This chapter describes some highlights of successful research focusing on knowledge-based and data-driven models for industrial and decision processes. This research has been carried out during the last ten years in a close cooperation of two research institutions in Hagenberg: - the Fuzzy Logic ...
For decision points in a behavioral model, smart agents can be trained based on data samples collected from rounds of constructive simulations which provide validated physical models and tactical principles. As a proof of concept, we constructed a simulation testbed of multi-warhead ballistic missile ...
Since the formalisation of problem-specific human expert knowledge is often difficult and tedious, data-driven machine learning techniques may be helpful to extract knowledge from ecological datasets. In this paper, both expert knowledge-based and data-driven fuzzy habitat suitability models were ...
(1) a knowledge-driven fuzzy model that uses a logistic membership function for deriving fuzzy membership values of input evidential maps and (2) a data-driven model, which uses a piecewise linear function based on quantified spatial associations between a set of evidential evidence features and ...
This paper proposes a novel knowledge-and-data-driven modeling (KDDM) approach for simulat- ing plant growth that consists of two submodels. One submodel is derived from all available domain knowledge, including all known relationships from physically based or mechanistic mod- els; the other is ...
In this paper, we described a data-driven sublanguage pattern mining method that can be used to create a knowledge model. We combined natural language processing (NLP) and semantic network analysis in our model generation pipeline. As a use case of our pipeline, we utilized data from an ...
Deep learning-based molecular generation has extensive applications in many fields, particularly drug discovery. However, the majority of current deep generative models are ligand-based and do not consider chemical knowledge in the molecular generation process, often resulting in a relatively low success...
Boundary-enhanced time series data imputation with long-term dependency diffusion models Chunjing Xiao, Xue Jiang, Xianghe Du, Wei Yang, ... Kevin ChettyIn Press, Journal Pre-proof, Available online 31 December 2024 Article preview select article LLM-based IR-system for bank supervisors Research ...
Such shells allow a user with domain-specific knowledge but minimal programming skills to build an expert system for a particular application quickly, by simply entering the necessary data and rules for manipulating such data. It appears that the current use of knowledge-based systems is mainly in...
Outlining the evolution of technologies and information models, Howell and Rezgui [1] position the DT to be fully reliant on the IFC models (in its OWL representation), ensuring semantic rich structured data, which would form the foundation for more efficient ontology based tools and agents. The...