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9 results for “Flood Prediction”
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Research ArticleOpen accessPhrase in the titleComparative Performance of Supervised Learning Algorithms for Flood Prediction in Kemaman, TerengganuNur Najihah Shaaban, Norlida Hassan, Aida Mustapha, Salama A. MostafaFlood is one of the most destructive phenomena all over the world. Because the flooding uncertainties and the urgency to prepare for disaster management, three specific technique approaches are compared in this study to predict the flood occurrence based on historical rainfall data. The study involved the rainfall data in Kemaman, Terengganu between 2017 and 2018 extracted from the official … …Journal of Computer Science, Vol. 17, Issue 5 · 7 May 2021 · 6,887 accessesView PDFCite
InvestigationOpen accessPhrase in the titleBackpropagation Vs. Radial Basis Function Neural Model: Rainfall Intensity Classification For Flood Prediction Using Meteorology DataSoo See Chai, Wei Keat Wong, Kok Luong GohRainfall is one of the important weather variables that vary in space and time. High mean daily rainfall (>30 mm) has a high possibility of resulting in flood. Accurate prediction of this variable would save human lives and properties. Soft computing methods have been widely applied in this field. Among the various soft computing methods, Artificial Neural Network (ANN) is … …Journal of Computer Science, Vol. 12, Issue 4 · 15 Apr 2016 · 8,705 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEfficient Rainfall Forecasting Using Sequential Momentum-Based Artificial Neural Networks for Urban Flood ManagementSherin K K, G. SuganthiUrban floods cause severe disruption in densely populated cities and damage essential public infrastructure. Rapid urbanization and weak drainage systems further increase the risk during heavy rainfall. Accurate short-term rainfall forecasting is required to support early warning and reduce losses. This research focuses on improving rainfall prediction accuracy using an Artificial Neural Network trained with a new optimizer named Sequential … …Journal of Computer Science, Vol. 22, Issue 4 · 9 Apr 2026 · 1,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutoencoder-Based Intrusion Detection for ARP Poisoning in SDN ControllersKago Seemela, Banyatsang Mphago, Thabo Semong, Phephisa MethulaAddress Resolution Protocol (ARP) poisoning is still a critical control plane attack in Software Defined Networks (SDNs), and spoofing of ARP mappings can trick SDNs controller and accomplish man in the middle, eavesdropping and denial of service attacks. Current SDN intrusion detection systems of ARP attacks rely on supervised learning and labelled attack data which is rather expensive and not … …Journal of Computer Science, Vol. 22, Issue 7 · 21 Jul 2026 · 869 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystematic Literature Review of Graph Neural Networks in Disaster Management: Methods, Applications, and Future DirectionsSularno, Wendi Boy, Putri Anggraini et al.The increasing frequency and complexity of natural disasters underscore the urgent need for intelligent systems that support timely and effective decision-making. Graph Neural Networks (GNNs) have emerged as a powerful deep-learning paradigm for modeling spatial and relational data, offering distinct advantages for disaster management. This study presents a Systematic Literature Review (SLR) of GNN-based approaches for disaster mitigation, emergency response, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,036 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Routing Discovery Based Velocity-Aware Probabilistic Using AODV with Link Prediction in Mobile Ad-hoc NetworksZaid BassfarThe current process associated with enhancing the QoS in routing for MANETs has reserved a high importance due to the limitation of available route discovery in dynamic topology. The conventional methods of route discovery schemes in MANETs are commonly designed in order to estimate the number of nodes in routes using the standard probabilistic models. Such models are utilized by … …American Journal of Applied Sciences, Vol. 14, Issue 8 · 1 Aug 2017 · 7,655 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Review of Flood Risk Analysis in NigeriaAkinola Adesuji Komolafe, Suleiman Abdul-Azeez Adegboyega, Francis Omowonuola AkinluyiNigeria has witnessed diverse flood events in the past years and due to the high level of vulnerability and lack of coping capacity of the people, with the fast occurrence of extreme events resulting from climate change, many lives and properties are at risk of its impacts. This paper reviews the recent past and present efforts in assessing the flood … …American Journal of Environmental Sciences, Vol. 11, Issue 3 · 12 Sep 2015 · 10,800 accessesView PDFCite
Research ArticleOpen accessIn the abstractNeural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun RiverSiti Hajar Arbain, Antoni WibowoThe Department of Irrigation and Drainage (DID) Malaysia and Meteorological Malaysia Department (MMD) has been measured the flood characteristics benchmark which included water level, area inundation, peak inundation, peak discharge, volume of flow and duration of flooding. In terms of water levels, DID have introduced three categories of critical level stages namely normal, alert and danger levels. One of the … …Journal of Computer Science, Vol. 8, Issue 9 · 13 Aug 2012 · 7,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdjustment of Peak Streamflows of a Tropical River for UrbanizationAta Amini, Thamer Mohammad Ali, Abdul Halim B Ghazali, Bujang Kim HuatPeak runoff from a catchment is influenced by many factors such as intensity and duration of rainfall, catchment topography, catchment shape, land use and other variables. For a particular catchment, landuse change and other human activities will alter the characteristic of catchment hydrograph. Problem statement: As a result of urbanization, the magnitude of floods occurring in a catchment increased. It … …American Journal of Environmental Sciences, Vol. 5, Issue 3 · 30 Jun 2009 · 7,546 accessesView PDFCite