On 21 November, at the 15th International Scientific Conference “EcoTech”, lead researcher Ph.D. Oskars Java delivered a presentation titled “Feeding Simulation Model: Data Acquisition to Achieve Climate Neutrality Goals.”
The presentation is an important part of the State Research Programme project “Climate Neutrality Decision Models in Action”, which focuses on the development of simulation models and the availability of the information necessary for their operation. Within the scope of the research, a prototype for data storage and exchange is being developed to enable efficient data collection and structuring for use in model operation.
In his talk, Oskars Java highlighted the data acquisition process, which is often one of the most complex stages in modelling projects. The project team has encountered a number of challenges — ranging from data diversity and fluctuations in data quality to technical obstacles in collecting data across different sectors.
Particular attention from the audience was drawn to the section of the presentation dedicated to anomaly detection and missing data generation using machine learning methods. These solutions are essential to ensure accurate and reliable model performance, especially in situations where the available data is incomplete or inconsistent.
