Mathematical Modeling and Optimization of System Parameters of Feed Plant Using Machine Learning

Shakuntla Singla, Komalpreet Kaur

2023

Abstract

In this study, RPGT is applied for mathematical modelling system constraints of cattle, poultry, and fish feed plant and stand optimized by machine learning. The plant is made up of three grinder units (A1A2A3) that grind three distinct raw materials into precipitate depending on the type of feed that needs to be prepared, as well as a single cold standby (A) aimed at aimed at all these grinders, each of these grinders has a common standby grinder that is operated by an imperfect switch-over device whose probability of successful replacing is p, so that, if any one of the three grinders fails, the standby grinder can still input the ingredients into the system, a mixer (B) that combines the powder by syrup, using stuffing unit and a packing (D). Optimization of system parameters is carried out using Machine Learning Algorithms as Linear SVC Classifier (LC), Logistic Regression (LR), and Decision Tree Classifier (DT). Tables and charts are likewise created to explain the system’s practical trend using specific situations.

Paper Citation

in Harvard Style

Singla S. and Kaur K. (2023). Mathematical Modeling and Optimization of System Parameters of Feed Plant Using Machine Learning. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 158-162. DOI: 10.5220/0012608200003739

in Bibtex Style

@conference{ai4iot23,
author={Shakuntla Singla and Komalpreet Kaur},
title={Mathematical Modeling and Optimization of System Parameters of Feed Plant Using Machine Learning},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={158-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012608200003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Mathematical Modeling and Optimization of System Parameters of Feed Plant Using Machine Learning
SN - 978-989-758-661-3
AU - Singla S.
AU - Kaur K.
PY - 2023
SP - 158
EP - 162
DO - 10.5220/0012608200003739
PB - SciTePress