Sökning: "machine-learning"
Visar resultat 1 - 5 av 866 avhandlingar innehållade ordet machine-learning.
1. Machine learning for building energy system analysis
Sammanfattning : Buildings account for approximately 40% of the global energy, and Heating, Ventilation, and Air Conditioning (HVAC) contributes to a large proportion of building energy consumption. Two main negative characteristics that contribute to performance degradation and energy waste in an HVAC system are inappropriate control strategies and faults. LÄS MER
2. Applied Machine Learning in Steel Process Engineering : Using Supervised Machine Learning Models to Predict the Electrical Energy Consumption of Electric Arc Furnaces
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. Energy Efficiency in Machine Learning : Approaches to Sustainable Data Stream Mining
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. Incremental Clustering of Source Code : a Machine Learning Approach
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. Protein Model Quality Assessment : A Machine Learning Approach
Sammanfattning : Many protein structure prediction programs exist and they can efficiently generate a number of protein models of a varying quality. One of the problems is that it is difficult to know which model is the best one for a given target sequence. Selecting the best model is one of the major tasks of Model Quality Assessment Programs (MQAPs). LÄS MER