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In this paper, comparison of seven backpropagation algorithms used in neural network is made for the three phase power quality assessment. Voltage sag and swell are the two disturbances taken into account for comparing the algorithms. These disturbances are generated with the help of programming in MATLAB. The input data, to train the network is the generated sag and swell disturbances. The backpropagation...
This paper presents the modelling of agarwood oil (AO) significant compounds by different qualities using Scaled Conjugate Gradient (SCG) algorithm. This technique involved of data collection from Gas Chromatography-Mass Spectrometry (GC-MS) for compound extraction. The development of Multilayer perceptron (MLP) is used to discriminate the qualities of AO chemical compounds to the high and low quality...
In this paper, enhanced gradient descent learning algorithms for complex-valued feed forward neural networks are proposed. The most known such enhanced algorithms for real-valued neural networks are: quick prop, resilient back propagation, delta-bar-delta, and Super SAB, and so it is natural to extend these learning methods to complex-valued neural networks, also. The complex variants of these four...
In order to remedy the weaknesses of conventional back-propagation (BP) neuronets, a novel 2-input Legendre orthogonal polynomial neuronet (2ILOPN) based on the theory of the multivariate function approximation is constructed and investigated in this paper. In addition, based on the weights-direct-determination (WDD) method, two weights-and-structure-determination (WASD) algorithms with different...
Early warning systems are critical in providing emergency response in the event of unexpected hazards. Cheap cameras and improvements in memory and computing power have enabled the design of fire detectors using video surveillance systems. This is critical in scenarios where traditional smoke detectors cannot be installed. In such scenarios, it has been observed that the smoke is visible well before...
Because of today's explosive information from Internet, people will contact much new information at any moment. So how to analyze this non-stationary information becomes more and more important. Clustering analysis is a good information analysis method, but many clustering algorithms only fit to stationary situation. Then in this paper, a novel incremental clustering algorithm based on self-organizing-mapping-IGSOM...
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