Essays about: "extreme gradient boosting model"

Showing result 1 - 5 of 26 essays containing the words extreme gradient boosting model.

1. 1. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES

   University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

   Author : Humphry Takang Bate; [2023]
   Keywords : ;

   Abstract : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. READ MORE

3. 2. Machine Learning of Laser Ultrasonic Data to Predict Material Properties

   University essay from Linköpings universitet/Statistik och maskininlärning

   Author : Filip Tuvenvall; [2023]
   Keywords : Machine Learning; Laser Ultrasonics; Material Properties; Steel; Hardness of Steel;

   Abstract : The hardness of steel is an important quality parameter for several industrial applications. Conventional mechanical testing is used in quality testing for material hardness and the method is time-consuming, can cause material mix-ups, and results in material waste. READ MORE

4. 3. A Comparative Analysis of Decision Tree Models in Identifying Landslide Susceptibility and Type Classification

   University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Author : Levi Jan Zuiverloon; [2023]
   Keywords : Landslides; landslide susceptibility mapping; Random Forest; Extreme Gradient Boosting; machine learning models; multiclass classification; binary classification; risk assessment; mitigation strategies; Italy; Aosta Valley; infrastructure vulnerability; supervised learning algorithms; Earth and Environmental Sciences;

   Abstract : Landslides pose a significant risk to human life and infrastructure, especially in Italy, which has a high frequency of landslide occurrences. To mitigate these hazards, Landslide Susceptibility Mapping (LSM) is crucial for identifying risk areas and developing appropriate mitigation strategies. READ MORE

5. 4. Predicting Short-term Absences of a Railway Crew using Historical Data

   University essay from KTH/Matematisk statistik

   Author : Agnes Björnfot; Sandra Fjelkestam; [2023]
   Keywords : statistics; machine learning; absence prediction; random forest; XGBoost; quantile regression; statistik; maskininlärning; frånvaroprognoser; random forest; XGBoost; kvantilregression;

   Abstract : Transportation via train is considered the most environmentally friendly way of traveling and is widely seen as the future of transportation. Canceled and delayed trains worsen customer satisfaction; thus, punctual trains are crucial for railway companies. READ MORE

6. 5. Toward an application of machine learning for predicting foreign trade in services – a pilot study for Statistics Sweden

   University essay from Stockholms universitet/Statistiska institutionen

   Author : Tea Unnebäck; [2023]
   Keywords : foreign trade in services; sampling; sampling frame; statistics; machine learning; random forest; predicting; extreme gradient boosting; k nearest neighbors; k-nn; official statistics; statistics sweden;

   Abstract : The objective of this thesis is to investigate the possibility of using machine learn- ing at Statistics Sweden within the Foreign Trade in Services (FTS) statistic, to predict the likelihood of a unit to conduct foreign trade in services. The FTS survey is a sample survey, for which there is no natural frame to sample from. READ MORE