Results 111 to 120 of about 59,339 (255)

Classification Improvement with Integration of Radial Basis Function and Multilayer Perceptron Network Architectures

Mathematics
The radial basis function architecture and the multilayer perceptron architecture are very different approaches to neural networks in theory and practice.
László Kovács
doaj   +1 more source

Experimental Modal Analysis‐Driven Gaussian Process Regression Modeling of Rectangular Steel Beams With Various Hole Geometries

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Understanding the dynamic behavior of structural components is crucial for optimizing performance and ensuring structural integrity. This study presents a new method that combines a systematic experimental investigation of four distinct hole geometries (circular, square, compact rectangular, and long rectangular) with varying hole counts, all ...
Amir Hossein Rabiee, Majid Rajaei, Mohammad Hossein Mahdavi Nasab, Parsa Shafiei   +3 more
wiley   +1 more source

Maximum Power Point Tracking Control of Offshore Hydraulic Wind Turbine Based on Radial Basis Function Neural Network

Energies
A maximum power point tracking control strategy for an affine nonlinear constant displacement pump-variable hydraulic motor actuation system with parameter uncertainty, used within an offshore hydraulic wind turbine, is studied in this paper.
Qinwei Wang, Zeli Du, Wenting Chen, Chao Ai, Xiangdong Kong, Jiarui Zhang, Keyi Liu, Gexin Chen   +7 more
doaj   +1 more source

Retracted: Simulation and Prediction of Fungal Community Evolution Based on RBF Neural Network. [PDF]

Comput Math Methods Med, 2023
Methods In Medicine CAM.
europepmc   +1 more source

Optimization of Flexural Strength of PLA Flexural Test Specimens Produced by FDM Using Taguchi L27 Orthogonal Array and Hybrid Regression Model

Journal of Polymer Science, EarlyView.
This study investigates the impact of FDM process parameters on the flexural strength of PLA components using a Taguchi L27 orthogonal array. Analysis reveals wall thickness and layer height as the primary determinants of mechanical performance. A highly accurate regression model is developed, providing a robust predictive framework to optimize 3D ...
Mehmet Şah Gültekin, Cüneyt Özdemir
wiley   +1 more source

Using deep learning to assess the toxicological effects of sublethal exposure of a novel green pesticide in a stored‐product beetle

Pest Management Science, EarlyView.
This study employs an AI‐driven multidisciplinary approach to increase our understanding of the toxicological effects of sublethal concentrations of carlina oxide on Prostephanus truncatus. Sublethal exposure to the carlina oxide induced changes in motor patterns and thigmotaxis, highlighting its potential role in integrated pest management strategies.
Anita Casadei, Maria C. Boukouvala, Gianluca Manduca, Nickolas G. Kavallieratos, Filippo Maggi, Marta Ferrati, Eleonora Spinozzi, Cesare Stefanini, Antonio DeSimone, Donato Romano   +9 more
wiley   +1 more source

Retracted: Signal Recognition Based on APSO-RBF Neural Network to Assist Athlete's Competitive Ability Evaluation. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

EXTRACTING RULES FROM TRAINED RBF NEURAL NETWORKS

Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference, 2005
This paper describes a method of rule extraction from trained artificial neural networks. The statement of the problem is given. The aim of rule extraction procedure and suitable neural networks for rule extraction are outlined. The RULEX rule extraction algorithm is discussed that is based on the radial basis function (RBF) neural network.
openaire   +3 more sources

Neural Network‐Based Adaptive Super‐Twisting Control for Perturbed Nonlinear Systems: Lyapunov Design

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT A newly developed robust control strategy based on an adaptive neural network (ANN) estimator performed in concert with adaptive super‐twisting (ASTW) control is presented. The proposed adaptive robust control algorithm is applied to a class of perturbed nonlinear systems and features a significantly decreased control gain with respect to the ...
Mohammad Javad Mirzaei, Mohamed Assaad Hamida, Yuri Shtessel, Franck Plestan   +3 more
wiley   +1 more source

Retracted: Optimization and Simulation of Enterprise Management Resource Scheduling Based on the Radial Basis Function (RBF) Neural Network. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source