Search Results - (( developing function learning algorithm ) OR ( learning location based algorithm ))
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Finally, surface defects are segmented from an anomaly heat map which is generated based on histogram distance functions. Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review
Published 2021“…Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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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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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak
Published 2020“…Towards achieving better detection in real-time environment, colour pixel-based images were trained on five pre-trained CNNs using transfer learning algorithm. …”
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Mobile application for blood donation using geolocation and rule-based algorithm / Muhammad Firzan Azrai Nuzilan and Mohd Ali Mohd Isa
Published 2021“…Besides, the rule-based algorithm is estimated to make the blood donation process goes efficiently by filtering the characteristic so that only suitable donor can donate the blood. …”
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Application Of Neural Network In Malaria Parasites Classification
Published 2006“…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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Quasi oppositional—Manta ray foraging optimization and its application to pid control of a pendulum system
Published 2022“…Therefore, a type of OBL namely Quasi Oppositional-based Learning will be adopted into MRFO in order to increase the possibility of finding the solution by considering the opposite individual location of fitness. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid
Published 2023“…This algorithm is capable of surmounting the aforementioned drawbacks especially premature convergence, through its reward-based dynamic leader assignment and self-learning strategies. …”
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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance
Published 2019“…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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Development of damage identification scheme using de-noised modal frequency response function data with artificial neural network / Mohamad Izzudin Hussein Shah
Published 2018“…Damaged identification scheme is used to monitor and locate the damage on a structure. Vibration based damage identification scheme which utilise vibrational modal data is popular due to its non-destructive nature. …”
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Fault diagnosis in unbalanced radial distribution networks using generalised regression neural network
Published 2011“…Nowadays, about 80% of interruptions are caused by faults in distribution networks and the application of fault location algorithms developed for transmission system is not an easy task due to the topology and operating principles of the distribution networks. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…Also, a corridor extraction algorithm has been developed to extract the region of interest (ROI) around the transmission towers. …”
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Enhanced recognition methods for text and slider CAPTCHA vulnerability assessment
Published 2025“…To address the limitation of traditional color enhancement algorithms that lack adaptive learning capabilities, three types of Variation Color Shift (VCS) algorithms have also been proposed for data augmentation. …”
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab
Published 2025“…The current research presents three different AI approaches: i) Multi-Layer Perceptron Neural Network (MLP-NN), ii) Radial Basis Function Neural Network (RBF-NN), and iii) Deep Learning Neural Network (DLNN). …”
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Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…In Chapter 2, we propose a new algorithm based on incremental Radial Basis Function Network (RBFN) to accelerate the learning in stream data. …”
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Extreme learning machine for user location prediction in mobile environment
Published 2011“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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