Search alternatives:
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary based » primary case (Expand Search), primary causes (Expand Search), primary care (Expand Search)
binary basic » binary mask (Expand Search)
based stress » based surveys (Expand Search)
basic codon » basic column (Expand Search)
stress optimization » step optimization (Expand Search), process optimization (Expand Search), task optimization (Expand Search)
codon optimization » wolf optimization (Expand Search)
primary based » primary case (Expand Search), primary causes (Expand Search), primary care (Expand Search)
binary basic » binary mask (Expand Search)
based stress » based surveys (Expand Search)
basic codon » basic column (Expand Search)
-
1
-
2
-
3
Table_1_Reinforcement learning for watershed and aquifer management: a nationwide view in the country of Mexico with emphasis in Baja California Sur.XLSX
Published 2024“…<p>Reinforcement Learning (RL) is a method that teaches agents to make informed decisions in diverse environments through trial and error, aiming to maximize a reward function and discover the optimal Q-learning function for decision-making. In this study, we apply RL to a rule-based water management simulation, utilizing a deep learning approach for the Q-learning value function. …”
-
4
Image1_Adverse events related to neuromuscular blocking agents: a disproportionality analysis of the FDA adverse event reporting system.pdf
Published 2024“…A positive signal was generated when both algorithms show an association between the target drug and the AE.…”
-
5
Table1_Adverse events related to neuromuscular blocking agents: a disproportionality analysis of the FDA adverse event reporting system.xlsx
Published 2024“…A positive signal was generated when both algorithms show an association between the target drug and the AE.…”
-
6
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
Published 2025“…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”