Search Results - (( developing function learning algorithm ) OR ( learning application matching algorithm ))
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A new text-based w-distance metric to find the perfect match between words
Published 2020“…The k-NN algorithm is an instance-based learning algorithm which is widely used in the data mining applications. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Development and application of an enhanced ART-Based neural network
Published 2009Get full text
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi
Published 2025“…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…The ANN programming algorithm was developed and computed automatically via Matlab software version R2010a. …”
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Book Section -
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Subjects:Conference paper -
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Prediction of shear strength of concrete using the artificial neural network / R. Rohim, S.F. Senin and N.F. Azman
Published 2022“…Feed-forward backpropagation was chosen for the neural network design and LevenbergMarquardt was used as the learning algorithm. An S-shaped sigmoid function was used to predict the probability as output between the range 0 to 1. …”
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Development of job matching algorithm with collective learning
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Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference
Published 2021“…Fundamentally, a stereo matching algorithm produces a disparity map or depth map. …”
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Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network
Published 2010“…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of seven hidden nodes with hyperbolic tangent sigmoid transfer function. …”
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A new function of stereo matching algorithm based on hybrid convolutional neural network
Published 2022“…This paper proposes a new hybrid method between the learning-based and handcrafted methods for a stereo matching algorithm. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
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A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…This study aims to develop an algorithm for the AOI system to segment and detect surface defects, requiring low processing power and a small number of learning dataset with labelling error resistance. …”
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Using Pattern Matching technique for feature recognition of STEP file
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Converged Classification Network For Matching Cost Computation
Published 2020“…This map is crucial for many applications such as 3D reconstruction, robotics and autonomous driving.The disparity map also prone to errors such as noises in the region which contains object occlusions, reflective regions, and repetitive patterns.So we propose this stereo matching algorithm to produce a disparity map and to reduce the errors by incorporating a deep learning approach. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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