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77 articles for “AI-Based Forecasting”
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Research ArticleOpen accessIn the abstractDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 481 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 abstractDengue Fever Prediction Empowered by Radial Basis Function Networks, Dynamic Mode Decomposition, and Learning-Based Foraging AlgorithmArchana T, Faritha Banu JDengue fever is presently considered a major health threat that must be addressed. External and internal factors that induce nonlinear oscillations in the occurrence of dengue disease have made optimal resource allocation stimulating. Public health initiatives aimed at eradicating this vector use accurate and timely data through field processes. In dengue-endemic nations, early dengue prediction remains a main concern for … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 1,496 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDFCite
Research ArticleOpen accessIn the abstractSales Forecasting Models: Comparison between ARIMA, LSTM and ProphetDmitry BrykinSales forecasting is crucial for business planning and resource allocation. Data-driven approaches have become popular in this field. This study compares the performance of three forecasting models: Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Prophet within the context of specific sales categories derived from acquiring data provided by a bank. This study uses a time series dataset … …Journal of Computer Science, Vol. 20, Issue 10 · 1 Aug 2024 · 7,981 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Model of Corn Commodity Production in Indonesia: Production and Operation Management-Quantitative Method (POM-QM) SoftwareAsriani, Dhian Herdhiansyah, Wa Embe, LM Fid AksaraFood is essential for humans. In addition to being consumed, it can also be a valuable commodity for economic purposes through the production of food crops. Therefore, this study aims to model the forecasting of maize production in Indonesia using Production and Operations Management-Quantitative Method (POM-QM) software. The uniqueness of this research lies in its innovative approach to predicting corn … …Journal of Computer Science, Vol. 20, Issue 4 · 20 Feb 2024 · 6,150 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuel Prediction Model for Driving Patterns Using Machine Learning TechniquesManjunath TK, Ashok Kumar PSIn recent years, the demand for fuel efficiency has become a crucial aspect of the automotive industry. Predicting fuel economy accurately is essential for optimizing vehicle performance and reducing environmental impact. This proposed model presents a machine learning-based approach for developing a fuel prediction model using the real dataset. The model aims to predict fuel efficiency for different drivers by … …Journal of Computer Science, Vol. 20, Issue 3 · 29 Jan 2024 · 5,480 accessesView PDFCite
Research ArticleOpen accessIn the abstractFlood Forecasting in Malawi's Shire River BasinDaniel Nakapu Hussein, Mwakio Tole, Maarifa MwakumanyaThis study describes a study conducted in 2021-2022 in the Shire River Basin (SRB) of Chikwawa District, Malawi to evaluate how flood forecasting is currently performed and to provide recommendations for improvement. Flooding often occurs in the basin, endangering people's lives and property. A case in point is the 2015 flood and 2019 Tropical Cyclone Idai, which were so devastating … …American Journal of Environmental Sciences, Vol. 19, Issue 2 · 30 May 2023 · 7,004 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,772 accessesView PDFCite