Filtry
wszystkich: 8
Najlepsze wyniki w katalogu: Potencjał Badawczy Pokaż wszystkie wyniki (8)
Wyniki wyszukiwania dla: xgboost
-
Katedra Automatyki i Energetyki
Potencjał BadawczyMikroprocesorowe urządzenia pomiarowo-rejestrujące i systemy monitorowania wykorzystujące technologie sieciowe, systemy sterowania urządzeniami i procesami technologicznymi. Systemy sterowania w obiektach energetyki odnawialnej, skupionych i rozproszonych. Modelowanie i symulacja obiektów dynamicznych, procesów oraz systemów sterowania i kontroli; projektowanie interfejsów operatorskich. Systemy elektroenergetyczne i automatyki...
-
Zespół Systemów Multimedialnych
Potencjał Badawczy* technologie archiwizacji, rekonstrukcji i dostępu do nagrań archiwalnych * technologie inteligentnego monitoringu wizyjnego i akustycznego * multimedialne technologie telemedyczne * multimodalne interfejsy komputerowe
-
Zespół Systemów Multimedialnych
Potencjał Badawczy* technologie archiwizacji, rekonstrukcji i dostępu do nagrań archiwalnych * technologie inteligentnego monitoringu wizyjnego i akustycznego * multimedialne technologie telemedyczne * multimodalne interfejsy komputerowe
Pozostałe wyniki Pokaż wszystkie wyniki (11)
Wyniki wyszukiwania dla: xgboost
-
User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers
PublikacjaDevices capable of tracking the user’s gaze have become significantly more affordable over the past few years, thus broadening their application, including in-home and office computers and various customer service equipment. Although such devices have comparatively low operating frequencies and limited resolution, they are sufficient to supplement or replace classic input interfaces, such as the keyboard and mouse. The biometric...
-
Personal bankruptcy prediction using machine learning techniques
PublikacjaIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
-
Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublikacjaIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
-
Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublikacjaThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
-
Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...