Search Results - (( developing activation function algorithm ) OR ( classification _ problems algorithm ))
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1
Jogging activity recognition using k-NN algorithm
Published 2022“…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
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2
Particle swarm optimization for neural network learning enhancement
Published 2006“…Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). …”
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3
Enhancement of new smooth support vector machines for classification problems
Published 2011“…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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4
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…A novel feature extraction algorithm was developed to extract the feature vectors. …”
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5
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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6
Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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7
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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8
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…This research aims are to develop an open-source Arduino based sEMG data acquisition device by formulating hybrid automata algorithm to differentiate MUAP activity during wheelchair propulsion. …”
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9
Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The hierarchical fuzzy clustering algorithm developed in this work assign the overlapping structures (structures having more than one activity) to more than one clusters if their fuzzy membership values are significantly high for those clusters. …”
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10
Diagnosis of vocal fold pathology using time-domain features and systole activated neural network
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11
Tracking and recognizing the activity of multi resident in smart home environments
Published 2017“…Thus, recognizing activities and tracking which resident perform the activity at the same time in the smart home are vital for the smart home development and future applications. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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13
Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…PNN is a fast training process to do the classification activities. As compared with the backpropagation method in literature review, it gives better result when classifying large data sets. …”
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14
Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer�s Disease
Published 2022“…It outperformed the fractal and Pearson-based connectivity approaches by 16.4 and 17.2, respectively. The classification algorithm developed based on the nonfractal connectivity feature and support vector machine classifier has shown an excellent performance, with an accuracy of 90.3 and 83.3 for the XHSLF dataset and ADNI dataset, respectively. …”
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15
Using genetic algorithms to optimise land use suitability
Published 2012“…The first task was studying the dominant of crops and economic suitability evaluation of land with the land evaluation framework developed by FAO, (1976-2007) using GIS. Second task is to determine the fitness function for the genetic algorithms. …”
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16
Incisor Malocclusion Using Cut-out Method And Convolutional Neural Network
Published 2024journal::journal article -
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…Compared to state-of-the-art algorithms and other common methods, our method outperformed them in terms of sensitivity, specificity, and accuracy. …”
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18
Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin
Published 2024“…Most of those research results varies as it uses different data, different network design, different parameters and optimizing algorithm. This research aims to experiment a new DNN model that functions modularly by looking into several features that will affect the NN training dynamics. …”
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19
Extreme Learning Machine neural networks for multi-agent system in power generation
Published 2023“…Several activation functions using benchmark datasets and real-world applications, i.e., satellite image, image segmentation, fault diagnosis in power generation (including circulating water systems as well as GAST governor) were used to test the ELM-MAS developed. …”
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Detection of Epileptic EEG Signal Using Wavelet Transform and Adaptive Neuro-Fuzzy Inference System
Published 2011“…Such algorithms use brain electrical activity signals called electro encephalography (EEG) and have 2 methods of detection: visual (by specialist inspection) and automatic (by using signal processing knowledge). …”
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