In this paper, we propose an enhanced swarm intelligence clustering (ESIC) method to select hidden layer neurons, and then, training a cosine RBFNN base on ...

The central problem in training a radial basis function neural network (RBFNN) is the selection of hidden layer neurons, which includes the selection of the ...

In this paper, we propose an enhanced swarm intelligence clustering (ESIC) method to select hidden layer neurons, and then, training a cosine RBFNN base on ...

The approach includes four DR techniques: the Bessel function (BF), Discrete Cosine Transform (DCT), Least Squares Linear Regression (LSLR), and Artificial ...

Jul 27, 2023 · This study addressed problems with wireless sensor networks and devised an efficient clustering and routing algorithm based on machine learning.

The proposed PLDC-RBFNN-SSA method is more efficient and accurate to obtain the optimal global solution for detecting and classifying leaf diseases in rice ...

This paper proposes to select hidden layer neurons based on data structure preserving criterion by preserving the data structure of samples including those ...

Dec 21, 2022 · The classification method adopted in this paper is a hybrid method of black widow optimization (BWO) algorithm and radial basis function neural ...

The following publications are possibly variants of this publication: An Enhanced Swarm Intelligence Clustering-Based RBF Neural Network Detection Classifier ...

This work introduces a novel data-driven approach for predicting PT-ETA based on RBF neural networks, using a modified version of the successful PSO-NSFM ...