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Multilayer perceptron-based DFE with lattice structure
Published 2001“…The adaptive lattice algorithm is a modification to the one developed by Ling and Proakis (1985). …”
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Multilayer perceptron-based DFE with lattice structure
Published 2001“…The adaptive lattice algorithm is a modification to the one developed by Ling and Proakis (1985). …”
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143
Anomaly Detection Based Framework for Profile Monitoring
Published 2023Get full text
doctoralThesis -
144
Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends
Published 2024“…The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. …”
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145
Reinforced steering Evolutionary Markov Chain for high-dimensional feature selection
Published 2024“…The proposed work has the following contributions and merits: (i) The paradigms of evolutionary computation, reinforcement learning, and Markov chain are incorporated into an integrational framework for feature selection in high dimensional spaces in a recursive manner. (ii) To support the global convergence of the algorithm and manage its computational complexity, a restricted group of the most effective agents is maintained within the evolutionary population. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”
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147
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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148
Machine Learning-Based Approach for EV Charging Behavior
Published 2021Get full text
doctoralThesis -
149
Severity-Based Prioritized Processing of Packets with Application in VANETs
Published 2019“…We thus develop a real-time heuristic that utilizes a relaxed version of the formulation. …”
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150
Improving Rule Set Based Software Quality Prediction
Published 2003Get full text
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151
Indoor Localization Based on Floor Plans and Power Maps
Published 2015“…An indoor localization algorithm that is based on fingerprinting and trilateration is developed. …”
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152
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Autonomous Robot Navigation Based On Recurrent Neural Networks
Published 2012Get full text
doctoralThesis -
154
A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm
Published 2023“…The t-test and the binary whale optimization algorithm (BWOA) were applied to choose the best features and train the support vector machine (SVM) model with validation and training data. …”
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155
Variable Selection in Data Analysis: A Synthetic Data Toolkit
Published 2024“…Lastly, we provide public access to the generated datasets to facilitate bench-marking of new feature selection algorithms in the field via our Github repository. The contributions of this paper aim to foster the development of novel feature selection algorithms and advance their study.…”
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156
Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates
Published 2020“…Each pair of enhanced LULC maps (1990–2000, 2000–2010, 2010–2018, and 1990–2018) were used as input data for an image difference algorithm to monitor LULC changes. …”
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Wind, Solar, and Photovoltaic Renewable Energy Systems with and without Energy Storage Optimization: A Survey of Advanced Machine Learning and Deep Learning Techniques
Published 2022“…This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. …”
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