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Improving the diversity of Neural Network Ensembles (NNE) plays an important role in creating robust classification systems in many fields. Several methods have been proposed in the literature to create such diversity using different sets of classifiers or using different portions of training/feature sets. Neural networks are often used as base classifiers in multiple classifier systems as they adapt...
The paper presents an upgrading process of rubber tree seed clones identification model using image processing techniques. Sample of rubber tree seeds are captured using digital camera where the RGB color image are processed involving segmentation algorithm which includes thresholding and morphological technique. Texture patterns from seed clones images are then analysed through wavelet's Daubechies...
In traditional language identification methods, it is not so easy for search engines to find relevant language database of a given query. Therefore, there is a need to identify the relevant user’s natural language query of unknown document database in a better way by automatic language identification. This novel approach presents an automatic method for classification of English and Arabic language...
Vehicle engine faults are serious faults that occur inside the engine, the ability to successfully perform fault diagnosis is highly dependent on technician skills. Some experienced technicians have some failure rate, which can lead to serious waste in time and money. Accordingly, an improved diagnosing methods is highly needed. In this paper, we develop an algorithm for fault diagnosis in vehicle...
With the advent of the Internet, search engines were developed for English language because English language was a lingua franca. Currently, most of popular search engines such as Google and Yahoo! are available in more than 50 languages. However, these search engines have received less attention in South Asian languages especially, Urdu language. In this paper, we propose a novel approach for feature...
This work proposes a leak detection system using sonic technology, wavelet transform and neural networks to decompose and analyze pressure signals from oil pipelines in real time. The similarity between pressure and sound signals makes it possible to treat the first through digital filtering and wavelet decomposition together with a neural network to characterize and classify leak profiles. The leak...
Image classification problem is one of the most challenges of computer vision. In this paper, a robust image classification approach using multilevel neural networks is proposed. In this approach, each image is fixedly divided into five regions each equal to half of the original image. Then these regions are classified by the multilevel neural classifier into five categories, i.e., ??sky??, ??water??,...
In this paper, the artificial neural network (ANN) inputs selection for detecting and quantifying the progressive value of an incipient defect in gears is carried out by experimental design evaluation. Several parameters in time-domain (root mean squared, crest factor, energy ratio, FM0, Kurtosis, FM4, NA4, M6A, NB4) and multiscale Hilbert-wavelet transformations are evaluated as a possible inputs...
Artificial neural networks are highly parallel structures inspired by the human brain. They have been used successfully in many human-like applications, such as pattern recognition. Performance of these networks can be enhanced if used properly in conjunction with equally powerful mathematical tools. In this paper, we used the discrete wavelet transform as a pre-processing tool for two well-known...
In this paper a self tuning adaptive PID control scheme for nonlinear systems is proposed using wavelet networks. The auto tuner consists of a discrete PID controller and a proposed new wavelet network structure called dynamic wavelet network (DWN). The DWN consists of a static feedforward wavelet network in cascade with an autoregressive moving average (ARMA) model. The learning strategy for the...
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