Asian Journal of Mathematics and Computer Research https://ikprress.org/index.php/AJOMCOR <p><strong>Asian Journal of Mathematics and Computer Research [ISSN: 2395-4205 (Print), 2395-4213 (Online)]</strong> aims to publish high-quality papers in all disciplines of Mathematics and Computer Science. This journal considers following <a href="https://ikprress.org/index.php/AJOMCOR/about/submissions">types of papers</a> (<a href="https://ikprress.org/index.php/AJOMCOR/about/submissions">Link</a>). </p> <p>The journal also encourages the submission of useful reports of negative results. This is a peer-reviewed, open access INTERNATIONAL journal. This journal follows OPEN access policy. All published articles can be freely downloaded from the journal website.</p> en-US submission@ikpress.org (International Knowledge Press) submission@ikpress.org (International Knowledge Press) Sat, 21 Sep 2024 12:55:26 +0000 OJS 3.3.0.11 http://blogs.law.harvard.edu/tech/rss 60 About Supports of Local Cohomology Modules https://ikprress.org/index.php/AJOMCOR/article/view/8864 <p>The article provides the relation between the theory of local cohomology modules, and vanishing results, and also about the theory of support of such modules. Here, we put results about the theory, and also we provide a relation of local cohomology in the theory of commutative algebra and homological algebra.</p> Carlos Henrique Tognon Copyright (c) 2024 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://ikprress.org/index.php/AJOMCOR/article/view/8864 Sat, 21 Sep 2024 00:00:00 +0000 Multi Time Series WA-LSTM-Adam for Water Level Forecasting in Center Vietnam https://ikprress.org/index.php/AJOMCOR/article/view/8891 <p>The central region of Vietnam suffers from oods almost every year as a result of a combination of frequent storms, heavy rainfall, and short, steep rivers in the region. This is a big problem because they can negatively affect the economy of the region as well as people's lives when not managed properly. Therefore, it is important to have a reliable forecasting method for ooding in order to ensure effective natural disaster management. In this research, we aim at addressing this issue by introducing a multi time series hybrid deep learning model that combines WA (wavelet analysis) and LSTM (long-short-term memory) optimized with the Adam algorithm and uses water level and rainfall data as the input variables. Compared to other traditional methods and some recent models, our WA-LSTM-Adam method shows better results overall.</p> Nguyen Duc Khoa, Nguyen Quang Dat, Vo Quang Linh, Nguyen Ha Vy, Vu Hoang Nam Khanh, Phan Viet Hoang Copyright (c) 2024 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. https://ikprress.org/index.php/AJOMCOR/article/view/8891 Thu, 10 Oct 2024 00:00:00 +0000