A neural network model based on a chaotic particle swarm optimization (CPSO) radial basis function-back propagation (RBF-BP) neural network was suggested to improve the accuracy of reactor temperature prediction. The training efficiency of the RBF-BP...
This article proposes a two-phase hybrid method to train RBF neural networks for classification and regression problems. During the first phase, a range for the critical parameters of the RBF network is estimated and in the second phase a genetic alg...
In this paper, a new hybrid radial basis function collocation method (HRBF-CM) is proposed to help resolve two-dimensional elastostatic symmetric problems. In the new approach, the hybrid radial basis function (HRBF) combines the infinitely smooth RB...
Control of the maglev system is one of the most significant technologies of the maglev train. The common proportion integration differentiation (PID) method, which has fixed control parameters, ignores the non-linearity and uncertainty of the model i...
Polyharmonic spline (PHS) radial basis functions (RBFs) have been used in conjunction with polynomials to create RBF finite-difference (RBF-FD) methods. In 2D, these methods are usually implemented with Cartesian nodes, hexagonal nodes, or most commo...
In this contribution, a scattered data approximation problem, chosen from the literature and using the Radial Basis Function (RBF) approach, is considered for the application of point cloud modelling. Three solutions are investigated for the approxim...
This paper develops a compact analytical framework for multiquadric radial basis function–Hermite finite difference (MQ RBF–HFD) approximations on nonuniform meshes. The main contributions are a unified local operator formulation, uniform...
This paper proposes a control strategy that combines an improved flux-based sliding mode observer with a Radial Basis Function Proportional-Integral-Derivative (RBF-PID) controller for the control of Permanent Magnet Synchronous Motors (PMSM). The st...
Ionospheric delay errors significantly reduce the positioning accuracy of global navigation satellite systems (GNSSs), whereas precise ionospheric modeling can effectively mitigate this issue. The ionosphere exhibits large-scale symmetry, and spheric...
With the increase in the elderly population in China and the growing number of individuals who are unable to walk normally, research on lower limb exoskeletons is becoming increasingly important. This study proposes a complete dynamic model parameter...
Profiting from the great progress of information technology, a huge number of multi-label samples are available in our daily life. As a result, multi-label classification has aroused widespread concern. Different from traditional machine learning met...
This paper presents modification of Radial Basis Function Artificial Neural Network (RBF ANN)-based temperature compensation models for Interferometric Fiber Optical Gyroscopes (IFOGs). Based on the mathematical expression of IFOG output, three tempe...
Radial basis function (RBF) networks are widely adopted to solve problems in the field of pattern classification. However, in the construction phase of such networks, there are several issues encountered, such as the determination of the number of no...
In this study, a radial basis function (RBF) neural network with three-layer feed forward architecture was developed to effectively predict the viscosity ratio of different ethylene glycol/water based nanofluids. A total of 216 experimental data invo...
The fractional diffusion equation is one of the important recent models that can efficiently characterize various complex diffusion processes, such as in inhomogeneous or heterogeneous media or in porous media. This article provides a method for the...
Active suspension control technologies have become increasingly significant in improving suspension performance for driving stability and comfort. An RBF-based fractional-order SMC fault-tolerant controller is developed in this research to guarantee...
Biogas production plays a key role in the development of renewable energy systems; however, forecasting biomethane yield remains challenging due to the nonlinear nature of anaerobic digestion. The objective of this study was to develop a predictive m...
This paper addresses the problem of complete synchronization of chaotic systems subject to external disturbances and parameter uncertainties, proposing a robust control strategy based on radial basis function (RBF) neural network fusion with a distur...
The live weight of pigs has always been an important reference index for growth monitoring and the health status of breeding pigs. An accurate weight acquisition of breeding pigs is the key to guide the scientific feeding of breeding pigs and improve...
This work investigates the influence of center positioning in Radial Basis Function (RBF) collocation methods for solving two-dimensional structural problems. The study enforces equilibrium using the indefinite equations approach and evaluates differ...
Lightning-induced voltages on overhead distribution lines present a formidable obstacle to ensuring the reliability of power systems, evaluated through conventional numerical techniques, such as the Finite Difference Time Domain (FDTD) method and the...
Riverbank filtration (RBF) is an important part of the surface water–groundwater cycle, and it intercepts and retains many pollutants in rivers. However, RBF affects the biogeochemical process which enables aquifer sediments to release iron (Fe...
Robot manipulator trajectory planning is one of the core robot technologies, and the design of controllers can improve the trajectory accuracy of manipulators. However, most of the controllers designed at this stage have not been able to effectively...
To satisfy the requirement of real-time and accurate control of the system, a time-delay prediction control system based on the PSO-RBF neural network model is established to solve the effect of time delay on the control system’s performance. F...
This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of ent...
In this paper, a radial basis function (RBF) neural network based trajectory generation strategy is proposed to solve the online rapid generation of initial reference trajectory for low-cost hypersonic glide vehicles (HGV) under initial state perturb...
Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated navigation is one of the key methods for achieving precise positioning in complex urban environments. However, in some scenarios such as urban canyons, overpasses,...
In this study, an annular jet pump optimization method is proposed based on an RBF (Radial Basis Function) neural network model and NSGA-II (Non-Dominated Sorting Genetic Algorithm) optimization algorithm to improve the hydraulic performance of the a...
Flexible manipulators have been widely used in industrial production. However, due to the poor rigidity of the flexible manipulator, it is easy to generate vibration. This will reduce the working accuracy and service life of the flexible manipulator....
In order to solve the problem that the control system of permanent magnet synchronous motor (PMSM) is difficult to meet the high control accuracy due to the influence of non-repeated disturbances such as external disturbance, system parameter variati...
The investigation of the reliability of long-life equipment is typically hindered by the lack of experimental data, which makes accurate assessments challenging. To address this problem, a bootstrap method based on the improved RBF (radial basis func...
To establish the complex functional relationship between the stator bar end structure and the maximum electric field strength, and to optimize the anti-corona structure, an optimization model for the stator bar end based on the Seahorse Optimization...
Soil fertility is a critical factor in agricultural production, directly impacting crop growth, yield, and quality. To achieve precise agricultural management, accurate spatial interpolation of soil parameters is essential. This study developed a new...
Thin plates are very often employed in a context of large displacements and rotations, for example, whenever the extreme flexibility of a body can replace the use of complicated kinematic pairs. This is the case of the flexible Printed Circuit Boards...
The Radial Basis Function (RBF) method has been considered an important meshfree tool for numerical solutions of Partial Differential Equations (PDEs). For various situations, RBF with infinitely differentiable functions can provide accurate results...
Coal mine safety is vital not only for maintaining production operations but also for ensuring the industry’s sustainable development. The threat posed by mine water hazards is especially severe, growing more critical as mining activities becom...
To enhance the tracking accuracy and compliance of unmanned excavators, a force–position heterogeneous dual-loop nested cooperative control strategy is proposed. The outer loop employs admittance control to establish a dynamic mapping between c...
Omnidirectional mobile robots have gained extensive application across diverse fields due to their exceptional maneuverability and adaptability in confined spaces. However, structural and systemic uncertainties significantly compromise motion accurac...
This paper focuses on the issue of unmodeled dynamics and large-range parametric uncertainties in air-breathing hypersonic vehicles (AHV), proposing an adaptive dynamic surface control method based on radial basis function (RBF) neural networks. Firs...
The large random errors in Micro-Electro-Mechanical System (MEMS) gyros are one of the major factors that affect the precision of inertial navigation systems. Based on the indoor inertial navigation system, an improved wavelet threshold de-noising me...
A camera equipped with a transparent shield can be modeled using the pinhole camera model and residual error vectors defined by the difference between the estimated ray from the pinhole camera model and the actual three-dimensional (3D) point. To cal...
The Kalman filter variants extended Kalman filter (EKF) and error-state Kalman filter (ESKF) are widely used in underwater multi-sensor fusion applications for localization and navigation. Since these filters are designed by employing first-order Tay...
A new proportional integral derivative (PID) control method is proposed for the 3D laser scanning system converted from 2D Lidar with a pitching motion device. It combines the advantages of a fuzzy algorithm, a radial basis function (RBF) neural netw...
To improve the control precision of the nonlinear register system for flexographic printing, a feedforward active disturbance rejection control (ADRC) parameter self-tuning decoupling control strategy based on radial basis function (RBF) is proposed...
In this paper, a global fast terminal fuzzy sliding mode control scheme based on the radial basis function (RBF) neural network is proposed for quadrotor unmanned aerial vehicle systems in the presence of external disturbances, system model uncertain...
Valve-controlled asymmetric hydraulic cylinders inherently exhibit bidirectional dynamic asymmetry attributable to differential chamber areas and heterogeneous gravitational coupling. This study proposes an event-triggered asymmetric gain RBF-PID str...
Complex single/multi-body structures are generally found in ship and ocean engineering. They have the smooth, sharp, concave, and convex surface features in common. Precise modeling of the structures is the basis of numerical simulation. However, the...
The torque is a significant indicator reflecting the comprehensive operational characteristics of a power system. Thus, accurate torque measurement plays a pivotal role in ensuring the safety and stability of the system. However, conventional torque...
To address high-precision trajectory tracking challenges in multi-joint robots facing model uncertainties, complex friction, and abrupt disturbances, this paper proposes a radial basis function (RBF) neural network-improved integral terminal sliding...
With the fast expansion of renewable energy systems during recent years, the stability and quality of smart grids using solar energy have been challenged because of the intermittency and fluctuations. Hence, forecasting photo-voltaic (PV) power gener...
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