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19 results for “infrastructure planning”
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Research ArticleOpen accessIn the keywordsA Hidden Genetic Layer Based Neural Network for Mobility PredictionL. Velmurugan, P. ThangarajProblem statement: With numerous wireless devices increasingly connecting to the internet, WLAN infrastructure planning becomes very important to maintain desired quality of services. For maintaining desired quality of service it is desirable to know the movement pattern of users. Mobility prediction involves finding the mobile device's next access point as it moves through the wireless network. Hidden Markov models and … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 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 abstractRandom Forest and Extreme Gradient Boosting with Bayesian Hyperparameter Optimization for Landslide Susceptibility Mapping in Penang Island, MalaysiaDorothy Anak Martin Atok, Soo See Chai, Kok Luong Goh et al.Landslide susceptibility models often face challenges of overfitting and overestimation. This research focuses on improving the predictive capabilities of the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms by applying Bayesian Hyperparameter Optimization (BayesOpt). Penang Island, a region in Malaysia prone to frequent landslides, was chosen as the study area. Ten Landslide Conditioning Factors (LCFs), including elevation, slope angle, … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 3,103 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Earthquake Evacuation Routes Using Dijkstra's Algorithm and WinQSBSandra Huarcaya Gonzales, Hugo Vega-Huerta, Gisella Luisa Elena Maquen-Niño et al.This research analyzes and generates optimal evacuation routes in the Barranco district during earthquake scenarios using the Dijkstra algorithm implemented through WinQSB. A preliminary review was conducted to establish key concepts related to earthquake dynamics, evacuation route planning, and the application of Dijkstra’s algorithm. Given its high seismic exposure and the prevalence of aging infrastructure, Barranco is considered highly vulnerable … …Journal of Computer Science, Vol. 21, Issue 10 · 9 Dec 2025 · 2,851 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Disaster Resilience through Spatial Planning Strategies, a Case Study of Bono Region, GhanaAmponsah Maxwell, Nandi Nandi, Maryani EnokThe adverse impact of climate change has necessitated the global community to leverage spatial planning to curb the negative impacts of such incidents. Disasters continue to occur in human settlements, which makes it necessary to develop resilience through spatial planning strategies. The research question underpinning this study is, how can disaster resilience be improved through spatial planning strategies? Reducing the … …Journal of Social Sciences, Vol. 20, Issue 1 · 30 Dec 2024 · 5,008 accessesView PDFCite
Research ArticleOpen accessIn the abstractLandslide Susceptibility Mapping with GIS in Nagi Dada Area of Panauti Municipality, Kavrepalanchwok District: A Comparison Between AHP and FR MethodArju Bhattarai, HimLal Shrestha, Asim Timalsina et al.Landslide Susceptibility Maps (LSM) are useful for both development planning and disaster management. Currently, LSMs are primarily created using GIS and remote sensing techniques. Landslide susceptibility mapping relies heavily on selecting and weighting causative elements based on their impact on slope instability. GIS is useful for calculating static parameters such as slope and aspect, as well as generating landslide susceptibility … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 4 · 22 Aug 2024 · 7,093 accessesView PDFCite
EditorialOpen accessIn the abstractVolume 2: and SGAMR Goes!Chiara Bedon, Mario D’Aniello, Flavio StochinoThe year 2018 starts with a great confirmation for SGAMR! The journal has been selected to host the extended version of some selected papers presented during the 6th International Workshop on Design in Civil and Environmental Engineering (DCEE2017), held at the University of Cagliari (Italy) during November 2017. A summary of selected papers from highly ranked, international scientists can be … …International Journal of Structural Glass and Advanced Materials Research, Vol. 4, Issue 1 · 28 Aug 2020 · 5,737 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Air Passenger Demand: A Comparison of LSTM and SARIMAQuang Hung Do, Shih-Kuei Lo, Jeng-Fung Chen et al.All airports need to have an accurate prediction of the number of passengers for their efficient management. An accurate prediction of the number of air passengers is crucial task since it provides information for planning decisions in the airport infrastructure to stabilize the service and maximize the profit. This study proposes a novel air passenger demand forecasting model based on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 8,555 accessesView PDFCite