Sökning: "machine learning"

Visar resultat 11 - 15 av 926 avhandlingar innehållade orden machine learning.

1. 11. Applied Machine Learning in Steel Process Engineering : Using Supervised Machine Learning Models to Predict the Electrical Energy Consumption of Electric Arc Furnaces

   Författare :Leo Carlsson; Pär Jönsson; Peter Samuelsson; Mikael Vejdemo-Johansson; Henrik Saxen; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Electric Arc Furnace; Electrical Energy Consumption; Statistical Modelling; Machine Learning; Interpretable Machine Learning; Predictive Modelling; Industry 4.0; Ljusbågsugn; Elenergiförbrukning; Statistisk Modellering; Maskininlärning; Tolkningsbar Maskininlärning; Prediktiv Modellering; Industri 4.0; Teknisk materialvetenskap; Materials Science and Engineering; Metallurgical process science; Metallurgisk processvetenskap;

   Sammanfattning : The steel industry is in constant need of improving its production processes. This is partly due to increasing competition and partly due to environmental concerns. One commonly used method for improving these processes is through the act of modeling. LÄS MER

3. 12. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining

   Författare :Eva García Martín; Håkan Grahn; Veselka Boeva; Emiliano Casalicchio; Jesse Read; Blekinge Tekniska Högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; machine learning; energy efficiency; data stream mining; green machine learning; edge computing; Computer Science; Datavetenskap;

   Sammanfattning : Energy efficiency in machine learning explores how to build machine learning algorithms and models with low computational and power requirements. Although energy consumption is starting to gain interest in the field of machine learning, still the majority of solutions focus on obtaining the highest predictive accuracy, without a clear focus on sustainability. LÄS MER

4. 13. Incremental Clustering of Source Code : a Machine Learning Approach

   Författare :Tobias Olsson; Morgan Ericsson; Sebastian Herold; Linnéuniversitetet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Machine Learning; Naive Bayes; Source Code Clustering; Incremental Clustering; Software Architecture; Technical Debt; Computer Science; Datavetenskap;

   Sammanfattning : Technical debt at the architectural level is a severe threat to software development projects. Uncontrolled technical debt that is allowed to accumulate will undoubtedly hinder speedy development and maintenance, introduce bugs and problems in the software product, and may ultimately result in the abandonment of the source code. LÄS MER

5. 14. Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach

   Författare :Alper Idrisoglu; Johan Sanmartin Berglund; Blekinge Tekniska Högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Automated decision-support; Classification; Machine Learning; Voice-affecting disorders; Voice dataset; Voice Features; Chronic Obstructive pulmonary disease COPD ; Tillämpad hälsoteknik; Applied Health Technology;

   Sammanfattning : Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. LÄS MER

7. 15. Understanding Complex Diseases and Disease Causative Agents : The Machine Learning way

   Författare :Zeeshan Khaliq; Jan Komorowski; Steven Bosinger; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Pathogens; Influenza A viruses; Human immunodeficiency virus; Simian immunodeficiency virus; Pathogenicity; Cancer; long noncoding RNAs; Machine learning; Host specificity; Host-specific signatures; Bioinformatics; Bioinformatik;

   Sammanfattning : Diseases can be caused by foreign agents – pathogens – such as viruses, bacteria and other parasites, entering the body or by an internal malfunction of the body itself. The partial understanding of diseases like cancer and the ones caused by viruses, like the influenza A viruses (IAVs) and the human immunodeficiency virus, means we still do not have an efficient cure or defence against them. LÄS MER