Quanta Research https://journals.tultech.eu/index.php/qr <p><strong><em>Quanta Research</em> (QR)</strong> is an open-access and free-of-charge journal aimed at creating a holistic view in integrated human-based disciplines such as social science, political science, psychological science, managerial science, environmental strategical science, and energy strategies with computational algorithms and numerical modeling. Basically, QR is a framework for the implementation of novel viewpoints in the computational human-based research area. In essence, QR serves as a framework for the application of novel perspectives in the field of computational human-based research. The Journal offers a framework for intelligent, long-lasting, operational changes in communities based on computational algorithms.</p> en-US Mohammad.Gheibi@tultech.eu (Mohammad Gheibi) qr.tultech@gmail.com (Administrator ) Sat, 30 Sep 2023 00:00:00 +0200 OJS http://blogs.law.harvard.edu/tech/rss 60 A Social-Based Decision Support System for Flood Damage Risk Reduction in European Smart Cities https://journals.tultech.eu/index.php/qr/article/view/141 <p>Today, Decision Support Systems (DSS), which include monitoring, prediction, and control sections, are assumed to be tools for smart, sustainable management of disasters such as floods. On the platforms, first, a process is designed for receiving valid data before, during, and after a flood. Then, with the application of artificial intelligence (AI) models, the essential features can be predicted. Meanwhile, the main predicted factors should be determined according to the goals of each research project. In the present study, two-stage machine learning models will be used, including damage values in cities and rural regions and social impacts. In the first step, damages will be estimated by machine learning computations based on rainfall (mm), hourly flow of the river (m3/s), type of vegetation, density, etc. In a parallel way, after the determination of structural equation modeling (SEM) of social parameters in flood and their weights, in the second step of AI modeling, the social feedback factor will be forecasted based on effective achieved features. Finally, with the application of controlling systems such as the Decision Tree (DT) model, a fast reaction system is designed.</p> Mohammad Gheibi, Reza Moezzi Copyright (c) 2023 Quanta Research https://creativecommons.org/licenses/by/4.0 https://journals.tultech.eu/index.php/qr/article/view/141 Thu, 05 Oct 2023 00:00:00 +0200