Set-Based Differential Evolution Algorithm Based on Guided Local Exploration for Automated Process Discovery
Evolutionary algorithm is an effective way to solve process discovery problem which aims to mine process models from event logs which are consistent with the real business processes. However, current evolutionary algorithms, such as GeneticMiner, ETM, and ProDiGen, converge slowly and in difficultly...
Saved in:
| Main Author: | Si-Yuan Jing |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/4240584 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Toward Automated Knowledge Discovery in Case-Based Reasoning
by: Sherri Weitl-Harms, et al.
Published: (2024-05-01) -
An intelligent comprehensive scoring approach based on improved differential evolution algorithm
by: WANG Rongsheng, et al.
Published: (2025-03-01) -
An intelligent comprehensive scoring approach based on improved differential evolution algorithm
by: WANG Rongsheng, et al.
Published: (2025-03-01) -
An adaptive differential evolution algorithm based on adaptive evolution strategy and diversity enhancement
by: Shengke Lin, et al.
Published: (2025-09-01) -
A robust audio steganography algorithm based on differential evolution
by: Zhaopin SU, et al.
Published: (2021-11-01)