On Spatio Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory is popular PDF and ePub book, written by Fabian Guignard in 2022-03-12, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, On Spatio Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory can be Read Online from any device for your convenience.
On Spatio Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory Book PDF Summary
The gathering and storage of data indexed in space and time are experiencing unprecedented growth, demanding for advanced and adapted tools to analyse them. This thesis deals with the exploration and modelling of complex high-frequency and non-stationary spatio-temporal data. It proposes an efficient framework in modelling with machine learning algorithms spatio-temporal fields measured on irregular monitoring networks, accounting for high dimensional input space and large data sets. The uncertainty quantification is enabled by specifying this framework with the extreme learning machine, a particular type of artificial neural network for which analytical results, variance estimation and confidence intervals are developed. Particular attention is also paid to a highly versatile exploratory data analysis tool based on information theory, the Fisher-Shannon analysis, which can be used to assess the complexity of distributional properties of temporal, spatial and spatio-temporal data sets. Examples of the proposed methodologies are concentrated on data from environmental sciences, with an emphasis on wind speed modelling in complex mountainous terrain and the resulting renewable energy assessment. The contributions of this thesis can find a large number of applications in several research domains where exploration, understanding, clustering, interpolation and forecasting of complex phenomena are of utmost importance.
Detail Book of On Spatio Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory PDF
- Author : Fabian Guignard
- Release : 12 March 2022
- Publisher : Springer Nature
- ISBN : 9783030952310
- Genre : Science
- Total Page : 170 pages
- Language : English
- PDF File Size : 12,5 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book On Spatio Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory by Fabian Guignard, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.