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141
Performance Modeling of Rooftop PV Systems in Arid Climate, a Case Study for Qatar: Impact of Soiling Losses and Albedo Using PVsyst and SAM
Published 2025“…The optimized approach reduced the root mean square error (RMSE) of predicted soiling ratios from 7.30 to 1.93 and improved the agreement between simulated and measured monthly energy yields for 2024, achieving normalized RMSE values of 4.66% in SAM and 4.86% in PVsyst. The findings demonstrate that coupling data-driven soiling optimization with refined albedo representation modernizes the predictive capabilities of PVsyst and SAM, yielding more reliable performance forecasts. …”
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142
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143
An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation
Published 2001“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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144
An evolutionary meta-heuristic for state justification insequential automatic test pattern generation
Published 2001“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic Algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
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145
Approximate XML structure validation based on document–grammar tree similarity
Published 2015“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
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146
Growing hierarchical self-organizing map for filtering intrusion detection alarms
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conferenceObject -
147
Approximate XML structure validation technical report
Published 2014“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
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148
A Comprehensive Overview of the COVID-19 Literature: Machine Learning–Based Bibliometric Analysis
Published 2021“…Publishers should avoid noise in the data by developing a way to trace the evolution of individual publications and unique authors.…”
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149
AI-Based Methods for Predicting Required Insulin Doses for Diabetic Patients
Published 2015“…This results in an enormous amount of data. Endocrinologists need to find a certain pattern in this data that would help them determine the optimal dosage of insulin to administer to each patient. …”
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150
Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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151
The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions
Published 2022“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”
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152
Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012)
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153
Machine Learning Model for a Sustainable Drilling Process
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154
Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings
Published 2022“…Experiments with features showed that acceleration data were the most contributing factor on the prediction compared to gyroscope data and that combined data of raw and extracted features provided a better overall performance. …”
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155
Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context
Published 0024“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. Machine learning algorithms can process large and complex datasets to identify patterns and trends that may not be immediately apparent. …”
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156
A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”
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157
An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. FS is an important data reduction step in data mining which finds the most representative features from the entire data. …”
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158
Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations
Published 2025“…Traditional methods often rely on centralized servers to gather and analyze consumption data, which can lead to significant privacy risks as personalized information becomes accessible online. …”
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159
Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features
Published 2024“…<p dir="ltr">Stress recognition, particularly using machine learning (ML) with physiological data such as heart rate variability (HRV), holds promise for mental health interventions. …”
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160
Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri...
Published 2025“…Yet several barriers were highlighted. Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …”
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