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Intrusion Detection Based on RBF Neural Network
2009 International Symposium on Information Engineering and Electronic Commerce, 2009Radial Basis Function (RBF) has been one of the most common neural networks used in the intrusion detection system(IDS). To improve the approximation performance and calculation speed of RBF, we describe a method to deal with the benchmark datasets adopted in the research. It includes converting the string to numeric elements firstly, then omitting the
Jing Bi, Kun Zhang, Xiaojing Cheng
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Time series forecasting with RBF neural network
2005 International Conference on Machine Learning and Cybernetics, 2005Radial basis function neural network (RBF NN) has been widely used for nonlinear system identification because of its simple topological structure and its ability to reveal how learning proceeds in an explicit manner. In this paper, descriptions and original applications of RBF NN, to the time series forecasting problem is presented.
null Xiang-Bin Yan +3 more
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Adaptive RBF neural networks for pattern classifications
Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290), 2003The viewpoints are presented that the centers and widths of kernels in RBF networks should be determined by a self-learning procedure, that a new kernel naturally comes into being according to which class some labeled patterns are misclassified to, and going a step further, that a current kernel be deleted if its effect on the test set is too trivial ...
null Gao Daqi, null Yang Genxing
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Intelligent prediction for digging load of hydraulic excavators based on RBF neural network
Measurement, 2022Dongyang Huo +4 more
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RBF, SOM, Hopfield, and Deep Neural Networks
2020In this chapter, four different types of neural networks are described: Radial Basis Functions-RBF, Self-Organizing Maps-SOM, the Hopfield, and the deep neural networks. RBF uses a different approach in the design of a neural network based on the hidden layer (unique in the network) composed of neurons in which radial basis functions are defined, hence
Arcangelo Distante, Cosimo Distante
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Coking flue temperature RBF neural network model
The 27th Chinese Control and Decision Conference (2015 CCDC), 2015A modified radial basis function neural networks (RBFNN) model is proposed to solve the control problem that the flue temperature in coke oven usually has the properties of high nonlinearity, large time-delay and multiple disturbances. The proposed method adopts K-means to initialize hidden layer and center parameters of the network.
Zhang Li +3 more
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Application of RBF neural network optimal segmentation algorithm in credit rating
Neural computing & applications (Print), 2020Xuetao Li, Yi Sun
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Robust Image Watermarking Using RBF Neural Network
2006In recent years digital watermarking was developed significantly and applied broadly for copyright protection and authentication. In this paper, a digital image watermarking scheme is developed using neural network to embedded watermark into DCT domain of each subimage blocks obtained by subsampling, which achieves adaptively watermark embedding and ...
Wei Lu, Hongtao Lu, Fu-Lai Chung
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A Growing Algorithm for RBF Neural Network
2009This paper presents a growing algorithm to design the architecture of RBF neural network called growing RBF neural network algorithm (GRBF). The GRBF starts from a single prototype randomly initialized in the feature space; the whole algorithm consists of two major parts: the structure learning phase and parameter adjusting phase.
Han Honggui, Qiao Junfei
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