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Zoekresultaten (8)

HBO/WO

MBO

1 november 2024

Computational Modelling of Terrains

An open textbook about the algorithms and methodologies to reconstruct, manipulate, and extract information from terrains (or DTMs or DEMs). It covers different representations of terrains (eg TINs, rasters, point clouds, contour lines) and presents techniques to handle large datasets. The book is currently used for the course Digital Terrain Modelling (GEO1015) in the MSc Geomatics at the Delft University of Technology in the Netherlands. The course is tailored for MSc students who have already followed an introductory course in GIS and in programming. Each chapter is a lesson in the course, and each lesson is accompanied by a video introducing the key ideas and/or explaining some parts of the lessons.

Open (Access) Tekst Boek

Hugo Ledoux

30 december 2025

Lessons Learned

Agent-based modelling (ABM) is one of the most widely applied computational modelling research techniques in archaeology, because it is well suited to the questions asked by archaeologists. However, the access to vocational training for ABM is limited. In this paper we present the Open Educational Resources (OER) that we produced in an international cooperation. For this purpose, we created online and open tutorials for ABM for archaeologists. In addition, how-to guides and support material were created, both for teachers and students. The materials adhere to international (European) standards in relation to education and the Digital Skills Passport for archaeology. The teaching materials have been well tested using a diverse group of archaeologists during various international conferences and meetings. It was shown that the knowledge and skills of the participants in relation to ABM improved. In addition, the demand for the teaching materials and the workshops was high, ensuring that the tutorials on ABM will be used in the future.

Document

Ronald Visser, Karsten Lambers, Kenneth Aitchison, Annemarie Jutte, James Douglas Rocks-Macqueen, Laura van der Knaap, Iza Romanowska, Tom Brughmans, Jeroen Linssen, Adam Pažout

23 augustus 2023

Lecture: Natural Language Processing

Students understand the basic concepts of Natural Language Processing Students learn NLP use cases Students get familiar with various NLP tools and concepts

Website

HCAIM Consortium

29 juli 2024

Classical Numerical Methods in Scientific Computing

Partial differential equations are paramount in mathematical modelling with applications in engineering and science. The book starts with a crash course on partial differential equations in order to familiarize the reader with fundamental properties such as existence, uniqueness and possibly existing maximum principles. The main topic of the book entails the description of classical numerical methods that are used to approximate the solution of partial differential equations. The focus is on discretization methods such as the finite difference, finite volume and finite element method. The manuscript also makes a short excursion to the solution of large sets of (non)linear algebraic equations that result after application of discretization method to partial differential equations. The book treats the construction of such discretization methods, as well as some error analysis, where it is noted that the error analysis for the finite element method is merely descriptive, rather than rigorous from a mathematical point of view. The last chapters focus on time integration issues for classical time-dependent partial differential equations. After reading the book, the reader should be able to derive finite element methods, to implement the methods and to judge whether the obtained approximations are consistent with the solution to the partial differential equations. The reader will also obtain these skills for the other classical discretization methods. Acquiring such fundamental knowledge will allow the reader to continue studying more advanced methods like meshfree methods, discontinuous Galerkin methods and spectral methods for the approximation of solutions to partial differential equations.

Open (Access) Tekst Boek

Jos van Kan, Guus Segal, Hans Kraaijevanger, Fred Vermolen

1 september 2020

Introduction to Financial Derivatives

Financial derivatives are widely used as instruments to modify exposures to various types of financial risk. Examples include call options on a stock index, interest rate derivatives such as swaptions, and credit derivatives. The theory of financial derivatives, as it has been developed in recent decades, is based on a mix of economic ideas and concepts from mathematics. The material in this Open Press textbook originates from notes for a course that the author has taught at Tilburg University for more than ten years, as part of the MSc program in Quantitative Finance and Actuarial Science. The text aims to provide students with an introduction to continuous-time models that are used to analyze derivative contracts in finance and insurance. Users are expected to have a solid background in standard calculus, linear algebra, and probability; prior experience with stochastic calculus, however, is not a prerequisite.

Open (Access) Tekst Boek

Johannes M. Schumacher

17 september 2024

Dynamic data processing: Recursive least-squares

This book is a follow-up on Adjustment theory. It extends the theory to the case of time-varying parameters with an emphasis on their recursive determination. Least-squares estimation will be the leading principle used. A least-squares solution is said to be recursive when the method of computation enables sequential, rather than batch, processing of the measurement data. The recursive equations enable the updating of parameter estimates for new observations without the need to store all past observations. Methods of recursive least-squares estimation are therefore particularly useful for applications in which the time-varying parameters need to be instantly determined. Important examples of such applications can be found in the fields of real-time kinematic positioning, navigation and guidance, or multivariate time series analysis. The goal of this book is therefore to convey the necessary knowledge to be able to process sequentially collected measurements for the purpose of estimating time-varying parameters. When determining time-varying parameters from sequentially collected measurement data, one can discriminate between three types of estimation problems: filtering, prediction and smoothing. Filtering aims at the determination of current parameter values, while smoothing and prediction aim at the determination of respectively past and future parameter values. The emphasis in this book will be on recursive least-squares filtering. The theory is worked out for the important case of linear(ized) models. The measurement-update and time-update equations of recursive least-squares are discussed in detail. Models with sequentially collected data, but time-invariant parameters are treated first. In this case only the measurement-update equations apply. State-space models for dynamic systems are discussed so as to include time-varying parameters. This includes their linearization and the construction of the state transition matrix. Elements from the theory of random functions are used to describe the propagation laws for linear dynamic systems. The theory is illustrated by means of many worked out examples. They are drawn from applications such as kinematic positioning, satellite orbit determination and inertial navigation.

Open (Access) Tekst Boek

Peter Teunissen

1 januari 2021

Theoretical modeling for cognitive science and psychology

Welcome to this open and interactive textbook on theoretical modeling for cognitive science and psychology. Are you a student or researcher in cognitive science or psychology? Would you like to be able to make your own, formally precise, theoretical models? You have no or little prior training in theory or modeling? This book is a place to start! Or, perhaps, you do have experience with theory and modeling but want to expand your skill and tool sets; or alternatively, you are just curious to have a taste of theoretical modeling to see what it is like? Whatever your interests, you are welcome here! Table of contents PART I - INTRO Chapter 1 - Introduction Chapter 2 - Conceptual foundations PART II - FORMALIZING Chapter 3 - Math concepts and notation Chapter 4 - Subset choice Chapter 5 - Coherence PART III - SIMULATING Chapter 8 - Simulating in Scala Chapter 9 - Scala and mathlib Chapter 10 - Subset choice Cover art The cover art is by Danielle Navarro (used with permission & released under CC-BY-SA 4.0). Danielle Navarro’s award-winning open textbook Learning Statistics with R and open teaching materials R for Psychological Science inspired us to write this open and online textbook. Choosing her art for the book’s cover represents our gratitude for this inspiration as much as our love for her artwork. License This open textbook is released under a CC-BY 4.0 license and the Scala software used herein is released under an UGN GPL v3 license or any later version. This book is written in Jekyll using the tufte-jekyll theme released under an MIT license. The source code is available on Github: https://github.com/computationalcognitivescience/lovelace How to cite this book Blokpoel, M. & van Rooij, I. (2021). Theoretical modeling for cognitive science and psychology. Retrieved [date] from [URL]. In-progress At present this book is a living document, some sections have been written while others are still under construction. If the parts you are interested in aren’t finished yet, please check back at a later time. Feedback and suggestions are welcome. About the authors Mark Blokpoel is a computer scientist and computational cognitive scientist. Iris van Rooij is a psychologist and cognitive scientist. Both authors are based at Donders Institute for Brain, Cognition, and Behaviour, Radboud University. Parts of this book were written while Van Rooij was at the Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS). Van Rooij and Blokpoel previously co-authored Cognition and Intractability with Johan Kwisthout and Todd Wareham. Reuse of materials Parts of this book are based on materials that previously appeared in: van Rooij, I., & Baggio, G. (2021). Theory before the test: How to build high-verisimilitude explanatory theories in psychological science. Perspectives on Psychological Science. van Rooij, I., & Blokpoel, M. (2020). Formalizing verbal theories: A tutorial by dialogue. Social Psychology, 51(5), 285-298 Specifically, parts of these papers were reused in the ‘Conceptual Foundations’, the ‘Math Concepts and Notation’, and ‘Subset Choice’ chapters. Acknowledgements We have learned a lot from participants in courses and workshops that we taught on the topic over the last 10 years. We would like to thank them all. This includes hundreds of BSc Artificial Intelligence students and dozens of Psychology, Cognitive Neuroscience, and Computer Science BSc, MSc and PhD students who have taken the Computational & Formal Modeling course at Radboud University. It also includes PhD students at the Behavioural Science Institute, staff at the Dept. of Social Psychology at Radboud University, and members of the Experimental Psychopathology and Affective Neuroscience (EPAN) research group at the Donders Institute who participated in workshops that we organized on the topic of this book. This work has been made possible by a Distinguished Lorentz Fellowship (DLF) & Prize awarded by NIAS and the Lorentz Center to Van Rooij and a Language in Interaction grant (nr. 024.001.006) supporting Blokpoel.

Open (Access) Tekst Boek

Mark Blokpoel, Iris van Rooij

26 juli 2020

4. Solution strategies

This publication contains two videos about solution strategies. In this first part of the series of solution strategies, you will learn a few solution strategies that can be used to solve problems. The video consists of two parts. In this part you will learn how to approach a problem, you will learn the solution strategies, guess and check, go through all the possibilities, and the divide a problem into subproblems. In this second part of the series of solution strategies, you will learn the use of formulas, discover a structure, make a model, the brute force, and the D&C solution strategies to solve problems.

Video

Aniel Bhulai