Search Results - (( pattern classification learning algorithm ) OR ( parameter classification learning algorithm ))
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The proposed system utilizes Biased ARTMAP for pattern learning and classification. The ARTMAP system is dependent on training sequence presentation to determine the effectiveness of the learning processes, as well as the strength of the biasing parameter, lambda λ. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Subjects:Conference Paper -
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…It is capable of envisaging results and mostly effective than other classification methods. The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation
Published 2023“…Classification (of information); Computer aided diagnosis; Fault detection; Fuzzy systems; Knowledge acquisition; Knowledge representation; Learning systems; Matrix algebra; Membership functions; Pattern recognition; Extreme learning machine; Fault detection and diagnosis; Fuzzy if-then rules; Fuzzy inference systems; Fuzzy membership function; Initialization technique; Interpretable rules; Rule based; Fuzzy inference; algorithm; artificial intelligence; artificial neural network; benchmarking; classification; electric power plant; factual database; feedback system; fuzzy logic; machine learning; nerve cell; reproducibility; statistical model; Algorithms; Artificial Intelligence; Benchmarking; Classification; Databases, Factual; Feedback; Fuzzy Logic; Machine Learning; Models, Statistical; Neural Networks (Computer); Neurons; Power Plants; Reproducibility of Results…”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani
Published 2005“…However, the performances of neural network in learning and classification task should be enhanced by redesigning and conducting experiment on other learning algorithm than back-propagation.…”
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Classification of heart sound signals for the detection of heart diseases / N. Shamsuddin and M. N. Taib
Published 2012“…With optimized learning parameter of 0.07, the network gave its best performance at 32-220-6. …”
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Neurons to heartbeats: spiking neural networks for electrocardiogram pattern recognition
Published 2024“…Establishing functioning spiking neural networks (SNN) involves figuring out the neuron’s state through its activity level, challenging due to its resemblance to the human brain’s data processing, yet appealing due to factors like improved unsupervised learning methods, with ten parameters chosen for the learning algorithm of SNN. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur...
Published 2012“…Artificial neural networks (ANN) has become one of the artificial intelligent techniques that has many successful examples when applied to classification problem such as doing pattern recognition and prediction. …”
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Research Reports -
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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Personalized Recommendation Classification Model of Students’ Social Well-being Based on Personality Trait Determinants Using Machine Learning Algorithms
Published 2023“…In this study, how different personality trait models compare in terms of accuracy and reliability is explored using different machine learning algorithms using the WEKA tool. Personality trait models are increasingly being used to measure social well-being. …”
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A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The performance of MANFIE was compared with existing methods in a diversity of practical benchmark applications such as pattern classifications, time series predictions, modeling with inverse learning control and mobile robot navigation. …”
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Spiking Neural Network For Energy Efficient Learning And Recognition
Published 2020“…The use of applications consumes energy and hard to perform through standard programmed algorithms. Spiking neural networks have emerged that achieve favourable advantages in terms of energy and time efficiency by using spikes for computation and communication as well as solving different problems such as pattern classification and image processing. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Complementing this, the Harmony Search Algorithm (HSA) is incorporated to augment data features, facilitating better pattern recognition and enhancing overall classification accuracy through optimized feature engineering. …”
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