Interpretable machine learning for predicting EUR of shale gas wells in the Weiyuan block. [PDF]
Sci RepHe S +5 more
europepmc +1 more source
CleanSurvival: automated data preprocessing for time-to-event models using reinforcement learning. [PDF]
BMC Med Inform Decis MakKoka Y +4 more
europepmc +1 more source
From Processing to Performance: A Multi-Scale Machine Learning Framework for SBS-Modified Asphalt Gels with Multi-Target Correlation and Explainable AI. [PDF]
GelsWu Z +5 more
europepmc +1 more source
A properties prediction strategy of aluminum anode foils through machine learning based on feature selection and stacking learning models. [PDF]
Sci RepPan S, Zhang Y, Luo S, Lin S.
europepmc +1 more source
Thrivaad: A Multilingual, Predictive Eye-Sign-Based AAC System Powered by Optimized Deep Learning. [PDF]
Sensors (Basel)Megalingam RK +3 more
europepmc +1 more source
Green credit risk assessment and prediction in China's construction industry: based on the optuna-catboost model. [PDF]
Sci RepQin Z, Meng M, Li D, Li J.
europepmc +1 more source
Beyond Bio-Inspired Algorithms: Using Bird Landing Dynamics to Design Adaptive Parameter Control in Metaheuristics. [PDF]
Biomimetics (Basel)Pérez A +5 more
europepmc +1 more source
Machine Learning-Driven Prediction and Design Guidance for Asphalt Concrete Using Marshall Stability and Indirect Tensile Strength. [PDF]
Materials (Basel)Xing J +5 more
europepmc +1 more source
Training PBertKla on an Integrated Multi-Source Dataset with a Machine-Learning Layer for Lysine Lactylation Site Prediction. [PDF]
Int J Mol SciJin SB +6 more
europepmc +1 more source
Samougađanje hiperparametara Cartographer algoritma korištenjem radnog okvira Optuna [PDF]
This work provides a more detailed overview of the theoretical elements of the algorithms and methods used throughout the project. A basic description of SLAM algorithms is given, followed by the specific characteristics of the Cartographer algorithm.
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