Results 91 to 100 of about 286,084 (291)

Artificial Intelligence in Autonomous Mobile Robot Navigation: From Classical Approaches to Intelligent Adaptation

Advanced Intelligent Systems, EarlyView.
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella, Angelo Cardellicchio, Cosimo Patruno, Massimiliano Nitti, Nicola Pedrocchi, Vito Renò   +5 more
wiley   +1 more source

Vector search using method of clustering using ensemble of oblivious trees

Научно-технический вестник информационных технологий, механики и оптики
Information retrieval using machine learning algorithms is based on transforming the original multimodal documents into vector representations. These vectors are then indexed, and the search is performed within this index.
N. A. Tomilov, V. P. Turov, A. A. Babayants, A. V. Platonov   +3 more
doaj   +1 more source

Cost Utility Analysis of Fluticasone Exhalation Delivery System Versus Budesonide Nasal Irrigation for Chronic Rhinosinusitis With Nasal Polyps

International Forum of Allergy &Rhinology, EarlyView.
ABSTRACT Background Chronic rhinosinusitis with nasal polyps (CRSwNP) is managed after sinus surgery with topical corticosteroids. Given limited distribution of nasal steroid sprays, patients have the option of either steroid nasal irrigation (SNI) or exhalation delivery system with fluticasone (EDS‐FLU).
Daniel Xiao, Martin J. Citardi, William C. Yao, Amber U. Luong   +3 more
wiley   +1 more source

Comparative analysis of machine learning algorithms for predicting Dubai property prices

Frontiers in Applied Mathematics and Statistics
IntroductionPredicting property prices is a crucial task in the real estate market, and machine learning algorithms offer valuable tools for accurate predictions. In this study, we introduce a comprehensive comparison of eight well-known machine learning
Abdulsalam Elnaeem Balila, Ani Bin Shabri   +1 more
doaj   +1 more source

Machine Learning in Slope Stability: A Review with Implications for Landslide Hazard Assessment

GeoHazards
Slope failures represent one of the most serious geotechnical hazards, which can have severe consequences for personnel, equipment, infrastructure, and other aspects of a mining operation.
Miguel Trinidad, Moe Momayez
doaj   +1 more source

Continual decision‐making dynamics across biological organisms

Biological Reviews, EarlyView.
ABSTRACT Decision‐making is a central function of adaptive behaviour in biological agents. However, strategies for adaptive decision‐making can vary substantially across species. Here, we aim to extend the comparative scope of decision‐making analyses to phylogenetically diverse organisms.
Liberty Severs, Qiuran Wang
wiley   +1 more source

IMPLEMENTASI METODE RANDOM FOREST DALAM MEMPREDIKSI SINYAL PERGERAKAN SAHAM

E-Jurnal Matematika
Trading involves purchasing stocks at low prices and then selling them at high prices to generate profits in a short period. Although it offers significant gains, trading is considered a high-risk activity.
MOCH. ANJAS APRIHARTHA, M. HUSNIYADI, TAUFIK NUR ALAM   +2 more
doaj   +1 more source

Probabilistic Analysis for Randomized Game Tree Evaluation

, 2004
We give a probabilistic analysis for the randomized game tree evaluation algorithm of Snir. We first show that there exists an input such that the running time, measured as the number of external nodes read by the algorithm, on that input is maximal in ...
Khan, Tämur Ali, Neininger, Ralph
core   +2 more sources

Quantifying Model Selection Uncertainty in Structural Analysis: Methodology and Application

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT With increasing focus on complex engineering systems under rare events, computational models are critical for predictions due to the scarcity or absence of data. However, selecting an appropriate model can be challenging. Using a single model without available test calibration could result in significant bias in performance predictions. A case
Ya‐Heng Yang, Tracy C. Becker
wiley   +1 more source

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors

Energy Science &Engineering, EarlyView.
Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen, Linming Dou, Atao Li, Wu Cai, Lei Zhang   +4 more
wiley   +1 more source