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Authors: Janis Peksa and Janis Grabis

Affiliation: Institute of Information Technology, Faculty of Computer Science and Information Technology, Riga Technical University, Kalku street 1, LV-1658, Riga, Latvia

Keyword(s): ERP Systems, Prediction Framework, AODPF.

Abstract: Enterprise resource planning (ERP) systems are large modular enterprise applications that are designed to execute the majority of enterprise business processes with a focus on transaction processing. Business processes, on the other hand, frequently necessitate complex decision-making. If data processing logic requires complex analytical calculations and domain specific knowledge, is is considered as complex. To externalize the analytical calculations and decouple them from the core ERP system, this paper elaborates an integration framework fererred as to Autonomous Open Data Prediction Framework (AODPF). The AODPF provides advanced prediction capabilities to ERP systems. It uses data integration and processing as well as best model selection functions to generate predictions passed to the ERP system for decision-making purposes. The framework is experimentally evaluated by prediction road conditions for the case of winter road maintenance. The utility of the framework is evaluated i n the expert survey. (More)

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Paper citation in several formats:
Peksa, J. and Grabis, J. (2022). Integration of the Autonomous Open Data Prediction Framework in ERP Systems. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 251-258. DOI: 10.5220/0011081300003179

@conference{iceis22,
author={Janis Peksa. and Janis Grabis.},
title={Integration of the Autonomous Open Data Prediction Framework in ERP Systems},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2022},
pages={251-258},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011081300003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Integration of the Autonomous Open Data Prediction Framework in ERP Systems
SN - 978-989-758-569-2
IS - 2184-4992
AU - Peksa, J.
AU - Grabis, J.
PY - 2022
SP - 251
EP - 258
DO - 10.5220/0011081300003179
PB - SciTePress

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