ABSTRACT: NILM (Nonintrusive Load Monitoring) or appliance recognition software that uses algorithms, namely Hidden Markov Model (HMM) and Factorial HMM, to detect changes in electricity values ...
Abstract: Transformer is the core equipment in power system. Winding faults are the main causes of sudden accidents, and it is important to obtain the winding status timely. This paper studies the ...
(Toronto, March 11, 2026) Researchers at Fondazione Policlinico Universitario Agostino Gemelli IRCCS have developed a promising machine learning algorithm capable of predicting survival and cause of ...
Train classification model with default params in silent mode. Calc model predictions on custom data set, output will contain evaluated class1 probability: catboost fit --learn-set train.tsv ...
Traditional statistical models often fail to capture the complex dynamics influencing survival outcomes in patients with bladder cancer after radical cystectomy, a procedure where approximately 50% of ...
Complete end-to-end AI pipeline for soil disease classification from sensor data. The system achieves 85.17% accuracy with F1-macro score of 0.8472 across 7 disease classes.
Social media algorithms determine what billions of users see daily, yet most creators barely scratch the surface of how they operate. Platforms prioritize content ranking using engagement metrics, ...
ABSTRACT: Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and ...
Interpretable Machine Learning Framework for Biomass–Plastic Co-gasification. This graphical workflow illustrates the development of an interpretable machine learning framework to predict syngas ...
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