التفاصيل البيبلوغرافية
| العنوان: |
Evolving LSTM Networks for Time-Series Classification in EdgeIoT |
| المؤلفون: |
Pei Cui, San Li, Kaina Jiang, Zhendong Liu, Xingkai Sun |
| بيانات النشر: |
Mathematical Problems in Engineering |
| سنة النشر: |
2023 |
| المجموعة: |
Hindawi Publishing Corporation |
| الوصف: |
We proposed a novel approach to evolve LSTM networks utilizing intelligent optimization algorithms and address time-series classification problems in EdgeIoT. Meanwhile, a new optimizer called cultural society and civilization (CSC) algorithm is proposed to reduce the probability of stagnated in the local optima and increase the convergence speed. The suggested method could relieve the problem that the traditional data mining and pattern extraction methods cannot guarantee high accuracy and are hard to deploy on terminal devices. The proposed CSC algorithm and CSC-optimized LSTM model is examined on benchmark problems and demonstrates remarkable superiority over traditional methods and can be applied to support EdgeIoT for learning and processing. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| Relation: |
https://doi.org/10.1155/2023/6469030 |
| DOI: |
10.1155/2023/6469030 |
| الاتاحة: |
https://doi.org/10.1155/2023/6469030 |
| Rights: |
Copyright © 2023 Pei Cui et al. |
| رقم الانضمام: |
edsbas.A6D7B600 |
| قاعدة البيانات: |
BASE |