Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- research-articleFebruary 2024
Fuzzy RBF neural network fault diagnosis method based on knowledge and data fusion for the recoil system
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (JIFS), Volume 46, Issue 22024, pp 4981–4994https://doi.org/10.3233/JIFS-230683To improve the accuracy of fault diagnosis for recoil systems under multiple operating conditions, a fuzzy RBF neural network (Radial Basis Function, RBF) fault diagnosis method based on knowledge and data fusion is proposed. A kinetic model for the ...
- research-articleDecember 2023
Neural Network Adaptive Observer design for Nonlinear Systems with Partially and Completely Unknown Dynamics Subject to Variable Sampled and Delay Output Measurement
AbstractThis paper proposes a novel Neural Network Adaptive Observer (NNAO) for Nonlinear Systems with Partially and Completely Unknown Dynamics (NSPCUD), subject to variable sampled and delayed output. The method involves designing a neural network ...
Highlights- A neural network observer is proposed under variable sampled and delayed output.
- A new weight update law is designed to construct the neural network observer.
- The proposed observer is extended to more general nonlinear systems.
- ArticleNovember 2023
Cascaded Fuzzy PID Control for Quadrotor UAVs Based on RBF Neural Networks
AbstractSince quadrotor UAVs often need to fly in complex and changing environments, their systems suffer from slow smooth control response, weak self-turbulence capability, and poor self-adaptability. Thus, it is crucially important to carefully ...
- research-articleJuly 2023
Fractional‐order dynamics and adaptive dynamic surface control of flexible‐joint robots
Asian Journal of Control (ASJC), Volume 25, Issue 4July 2023, pp 3029–3044https://doi.org/10.1002/asjc.3002AbstractThis paper establishes a novel fractional‐order model for n‐links flexible‐joint (FJ) robots and proposes an adaptive dynamic surface control (DSC) scheme to address the tracking control problem. The fractional‐order FJ model is built by ...
- research-articleMay 2023
MEMS Gyroscope Temperature Compensation Based on SSA-RBF Neural Network
AIPR '22: Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern RecognitionSeptember 2022, pp 109–114https://doi.org/10.1145/3573942.3573959The output of the Micro Electro-mechanical System (MEMS) gyroscope is susceptible affected by temperature drift, which reduces the measurement accuracy of the gyroscope. In this paper, a gyroscope temperature compensation method based on sparrow search ...
-
- research-articleApril 2023
Fault Diagnosis of Motor Bearing Equipment Based on Sound Signal
ICITEE '22: Proceedings of the 5th International Conference on Information Technologies and Electrical EngineeringNovember 2022, pp 337–342https://doi.org/10.1145/3582935.3582990In the diagnostic technology of the motor, the sound of the motor at work contains a lot of useful information. The identification of the sound signal can reflect the running status of the motor, so that the parts with problems can be repaired. In this ...
- research-articleApril 2023
Cognitive spectrum sensing algorithm based on an RBF neural network and machine learning
Neural Computing and Applications (NCAA), Volume 35, Issue 36Dec 2023, pp 25045–25055https://doi.org/10.1007/s00521-023-08488-yAbstractAfter 70 years of intricate development, machine learning, represented by deep learning, is based on the multilevel structure of the human brain and the layer-by-layer analysis and processing mechanism of neuron connection and interaction ...
- research-articleApril 2023
Fuzzy Sliding Mode Control of Manipulator Based on Disturbance Observer and RBF Neural Network
Automatic Control and Computer Sciences (ACCS), Volume 57, Issue 2Apr 2023, pp 123–134https://doi.org/10.3103/S0146411623020098AbstractAiming at the nonlinear and uncertain manipulator system, this paper proposes a fuzzy sliding mode control method based on disturbance observer and radial basis function (RBF) neural network, so that the manipulator can track a given trajectory ...
- research-articleMarch 2023
A Novel Adaptive Sliding Mode Control of Robot Manipulator Based on RBF Neural Network and Exponential Convergence Observer
Neural Processing Letters (NPLE), Volume 55, Issue 7Dec 2023, pp 10037–10052https://doi.org/10.1007/s11063-023-11237-wAbstractThis paper focuses on a novel adaptive sliding mode control (NASMC) of robot manipulator based on RBF (radial basis function) neural network and observer. A novel adaptive sliding mode control can achieve high performance tracking control by ...
- research-articleJanuary 2023
Research on the application of RBF neural network in the evaluation of college English teaching quality
ICDTE '22: Proceedings of the 6th International Conference on Digital Technology in EducationSeptember 2022, pp 118–123https://doi.org/10.1145/3568739.3568761Because of the diversity of teaching and students and the supervisory factors of the educational affairs department, it is difficult to be objective and fair in teaching quality evaluation. In order to solve the problems existing in the traditional ...
- research-articleJanuary 2023
A hybrid estimation procedure for modeling shallow foundation’s settlement: RBF-optimized neural network
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (JIFS), Volume 45, Issue 12023, pp 1387–1396https://doi.org/10.3233/JIFS-223907The complexity of the cohesive soil structure necessitates settlement modeling beneath shallow foundations. The goal of this research is to use recently discovered machine learning techniques called the hybridized radial basis function neural network (...
- research-articleJanuary 2023
Multiview collaboration learning classification model of stock data based on view weighting mechanism
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (JIFS), Volume 45, Issue 42023, pp 5251–5264https://doi.org/10.3233/JIFS-223202Machine learning methods have become an effective strategy commonly used in quantitative hedge funds, which can maximize profits and reduce investment risks to a certain extent. Traditional stock forecasting systems are usually based on a single attribute ...
- research-articleJanuary 2023
A novel prediction and control method for solar energy dispatch based on the battery energy storage system using an experimental dataset
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology (JIFS), Volume 44, Issue 32023, pp 3667–3680https://doi.org/10.3233/JIFS-221123The high power generation growth by photovoltaic systems needs to forecast the power generation profile during a day. It is also required to evolve the high-efficient and optimal on-grid/off-grid photovoltaic power generation units. Furthermore, some ...
- research-articleJanuary 2023
Atrial fibrillation medical image encryption algorithm based on deep learning and adaptive block
International Journal of Communication Networks and Distributed Systems (IJCNDS), Volume 29, Issue 62023, pp 679–693https://doi.org/10.1504/ijcnds.2023.133905In this paper, a deep learning and adaptive block-based chaotic encryption algorithm for atrial fibrillation medical image is proposed. Firstly, we use 2D Sine Logistic chaos system to generate two security sequences with good chaotic characteristics. ...
- research-articleJanuary 2023
Frequency matching optimization model of ultrasonic scalpel transducer based on neural network and reinforcement learning
Engineering Applications of Artificial Intelligence (EAAI), Volume 117, Issue PAJan 2023https://doi.org/10.1016/j.engappai.2022.105572AbstractAiming at the problem that the excitation frequency and resonant frequency of the transducer cannot keep synchronous, the output amplitude decreases and the vibration is unstable. In this study, the working principle of piezoelectric ...
Graphical abstractDisplay Omitted
Highlights- The relationship between resonant frequency and its variables is established.
- ...
- research-articleDecember 2022
Design of a modular neural network based on an improved soft subspace clustering algorithm
Expert Systems with Applications: An International Journal (EXWA), Volume 209, Issue CDec 2022https://doi.org/10.1016/j.eswa.2022.118219AbstractBeing a commonly used way for task decomposition in modular neural network (MNN), clustering analysis is employed to decompose the complex task into several simple subtasks for learning. Recent studies mainly focus on hard clustering, ...
- research-articleDecember 2022
Research on target location prediction based on improved PSO-RBF Neural Network
IMMS '22: Proceedings of the 5th International Conference on Information Management and Management ScienceAugust 2022, pp 63–68https://doi.org/10.1145/3564858.3564869In order to make the antenna point to the target position in real time and obtain the current target parameters, an improved PSO-RBF neural network for antenna target position prediction was proposed. Based on the RBF neural network model, the improved ...
- research-articleNovember 2022
Research on strip crown by uncertain sampling strategy modified particle swarm optimization with RBF neural network
Applied Soft Computing (APSC), Volume 130, Issue CNov 2022https://doi.org/10.1016/j.asoc.2022.109661AbstractThe strip crown directly affects the quality of strip. The prediction of strip crown by general machine learning models usually focuses on the production of a single category of strip steel, and the models lack good prediction ability ...
Highlights- A new PSO algorithm (US-MPSO) is developed.
- A combination of US-MPSO and RBF ...
- research-articleOctober 2022
Denoising method for terahertz signal using RBF neural network with adaptive projection learning algorithm
Wireless Networks (WIRE), Volume 29, Issue 2Feb 2023, pp 749–759https://doi.org/10.1007/s11276-022-03128-0AbstractRadial basis function (RBF) neural network has the ability to eliminate the terahertz (THz) spectrum’s noise via its robust feature removal ability. Unfortunately, this method has some disadvantages, such as difficulty in obtaining clean training ...
- ArticleOctober 2022
RBF Neural Network Based on FT-Windows for Auto-Tunning PID Controller
- O. F. Garcia Castro,
- L. E. Ramos Velasco,
- M. A. Vega Navarrete,
- R. Garcia Rodriguez,
- C. R. Domínguez Mayorga,
- E. Escamilla Hernández,
- L. N. Oliva Moreno
Advances in Computational IntelligenceOct 2022, pp 138–149https://doi.org/10.1007/978-3-031-19493-1_11AbstractThe weighted function windows are used in many areas as signal analysis and application systems. In addition, the weighted functions are broad uses in filter design where different windows allow to choose different filter characteristics. The most ...