Cerek, KacperKacperCerekGupta, ArjunArjunGuptaDao, Duy AnhDuy AnhDaoHadjiloo, ElnazElnazHadjilooGrabe, JürgenJürgenGrabe2024-08-022024-08-022024-08-02https://hdl.handle.net/11420/48605This repository contains a Python script for processing and analysing sequential data using a Bidirectional Long Short-Term Memory (LSTM) model. The script is designed to perform various configurations, evaluate model performance, and save results for further analysis. It specifically targets parameter studies conducted on simulated CRS element tests. The script applies different configurations to train the model and evaluate its performance on test data, including varying data percentages, point skips, number of time steps, and batch sizes.enhttps://creativecommons.org/licenses/by/4.0/Bidirectional LSTMNeural NetworkSequential Data ProcessingPython ScriptArtificial IntelligenceNatural Sciences and Mathematics::550: Earth Sciences, GeologySource Code10.15480/882.1319010.15480/882.13190