Tag: Spatio

Free Download Stefan Meinecke, "Spatio-Temporal Modeling and Device Optimization of Passively Mode-Locked Semiconductor Lasers "
English | ISBN: 3030962474 | 2022 | 269 pages | PDF | 10 MB
This thesis investigates passively mode-locked semiconductor lasers by numerical methods. The understanding and optimization of such devices is crucial to the advancement of technologies such as optical data communication and dual comb spectroscopy. The focus of the thesis is therefore on the development of efficient numerical models, which are able both to perform larger parameter studies and to provide quantitative predictions. Along with that, visualization and evaluation techniques for the rich spatio-temporal laser dynamics are developed; these facilitate the physical interpretation of the observed features.

Free Download Fabian Guignard, "On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory "
English | ISBN: 3030952304 | 2022 | 176 pages | PDF | 6 MB
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.

Free Download Spatio-Temporal Models for Ecologists
English | 2024 | ISBN: 1032531010 | 294 Pages | PDF (True) | 18 MB
Ecological dynamics are tremendously complicated and are studied at a variety of spatial and temporal scales. Ecologists often simplify analysis by describing changes in density of individuals across a landscape, and statistical methods are advancing rapidly for studying spatio-temporal dynamics. However, spatio-temporal statistics is often presented using a set of principles that may seem very distant from ecological theory or practice. This book seeks to introduce a minimal set of principles and numerical techniques for spatio-temporal statistics that can be used to implement a wide range of real-world ecological analyses regarding animal movement, population dynamics, community composition, causal attribution, and spatial dynamics. We provide a step-by-step illustration of techniques that combine core spatial-analysis packages in R with low-level computation using Template Model Builder. Techniques are showcased using real-world data from varied ecological systems, providing a toolset for hierarchical modelling of spatio-temporal processes. Spatio-Temporal Models for Ecologists is meant for graduate level students, alongside applied and academic ecologists.