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modeling algorithm » scheduling algorithm (Expand Search)
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181
Peripheral inflammatory and metabolic markers as potential biomarkers in treatment-resistant schizophrenia: Insights from a Qatari Cohort
Published 2024“…Linear regression analysis revealed that MLR and clozapine treatment were significantly correlated with the severity of schizophrenia symptoms. The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87 % and 88.41 %, respectively. …”
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182
Condenser capacity and hyperbolic perimeter
Published 2022“…Our computational experiments demonstrate, for instance, sharpness of established inequalities. In the case of model problems with known analytic solutions, very high precision of computation is observed.…”
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183
Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort
Published 2023“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”
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184
Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…Fast convergence validates the efficacy of our algorithms for different system parameters. Simulation results are shown to be close to optimal for the case of newly arriving blocks.…”
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185
Machine Learning Techniques for Pharmaceutical Bioinformatics
Published 2018“…In this matrix, each drug is represented by a vector of attributes from all other drugs. A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. …”
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186
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…In the case of ensemble learning, soft voting ensembles of task-specific CNNs achieved an accuracy of 90.4%. …”
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187
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…In the case of ensemble learning, soft voting ensembles of task-specific CNNs achieved an accuracy of 90.4%. …”
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188
Capillary trapping in mixed-wet porous media: Implications for subsurface carbon dioxide sequestration
Published 2025“…Insights from this study can be used for improving pore network models and training machine learning algorithms.</p><h2>Other Information</h2><p dir="ltr">Published in: International Journal of Multiphase Flow<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijmultiphaseflow.2025.105307" target="_blank">https://dx.doi.org/10.1016/j.ijmultiphaseflow.2025.105307</a></p>…”
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189
Seasonal variations in feed-water chemistry and fouling dynamics of reverse-osmosis systems: A global climate lens
Published 2025“…<p>Reverse osmosis desalination plants are built for worst-case conditions, yet seasonal variations in feed water quality often outpace their design assumptions, leading to avoidable membrane performance losses. …”
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190
Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Most methods rely on the concept of Lowest Comment Ancestor (LCA) between two or multiple structural nodes to identify the most specific XML elements containing query keywords posted by the user. …”
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191
Revolutionizing chronic lymphocytic leukemia diagnosis: A deep dive into the diverse applications of machine learning
Published 2023“…With the significant advancements in machine learning (ML) and artificial intelligence (AI) in recent years, numerous models and algorithms have been proposed to support the diagnosis and classification of CLL. …”
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192
Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices
Published 2025“…Focusing on high-ranking cities ensures the study analyzes robust and reliable data, avoiding noise and inconsistencies arising from lower-performing or less-documented cases. Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various <u>ML algorithms</u> to categorize cities into <u>performance classes</u>, ranging from high-achieving Class 1 to emerging Class 3 cities. …”
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193
The role of Reinforcement Learning in software testing
Published 2023“…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…”
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194
A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
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195
A Multi-Channel Convolutional Neural Network approach to automate the citation screening process
Published 2021“…It was shown that for 18 out of 20 review datasets, the proposed method achieved significant workload savings of at least 10%, while in several cases, our model yielded a statistically significantly better performance over two benchmark review datasets. …”