Riyadi, Ahmad and Rokhman, Nur and Heryawan, Lukman (2025) A review on long short-term memory combination development. IAES International Journal of Artificial Intelligence, 14 (6). 4427 - 4441. ISSN 20894872
A REVIEW....pdf - Published Version
Restricted to Registered users only
Download (968kB) | Request a copy
Abstract
Long short-term memory (LSTM) has continued to develop since it was proposed in 1997. LSTM has optimized solutions to various problems. The LSTM cell, architecture, and memory model have been reviewed. A review of LSTM implementation has been carried out in various problem domains. There are combinations of LSTM with other methods to optimize solutions. However, there is no review on the development of LSTM combination (LC). This research reviews the development of the LC model on nine research questions, namely: development framework, data, preprocessing, learning process, tasks, optimization and evaluation, domain problems, trends, and challenges. The results show that the LC model is increasingly widespread in solving problems. The LC model has completed 26 types of tasks. Prediction, detection, forecasting, classification, and recognition are the most frequently performed tasks. LC model development trends show that LSTM is increasingly collaborative with other methods on a wider scope. The challenges identified include research areas, data, model developments, the area of implementation, performance, and efficiency.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Combination; Deep learning; Long short-term memory; Optimization; Systematic literature review |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Mathematics and Natural Sciences > Computer Science & Electronics Department |
| Depositing User: | Wiyarsih Wiyarsih |
| Date Deposited: | 19 Jun 2026 06:27 |
| Last Modified: | 19 Jun 2026 06:27 |
| URI: | https://ir.lib.ugm.ac.id/id/eprint/27595 |
