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290 articles for “decision-making”
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Research ArticleOpen accessIn the abstractEvaluating Waste's Hazardousness using Fuzzy Logic and Simple Additive WeightingTimothy Marcelleon, Ditdit Nugeraha UtamaIt is vital to determine the most dangerous types of trash in terms of the environment and human health. The purpose of this selection is to make readers aware of the impact of garbage on the environment. As human knowledge of the environment grows, the utilization of garbage will naturally decrease. The goal of this research is to create a … …Journal of Computer Science, Vol. 19, Issue 1 · 19 Jan 2023 · 5,604 accessesView PDFCite
Research NotesOpen accessIn the abstractMetadata Stewardship and Quality in Telecom SectorBhola Gan Chaudhuri, Shalli RaniThe spread of the telecom network infrastructure, constellations of satellites and the use of the Internet of Things (IoT) have brought about unprecedented volumes of heterogeneous information which facilitate the contemporary monitoring systems of the environment and the earth. Metadata control and information quality have also become significant in the telecom industry in controlling data reliably, enhancing data services, and … …Journal of Computer Science, Vol. 22, Issue 10 · 22 Oct 2026 · 335 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Efficient Cluster Head Selection in IoV-Enabled VANETs Using a Federated Diffusion Convolutional Recurrent Neural Networks FrameworkP Subhash, Madana Srinivas, A. Ranjith et al.The IoV enables the formation of VANETs that require a strong selection of CHs for effective communication within high-velocity changing traffic scenarios. Existing approaches often face issues related to scalability, privacy, and adaptability. To meet the aforementioned urgent needs, we design a decentralized scheme for intelligent CH selection based on Federated Learning with Diffusion Convolutional Recurrent Neural Networks (DCRNNs). According … …Journal of Computer Science, Vol. 22, Issue 10 · 1 Oct 2026 · 599 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessIn the abstractAbstractive Summarization of Long Educational Transcripts in the Era of GenAIDeepa Fernandes, Rupali Sunil WaghThe surge in online video data presents the imperative requirement of summarizing it for information compression, efficient understanding, and to support decision-making. Recent research studies have predominantly utilized structured input data for summarization. This paper explores the current state-of-the-art models in summarizing unstructured, conversational, and long transcript data. We further apply a transfer learning approach using a fine-tuned BART model, … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 403 accessesView PDFCite
Research ArticleOpen accessIn the abstractFL-CARE: Federated Learning-Based Contention-Aware and Energy-Balanced Routing for Dense FANETsHalimjon Khujamatov, Elyanora Jolimbetova et al.In dense multi-drone FANET environments, routing efficiency is often reduced due to constant competition for a wireless channel, frequent changes in network topology, and uneven energy consumption between UAV nodes. These factors lead to a decrease in the packet delivery ratio, an increase in delays on the busiest or most unstable routes, and a reduction in the total network lifespan. … …Journal of Computer Science, Vol. 22, Issue 8 · 13 Aug 2026 · 1,172 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Areas Susceptible to Gullies in Ideato South Local Government Area of Nigeria Using Geographic Information System and Remote Sensing TechnologySylvanus IroGully erosion is a critical environmental hazard in Southeastern Nigeria, threatening agricultural productivity, infrastructure, and communal safety. This study provides a spatially explicit assessment of gully erosion susceptibility in Ideato South Local Government Area (LGA), Imo State, using an integrated Geographic Information System (GIS) and Remote Sensing framework. The methodology employed a multi-criteria decision-making approach, utilizing the Analytical Hierarchy Process … …American Journal of Environmental Sciences, Vol. 22, Issue 1 · 20 Jul 2026 · 1,189 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Soft Voting Ensemble of XGBoost and DNN for At-Risk Student Performance PredictionEugene Wan, Po Chan Chiu, Mohammad bin Hossin et al.Early identification of at-risk students in higher education is important for timely academic intervention, yet conventional prediction methods often struggle with data imbalance and limited model precision. This study proposes a hybrid soft voting ensemble model that integrates Extreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN) to enhance multi-class student grade prediction (A-F classification) and at-risk student identification. This … …Journal of Computer Science, Vol. 22, Issue 5 · 28 May 2026 · 1,390 accessesView PDFCite