with the advanced methodology of Genetic Ant Swarm Fuzzy (GAsF), to assess and optimize interventions across various dimensions. The constructed GAsF model implementation of the genetic algorithm-based ant swarm optimization the key features related to the revitalization are estimated. The estimated features are categorized with the fuzzy dynamic planning model for the classification of the program in rural revitalization with the path model implementation in the fuzzy dynamic planning system. Through the computed features classification is performed for the estimation of the features in the programs. Results stated that strategies such as the "Ecotourism Development Strategy" and the "Community Empowerment Program" as particularly promising, demonstrating strong performance in economic, social, and environmental dimensions. Simulation analysis demonstrated that the propose GAsF model achieved the classification accuracy of 0.98 with significant green development values. Through the fuzzy dynamic modelling the GAsF optimize the best fitness value for the ecotourism development value of 0.93.

High‐order robust control design with optimized parameters based on confidence index

AbstractUnder the theoretical support of fuzzy sets theory and confidence index, the proposed approach involves the development of a high‐order robust control method that incorporates optimization techniques to address uncertain systems. First, the utilization of fuzzy sets theory is employed to establish a fuzzy dynamical model. Second, the design of a high‐order robust controller is performed. Third, the design parameters are optimized based on confidence index, and the values are found that minimize the control cost. The simulation results show that this high‐order robust control has significant advantages in dealing with uncertainty, as well as minimizing the control cost. It can be ensured the uniform boundedness and uniform ultimate boundedness. Thus, this proposed method offers the advantage of achieving both robustness and optimality simultaneously.

Optimal design of robust control for belt conveyor systems based on fuzzy dynamic model and Nash game

An optimized robust control method is proposed in this paper to deal with the disturbances of nonlinear factors such as uncertainty in belt conveyor and to realize the speed control of belt conveyor. By controlling the subsystems to track the same desired speed, belt breaks and overlaps caused by varying belt speeds from one section to another are limited. First, a fuzzy model is developed by applying fuzzy set theory to describe uncertainties of belt conveyor such as masses, stiffness, damping and frictions. Second, a robust control is designed for the nominal system and compensating for the uncertainty. With the robust control, the belt conveyor system is proved to be uniformly bounded and uniformly ultimately bounded by the Lyapunov approach. Third, the parameters of controller are optimized based on a non-cooperative game approach. The optimal solution is the Nash equilibrium. Optimal solution allows the controller system to perform better and decrease the cost of control. Finally, by comparing with LQR control and different parameters, the feasibility of robust control and the rationality of the optimal parameters are proven.

Extended state-based finite-time fuzzy optimal recoil control for nonlinear drilling riser systems after emergency disconnection

To guarantee the safety and reliability of drilling riser after emergency disconnection, it is significant to investigate and refrain recoil response of the riser. This paper deals with the problem of Takagi–Sugeno (T-S) fuzzy recoil dynamic modeling and optimal recoil control of nonlinear deepwater drilling riser systems subject to friction resistance of fluid discharge and platform heave motion. First, a nonlinear recoil control model of coupled riser-tensioner is proposed by taking the nonlinear top tension of tensioner into account. Then, a T-S fuzzy dynamic model of the riser-tensioner system is established to approximate the original nonlinear one by using fuzzy modeling scheme. Third, an augmented T-S fuzzy model of riser system is proposed, where the linear exosystem model of friction resistance and platform heave motion is utilized. Fourth, a finite-time fuzzy optimal recoil controller is designed to suppress the recoil response of the riser, the existence and design algorithm of the fuzzy optimal recoil controller are derived. Simulation results demonstrate that the nonlinear recoil model is more accurate than the existing linear one to describe the recoil characteristics of the riser, and the fuzzy optimal recoil controllers are effective to reduce recoil responses and guarantee the safety of the riser significantly.

Research on fuzzy dynamic route choice model and algorithm of wargame

Research on fuzzy dynamic route choice model and algorithm of wargame

Exponential robust control for fuzzy belt conveyors model with adaptive tension force

AbstractThere exist multiple uncertainties in the belt conveyor system. To reduce the system errors and save the control energy, the uncertainties need to be described and compensated accurately. In this paper, the fuzzy set theory is applied to establish the fuzzy dynamical model. Then, an exponential control is designed and a noncooperative‐game based optimization approach is proposed to solve out the Nash equilibrium. The novel control with optimal parameters including the adaptive tension force are applied to render the system uniform boundedness and uniform ultimate boundedness. Finally, the simulations are performed for verification.

Fuzzy Dynamic Modeling for Export Consortia in Small and Medium-Sized Enterprises

Fuzzy Dynamic Modeling for Export Consortia in Small and Medium-Sized Enterprises

Economic value of virtual water with the approach of maximizing the productivity of irrigation water

Abstract The increasing use of water and the decrease in average rainfall along with climate change have caused the reduction of water resources in arid and semi-arid regions. In addition, despite the consumption of more than half of these resources in the agricultural sector, a rate between 0 and 15% of the price of the products has always been received from the farmers. Considering the concept of virtual water and the water content of products in the form of green water, blue water and gray water, the present research has calculated the economic value of virtual water of agricultural products with the approach of maximizing water use efficiency. The investigated sample includes eight cities (counties) of Sanmenxia, Jiaozuo, Nanyang, Shangqiu, Puyang, Luohe, Luoyang and Kaifeng and six agricultural products (wheat, barley, potato, rapeseed, tomato and corn). A fuzzy dynamic programming model has been used to evaluate the objective function. The results showed that the maximum and minimum economic value of water content (sum of surface and groundwater) of the products were estimated for Kaifeng and Shangqiu regions equal to 1.16 and 0.86 Yuan/m3, respectively.

Renewable energy performance analysis using fuzzy dynamic directional distance function model under natural and managerial disposability

Addressing the dynamic performance aspects of processes and identifying the sources of inefficiency are key considerations for making informed decisions, especially in situations where imprecise data are available. This study aims to evaluate the performance of renewable energy using the Fuzzy Dynamic Directional Distance Function (FDDDF) model considering natural and managerial disposability for 34 OECD member countries. As a non-parametric methodology, Data Envelopment Analysis (DEA) is used to measure dynamic fuzzy environmental efficiencies of renewable energy through multiple fuzzy inputs and outputs. Using the proposed approach, optimistic, pessimistic and integrated renewable energy performances of entities with carry-overs are assessed for each period and generally. The empirical findings reveal that the proposed FDDDF approach has strong capability to discriminate the performance of renewable energy.

Fuzzy Dynamic Optimal Model for COVID-19 Epidemic in India Based on Granular Differentiability

Fuzzy Dynamic Optimal Model for COVID-19 Epidemic in India Based on Granular Differentiability

Risk assessment of disconnect operations of MNPP using similarity aggregation method based fuzzy dynamic Bayesian networks model

Marine Nuclear Power Platforms (MNPP) have the potential to provide a safe and efficient energy supply for offshore oil extraction and remote islands. During the service, MNPP is subject to disconnect operations and return to the dock for repair and maintenance. However, the failure of disconnect operations of MNPP can have catastrophic consequences. It is essential to carry out an accurate risk assessment of the disconnect operation process. In this study, a comprehensive dynamic quantitative dynamic risk assessment method is proposed to study the whole process of MNPP disconnect operations from preparation to towing. Firstly, a similarity aggregation method (SAM) is used to solve the expert fuzzy opinion aggregation problem, and then the probability of failure of the event consistent with the group consensus opinion is obtained. Secondly, a dynamic Bayesian networks (DBNs) model is developed for three stages, including YOKE offloading operation, YOKE dropping operation, and equipment recovery operation, and then predicts the dynamic probability of failure during the disconnect operations. Finally, the prediction, sensitivity, and diagnostic analysis techniques in DBNs are used to simulate the evolution of the whole risk system. Meanwhile, the basic events probabilities were updated based on new evidence, and the most likely causes of accidents were found. Safety control measures are developed to effectively reduce the risks faced by the MNPP in the disconnect operations.

A Fuzzy Dynamic Model for Total Quality Cost

A Fuzzy Dynamic Model for Total Quality Cost

Novel intelligent computing knacks for fuzzy dynamical model of vibrating mass system

This study is designed to analyze the fuzzy dynamical model of vibrating mass system by using neural networks (NNs). Stochastic numerical solvers are implemented with Levenberg–Marquardt backpropagation (LMB) algorithm. The proposed solvers handle the uncertainties of fuzzy differential system and minimize the error consistently. Validation, constancy and verification of NNs with LMB algorithm are endorsed by attaining reasonable accuracy through statistical measures in terms of error histograms, regression and mean squared errors for different values of fuzzy parameters.

A neutrosophic approach in the optimal solution of a neutrosophic fuzzy capital budgeting problem

This paper is proposed to apply neutrosophic fuzzy dynamic programming to solve neutrosophic fuzzy capital budgeting problems (NFCBPs). This paper proposes an optimal solution to a NFCBP with indefinite parameters. In this proposed approach, the revenues are taken as neutrosophic triangular fuzzy numbers (NTFNs). Neutrosophic numbers are used to state indeterminate and inconsistent information. In this paper, ÃN = (a1, a2, a3; b1, b2, b3; c1, c2, c3) is taken as a NTFN whose truth membership TÃN, indeterminacy membership IÃN and falsity membership FÃN are defined in such a way that 0 ≤ TÃN(x) + IÃN(x) + FÃN(x) ≤ 3, x ∈ ÃN. Both forward and backward recursive equations are formulated with neutrosophic fuzzy approach to find the fuzzy optimal solution. The approach is illustrated by a numerical example. This proposed approach will pave the way for further researches in fuzzy dynamic programming models with neutrosophic approach.

Fuzzy Dynamic Modeling for Accurate Control of Uncertain Mechanical Systems

Fuzzy Dynamic Modeling for Accurate Control of Uncertain Mechanical Systems

BV quantization of dynamical fuzzy spectral triples

This paper provides a systematic study of gauge symmetries in the dynamical fuzzy spectral triple models for quantum gravity that have been proposed by Barrett and collaborators. We develop both the classical and the perturbative quantum BV formalism for these models, which in particular leads to an explicit homological construction of the perturbative quantum correlation functions. We show that the relevance of ghost and antifield contributions to such correlation functions depends strongly on the background Dirac operator around which one perturbs, and in particular on the amount of gauge symmetry that it breaks. This will be illustrated by studying quantum perturbations around (a) the gauge-invariant zero Dirac operator in a general -model, and (b) a simple example of a non-trivial in the quartic -model.

Dynamic Fuzzy Model to Detect Verbal Violence in Real Time

The crime rates in Mexico have been increasing in recent years, every day there are news on social media and in the news where assaults and verbal aggressions by criminals can be seen. Public transportation units suffer from violence that authorities have not been able to reduce, despite their efforts. That is why we have developed a fuzzy logic model that can adapt to almost any scenario thanks to the dynamism that we have implemented in each one of its stages. We have obtained promising results that we believe will be of great help to the authorities in the police headquarters to detect in real time the exact moment in which a verbal aggression typical of a violent assault is happening. This is a tool to help the authorities, not a substitution; making use of the latest technologies available to us.

Optimal design of robust control based on compound form: steady-state performance and control cost

In this paper, we propose an optimal robust control for dealing with the uncertain fuzzy dynamical systems. First, a dynamical system is established with uncertainty. The uncertainty is nonlinear, time varying, and is regarded as bounded. The bound exists within a specified fuzzy set. Then, a robust control is proposed to ensure the system performance. The proposed control is deterministic, which is not on the basis of the IF-THEN rule. Besides, to achieve better performance, a performance index, including both the steady-state performance measurement and the control cost measurement of the system, is proposed. Furthermore, a fuzzy dynamical model of the robot joint module system is established with parameters uncertainty and external disturbance. By using the proposed optimal robust control, the performance of the dynamical system is not only definitely ensured but also optimized.

Novel adaptive strategies for synchronization control mechanism in nonlinear dynamic fuzzy modeling of fractional-order genetic regulatory networks

The synchronization problem for a nonlinear dynamic fuzzy modeling of fractional-order genetic regulatory networks with adaptive feedback controllers is addressed in this article. To address such a problem, a fuzzy feedback MAX template and a fuzzy feedback MIN template of fuzzy modeling are introduced. We developed adaptive based criteria to ensure the asymptotic and finite-time stability of the error system by constructing a suitable Lyapunov functional with linear matrix inequality (LMI) approach, which ensures the drive system synchronizes with the response system. Meanwhile, two distinct controllers, linear feedback and adaptive feedback control are being developed. It should be noted that the presented results are expressed in terms of LMI, which can be efficiently solved using Matlab LMI toolbox. Numerical simulations are carried out to illustrate the theoretical results.

Nonlinear Time Series Fuzzy Regression for Developing Explainable Consumer Preferences’ Models Based on Online Comments

In modeling of consumer preferences based on online comments, nonlinearity and fuzziness exist in the relationship between the product design attribute and the consumer preference. On the other hand, consumer preferences are not static and changing over the time. Previous studies have proposed few approaches to model the variational consumer preferences based on online comments. However, the obtained models have black box problems and are not easy to be understood by humans as explicit models cannot be shown, which give rise to the research area of explainable artificial intelligence. Therefore, it is necessary to develop understandable and accurate consumer preferences’ models. In this article, a nonlinear time series fuzzy regression method is proposed to model the variational consumer preference based on online comments, which can generate a fuzzy dynamic consumer preference model with interactive terms, second-order and/or higher order terms. The datasets are first extracted from online comments using the sentiment analysis. Then, the polynomial structure of the fuzzy dynamic consumer preference model is established by using multiobjective chaos optimization algorithm. Then, the fuzzy regression method is used to allocate the fuzzy coefficients of each item of the model. Using sweeping robot as a case study, the validation results from the proposed approach are compared with those from fuzzy least squares regression, time series fuzzy least squares regression, fuzzy regression, and time series fuzzy regression, and it is found that the proposed approach performs better than the other four approaches in terms of mean relative errors and mean system credibility.