In this article, two data-driven modeling approaches are investigated, which allow an explicit modeling of uncertainty. For this purpose, parametric Takagi-Sugeno multi-models with bounded-error parameter estimation and nonparametric Gaussian process regression are applied and compared. These models can for instance be used for robust model-based control design. As an application, the prediction of residual stresses during hard turning depending on the machining parameters and the initial hardness is considered.

Bipartite graphs are an important model for the representation and analysis of relationships between two different types of entities. Datasets in this form are commonly found in many fields, such as social networks, biology, and economics. Formal concept analysis is a research approach that allows for the analysis of such bipartite graphs by clustering the data into so-called concepts and ordering those in a lattice structure. In this thesis we propose multiple approaches for the extraction and visualization of ...

This work is a holistic investigation of the question of how and why reinforcement learning (RL) agents fail to develop planning communication in a cooperative setting. It is also a guide to anyone trying to build a system that learns to use planning communication patterns. We examine the state of the art in multi-agent systems and emergent communication for the existence of communication patterns that share information about future actions and plans. To do this, we strategically formulate hypotheses that question ...

Attribute exploration is a knowledge acquisition method from the realm of formal concept analysis that allows a domain expert to efficiently uncover the dependencies in a domain. It is based on a question-answering scheme where the exploration algorithm generates questions about dependencies in the domain that are then answered by a domain expert. Even though many variants and extension to this were developed, only few attempts to incorporate multiple experts were made. The overarching goal of this thesis is to extend ...

In this work, we will first review the Quantum Mechanics theory to derive the main equations. Next, we will analyze these equations by Functional Analysis methods to find conditions for existence, uniqueness, multiplicity, and other properties as positivity. Next, we will review and develop some numerical methods for solving the nonlinear Schrödinger equation, its time version, generalizations with rotational terms, and systems of NLSE (NLSS). We notice that the main problem to run numerical methods is the memory ...

Distributed systems have been established in many areas of IT and will play an even more significant role in the future. Such systems are no longer limited to specific fields of application but interconnect many different domains. They encompass, e. g. Cloud Computing, Internet of Things, service robotics, and autonomous vehicles. The integrated sub-systems communicate in order to exchange information and, if necessary, perform tasks together. Moreover, the number of interconnected sub-systems is constantly growing. ...

Sentiment analysis is a hot topic in many research fields such as linguistics, computer science and marketing. With the development of technology, machines can reach very high performance on explicit sentiment analysis both sentence-level and aspect-level. The role of computational linguists has also changed from handcrafting scoring rules to guide training data annotation as the algorithms are developed from rule-based scoring to deep learning models that can extract language features themselves. Moreover, research ...

Nach Angaben der Weltgesundheitsorganisation sterben weltweit noch immer jährlich rund 1,35 Millionen Menschen bei Verkehrsunfällen. Ungefähr 54% dieser Todesfälle ereignen sich unter ungeschützten Verkehrsteilnehmern wie Fußgängern, Radfahrern und Motorradfahrern. Fußgänger und Radfahrer machen dabei zusammen rund 26% aller Verkehrstoten aus. Im Gegensatz zu fahrzeugbasierten Kollisionsvermeidungssystemen setzen kooperative Systeme die Verwendung von mobilen Geräten wie Smartphones zur kontinuierlichen Erfassung von ...

Continuous Kernels have been a recent development in convolutional neural networks. Such kernels are used to process data sampled at different resolutions as well as irregularly and inconsistently sampled data. Convolutional neural networks have the property of translational invariance (e.g., features are detected regardless of their position in the measurement domain), which is unsuitable if the position of detected features is relevant for the prediction task. However, the capabilities of continuous kernels to ...

Continuous Kernels have been a recent development in convolutional neural networks. Such kernels are used to process data sampled at different resolutions as well as irregularly and inconsistently sampled data. Convolutional neural networks have the property of translational invariance (e.g., features are detected regardless of their position in the measurement domain), which is unsuitable for certain types of data, where the position of detected features is relevant. However, the capabilities of continuous kernels ...