A Closer Look at Invalid Action Masking in Policy Gradient Algorithms by Shengyi Huang, Santiago Ontañón

“…In recent years, Deep Reinforcement Learning (DRL) algorithms have achieved state-of-the-art performance in many challenging strategy games. …”
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Self-Stabilizing TDMA Algorithms for Dynamic Wireless Ad Hoc Networks by Pierre Leone, Elad M. Schiller

“…We propose a self-stabilizing MAC algorithm for DynWANs that guarantees a short convergence period, and by that, it can facilitate the satisfaction of severe timing requirements, such as the above. …”
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Efficient Machine Learning Algorithms in Hybrid Filtering Based Recommendation System by . Ruchika, Mayank Sharma, Syed Akhter Hossain

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Advancing Hyperspectral Image Classification with Deep Features Learning and Evolutionary Algorithms by M. B. Amri, M. B. Amri, D. Yedjour, M. E. A. Larabi, F. Berrichi

“…In addition, the experiments conducted on simulated benchmarks validate the superior performance of the proposed approach compared to the baseline ML model in terms of prediction accuracy and F1-score.…”
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Comparison of algorithms using deep reinforcement learning for optimization of hyperbolic metamaterials by Kenta Hamada, Hui-Hsin Hsiao, Wakana Kubo

“…By analyzing the absorption spectra obtained from the three algorithms with limited number of datasets, we assessed the prediction accuracy of each algorithm. …”
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An Exploratory Application of Machine Learning Algorithms in Estimating Net Salaries in Romania by Adriana Aiftincăi

“…The results demonstrate a high prediction accuracy (MAE: 59.47 lei, RMSE: 97.60 lei – Random Forest model), providing realistic values for future salary scenarios. …”
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Wind Farm Layout Optimization Problem Using Nature-Inspired Algorithms by Mukesh Kumar, Ajay Sharma, Nirmala Sharma, Fani Bhushan Sharma, Mahendra Bhadu

“…Nowadays, researchers from a variety of fields are developing nature-inspired algorithms (NIAs) to solve difficult real-world problems. …”
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Scattering-Based Machine Learning Algorithms for Momentum Estimation in Muon Tomography by Florian Bury, Maxime Lagrange

“…Several real-life requirements are considered, such as the inclusion of hit reconstruction efficiency and resolution and the need for a momentum resolution prediction that can improve reconstruction methods.…”
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Computational Analysis of Self-Healing in Nanomaterials Using Neural Spike Algorithms by Jongho Seol, Jongyeop Kim, Abhilash Kancharla

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Validation of Material Algorithms for Femur Remodelling Using Medical Image Data by Shitong Luo, Xingquan Shen, Xin Bai, Jing Bai, Jianning Han, Yu Shang

“…Moreover, the simulated L-T ratios (the ratio of longitude modulus to transverse modulus) by the orthotropic algorithm were close to the reported results. This study suggests a role for “error-driven” algorithm in bone material prediction in abnormal mechanical environment and holds promise for optimizing implant design as well as developing countermeasures against bone loss due to weightlessness. …”
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Psychological artificial intelligence: Designing algorithms to deal with the uncertainty of rework in construction by Peter E.D. Love, Jane Matthews, Weili Fang

“…Bayesian statistical models cannot be utilized to predict rework as objective, and even subjective probabilities are unknown. …”
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Accuracy Comparison of Machine Learning Algorithms on World Happiness Index Data by Sadullah Çelik, Bilge Doğanlı, Mahmut Ünsal Şaşmaz, Ulas Akkucuk

“…Subsequently, classification algorithms are used to predict the cluster membership and the accuracy scores obtained serve as an indirect measure of the clustering quality. …”
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Application of Metaheuristic Algorithms and ANN Model for Univariate Water Level Forecasting by Sarah J. Mohammed, Salah L. Zubaidi, Nadhir Al-Ansari, Hussein Mohammed Ridha, Anmar Dulaimi, Ruqayah Al-Khafaji

“…The methodology includes preprocessing data methods, and the ANN model optimises with a marine predator algorithm (MPA). In the optimisation procedure, to decrease uncertainty and expand the predicting range, the slime mould algorithm (SMA-ANN), constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithms (CPSOCGSA-ANN), and particle swarm optimisation (PSO-ANN) are applied to compare and validate the MPA-ANN model performance. …”
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Random Oversampling-Based Diabetes Classification via Machine Learning Algorithms by G. R. Ashisha, X. Anitha Mary, E. Grace Mary Kanaga, J. Andrew, R. Jennifer Eunice

“…The proposed approach considers ML algorithms such as random forest, gradient boosting models, light gradient boosting classifiers, and decision trees, as they are widely used classification algorithms for diabetes prediction. …”
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Comparison of three one-dimensional time-domain electromagnetic forward algorithms by Frederik Alexander Falk, Anders Vest Christiansen, Thomas Mejer Hansen

“…Accurate, efficient, and accessible forward modeling of geophysical processes is essential for understanding them and for inversion of geophysical data. Various algorithms are available for predicting data with the time domain electromagnetic method (TDEM). …”
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Machine Learning Algorithms for Nondestructive Sensing of Moisture Content in Grain and Seed by Arthur P. LeBlanc, Samir Trabelsi, Khaled Rasheed, John A. Miller

“…Performance of this model is investigated and compared with models trained on an individual grain or seed by using different algorithms, including artificial neural network (NN), support vector regression (SVR), ElasticNet, among other algorithms. …”
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Cross-validation for training and testing co-occurrence network inference algorithms by Daniel Agyapong, Jeffrey Ryan Propster, Jane Marks, Toby Dylan Hocking

“…We propose a novel cross-validation method to evaluate co-occurrence network inference algorithms, and new methods for applying existing algorithms to predict on test data. …”
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An evaluation of flow-routing algorithms for calculating contributing area on regular grids by A. B. Prescott, J. D. Pelletier, S. Chataut, S. Ananthanarayan

“…We revisit the purported excess dispersion of the multiple-flow-direction (MFD) algorithm of Freeman (1991) that motivated the development of <span class="inline-formula"><i>D</i>∞</span> and demonstrate that MFD is superior to <span class="inline-formula"><i>D</i>∞</span> when tested against analytic solutions for the contributing areas of idealized landforms and the predictions of the shallow-water equation solver FLO-2D for more complex landforms in which the water surface slope is closely approximated by the bed slope. …”
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From multi-omics to predictive biomarker: AI in tumor microenvironment by Luo Hai, Luo Hai, Ziming Jiang, Haoxuan Zhang, Yingli Sun, Yingli Sun, Yingli Sun

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Research on SBMPC Algorithm for Path Planning of Rescue and Detection Robot by Lin-Lin Wang, Li-Xin Pan

“…Sampling-Based Model Predictive Control (SBMPC) algorithm is proposed basing on the construction of cost function and predictive kinematics model. …”
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