Machine learning approaches for auto insurance big data
M Hanafy, R Ming - Risks, 2021 - mdpi.com
The growing trend in the number and severity of auto insurance claims creates a need for
new methods to efficiently handle these claims. Machine learning (ML) is one of the methods …
new methods to efficiently handle these claims. Machine learning (ML) is one of the methods …
Integrating capacity and efficiency for optimal hydrogen storage site selection in saline aquifers
Hydrogen (H2) energy is a promising transition pathway from conventional fossil fuels to
sustainable clean energy. However, H2 requires a large storage capacity because of its low …
sustainable clean energy. However, H2 requires a large storage capacity because of its low …
Artificial neural network-based geometry compensation to improve the printing accuracy of selective laser melting fabricated sub-millimetre overhang trusses
Selective laser melting processes deposit and join metal powders to near net shape in a
layer-by-layer manner. The process of melting and re-solidification of several layers of …
layer-by-layer manner. The process of melting and re-solidification of several layers of …
Investigation of factors affecting transactional distance in E-learning environment with artificial neural networks
In this study, the factors affecting the transactional distance levels of university students who
continue their courses with distance education in the 2020–2021 academic years due to the …
continue their courses with distance education in the 2020–2021 academic years due to the …
[HTML][HTML] Metamodel-based generative design of wind turbine foundations
Q Shen, F Vahdatikhaki, H Voordijk… - Automation in …, 2022 - Elsevier
Wind turbines play an integral role in energy transition agendas. The optimized design of
wind turbine foundations is a complex and intricate task that requires iterative running of …
wind turbine foundations is a complex and intricate task that requires iterative running of …
Principal component analysis and machine learning approaches for photovoltaic power prediction: A comparative study
Nowadays, in the context of the industrial revolution 4.0, considerable volumes of data are
being generated continuously from intelligent sensors and connected objects. The proper …
being generated continuously from intelligent sensors and connected objects. The proper …
[PDF][PDF] Analysis of Factors Effecting PISA 2015 Mathematics Literacy via Educational Data Mining.
Programme for International Student Assessment–PISA, financed by Organization for
Economic Co-operation and Development (OECD), is a large scale research targeting to …
Economic Co-operation and Development (OECD), is a large scale research targeting to …
Spatial assessment of solar radiation by machine learning and deep neural network models using data provided by the COMS MI geostationary satellite: A case study …
Although data-driven methods including deep neural network (DNN) were introduced, there
was not enough assessment about spatial characteristics when using limited ground …
was not enough assessment about spatial characteristics when using limited ground …
Machine learning modeling of horizontal photovoltaics using weather and location data
Solar energy is a key renewable energy source; however, its intermittent nature and
potential for use in distributed systems make power prediction an important aspect of grid …
potential for use in distributed systems make power prediction an important aspect of grid …
Multimodal learning analytics for assessing teachers' self-regulated learning in planning technology-integrated lessons in a computer-based environment
Teachers' self-regulated learning (SRL) plays a crucial role in develo** technological
pedagogical content knowledge (TPACK), a complex professional skill. It is crucial to identify …
pedagogical content knowledge (TPACK), a complex professional skill. It is crucial to identify …