Business analytics is an extensive use of data acquired from diverse sources, statistical and quantitative analysis, explainable and predictive models, and fact-based management to make better strategic decisions for different stakeholders. To be able to model complex systems holistically in such a way that they can be fed into an efficient simulation-based optimization in the sense of prescriptive analytics, approaches and solutions that go beyond state-of-the-art are required. This paper introduces the basic technologies used in prescriptive analytics and proposes secure prescriptive analytics (SPA) that is based on component-based hierarchical modeling and dynamic optimization. Each element under the SPA framework is defined and illustrated by an example of production plan optimization.
%0 Conference Paper
%1 10130953
%A Affenzeller, Michael
%A Bögl, Michael
%A Fischer, Lukas
%A Sobieczky, Florian
%A Yang, Kaifeng
%A Zenisek, Jan
%B 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
%D 2022
%K cooperative deep-learning interact models simulation
%P 1-8
%R 10.1109/SYNASC57785.2022.00009
%T Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way
%U https://ieeexplore.ieee.org/document/10130953
%X Business analytics is an extensive use of data acquired from diverse sources, statistical and quantitative analysis, explainable and predictive models, and fact-based management to make better strategic decisions for different stakeholders. To be able to model complex systems holistically in such a way that they can be fed into an efficient simulation-based optimization in the sense of prescriptive analytics, approaches and solutions that go beyond state-of-the-art are required. This paper introduces the basic technologies used in prescriptive analytics and proposes secure prescriptive analytics (SPA) that is based on component-based hierarchical modeling and dynamic optimization. Each element under the SPA framework is defined and illustrated by an example of production plan optimization.
@inproceedings{10130953,
abstract = {Business analytics is an extensive use of data acquired from diverse sources, statistical and quantitative analysis, explainable and predictive models, and fact-based management to make better strategic decisions for different stakeholders. To be able to model complex systems holistically in such a way that they can be fed into an efficient simulation-based optimization in the sense of prescriptive analytics, approaches and solutions that go beyond state-of-the-art are required. This paper introduces the basic technologies used in prescriptive analytics and proposes secure prescriptive analytics (SPA) that is based on component-based hierarchical modeling and dynamic optimization. Each element under the SPA framework is defined and illustrated by an example of production plan optimization.},
added-at = {2023-08-04T09:52:14.000+0200},
author = {Affenzeller, Michael and Bögl, Michael and Fischer, Lukas and Sobieczky, Florian and Yang, Kaifeng and Zenisek, Jan},
biburl = {https://www.bibsonomy.org/bibtex/2276d530eda60f42f63a29c8f1b44b167/scch},
booktitle = {2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)},
doi = {10.1109/SYNASC57785.2022.00009},
interhash = {630dd0c3259e5231170dc9eb90d522a8},
intrahash = {276d530eda60f42f63a29c8f1b44b167},
issn = {2470-881X},
keywords = {cooperative deep-learning interact models simulation},
month = {Sep.},
pages = {1-8},
timestamp = {2023-08-04T09:52:14.000+0200},
title = {Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way},
url = {https://ieeexplore.ieee.org/document/10130953},
year = 2022
}