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Adaptive Linear System Identification over Simulated Wireless Environment
Published 2009“…The work looks thoroughly on three forms of instantaneous learning algorithms which are: first order algorithms (e.g. least mean square (LMS)), second order algorithms (e.g. …”
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron
Published 2013“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…Hitherto, the majority of computer vision approaches have been focused on designing sophisticated algorithms to achieve a robust feature representation for plant data. …”
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Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning
Published 2023“…Augmented reality; Learning algorithms; Machine learning; Usability engineering; Between clusters; Mobile augmented reality; Prioritization; Prioritization techniques; Unsupervised machine learning; Usability; K-means clustering…”
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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms
Published 2022“…The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. …”
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Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer
Published 2018“…Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…This work investigates the suitability and effectiveness of machine learning algorithms such as Multinomial Naive Bayes, KNN, Logistic Regression, Decision Tree for predicting levels of arousal intensity among the programmers and LSTM deep learning algorithm to classify the programmers according to their performance. …”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich
Published 2019“…The main objective of this work is to propose and implement an efficient handover decision procedure based on users’ profiles using Q-learning technique in a LTE-A macrocell-femtocell networks. …”
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Comparison of Gradient Boosting Decision Tree Algorithms for CPU Performance
Published 2021“…This paper aims to compare the performance of CPU implementation of the top three gradient boosting algorithms. We start by explaining how the three algorithms work and the hyperparameters similarities between them. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…In one-side incomplete information problem, comparison between MGT algorithm and smart random trade-offs (SRT) algorithm indicates that MGT outperforms SRT. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
Published 2015“…The lack of diversity has been solved in this work by replacing the inactive particles adaptively based on a predefined constant which represents the difference between local best and global best optimization criterion. …”
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