Energy Efficiency Data Mining and Scheduling Optimization of Discrete Workshop

Authors

Yugu Lin, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;
Wang Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: This paper addresses the optimization of energy consumption in discrete workshops and establishes the energy efficiency optimization model of discrete workshops. The relationship between data mining and knowledge discovery is established. Through scheduling data preprocessing and C4.5 decision tree learning algorithm, the discovery of scheduling knowledge is realized. Energy efficiency optimization calculation is achieved in discrete workshops by the combination of scheduling knowledge and improved differential evolution algorithm (IDE). By comparing with TLBO, GA and PSO, the feasibility of IDE algorithm is verified.

Recommended Citation

Lin, Yugu and Yan, Wang (2019) "Energy Efficiency Data Mining and Scheduling Optimization of Discrete Workshop," Journal of System Simulation: Vol. 31: Iss. 12, Article 18.
DOI: 10.16182/j.issn1004731x.joss.19-FZ0257
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss12/18

First Page

2702

Revised Date

2019-06-26

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-FZ0257

Last Page

2711

CLC

TP391.9

Recommended Citation

Lin Yugu, Wang Yan. Energy Efficiency Data Mining and Scheduling Optimization of Discrete Workshop[J]. Journal of System Simulation, 2019, 31(12): 2702-2711.

DOI

10.16182/j.issn1004731x.joss.19-FZ0257