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121
Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…It was found that the calibrated model achieved these metrics with RMSE of 0.3 ◦C, and MAD of 0.8 ◦C, and 85% of data points with an error less than 0.5 ◦C for a school building case.…”
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122
Haplotype inference by pure-parsimony using revamped delayed haplotype selection. (c2011)
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masterThesis -
123
Parallel implementation of clique partitioning using artificial neural networks. (c2000)
Published 2000Get full text
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masterThesis -
124
Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE
Published 2018“…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …”
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125
Stacking-based ensemble learning for remaining useful life estimation
Published 2023“…In this study, predictive models that estimate the remaining useful life of turbofan engines have been developed using deep learning algorithms on NASA’s turbofan engine degradation simulation dataset. …”
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126
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127
A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
Published 2022“…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …”
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128
Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…The obtained results illustrate the efficacy of the proposed algorithm to analyze the time series data from the IoT devices for spam detection.…”
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129
Content-Aware Adaptive Video Streaming Using Actor-Critic Deep Reinforcement Learning
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doctoralThesis -
130
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131
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132
BUC algorithm for iceberg cubes
Published 2003“…The Uniform distribution is used as a basis for comparison. Results show that when the cube is sparse there is a correlation between the data distribution and the running time of the algorithm. …”
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conferenceObject -
133
An enhanced quorum selection algorithm
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134
An Improved Quorum Selection Algorithm
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conferenceObject -
135
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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136
Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…Different classification algorithms were applied to the dataset using the Rapidminer tool. …”
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137
The use of multi-task learning in cybersecurity applications: a systematic literature review
Published 2024“…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”
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138
A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995)
Published 1995Get full text
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masterThesis -
139
Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT
Published 2021“…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”
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140
QU-GM: An IoT Based Glucose Monitoring System From Photoplethysmography, Blood Pressure, and Demographic Data Using Machine Learning
Published 2024“…Bagged Ensemble Trees outperform other algorithms in estimating blood glucose level with a correlation coefficient of 0.90. …”