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39 results for “Yield Prediction”
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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
Research ArticleOpen accessIn the abstractTree Volume Prediction Model of Cupressus lusitanica Species: in North-Western Highlands of EthiopiaYishak Adgo Kassie, Abebaw Alene YallewA significant basis of raw materials for the forest products industry is provided by Cupressus lusitanica, one of the commercial timber tree species found in the forest. Accurate tree and stand volume development models are necessary for intensive forest management to yield timber. The goal of this study was to develop and validate volume equations for Cupressus lusitanica tree species … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 26 Aug 2025 · 5,936 accessesView PDFCite
Research ArticleOpen accessIn the abstractSmart Weather Data Management System for Sustainable Agriculture in Maharashtra Using Machine LearningAishwarya V. Kadu, Kuraparthi Tirumala V. ReddyAgriculture will benefit greatly from efficient weather data sustainable management. Data can be utilized to schedule the prediction yield, crop growth, and irrigation. This paper collects real-time meteorological station data via APIs, primarily focusing on the weather data sustainable management system and data related to Maharashtra Wardha, India, which is involved in a live series period. Agriculture can make potential … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,507 accessesView PDFCite
Research ArticleOpen accessIn the abstractTransforming Saffron Cultivation With Smart Hydroponics: An Artificial Intelligence of Things Approach to Crops and Nutrients ManagementVivek Raj, Gregory Allen, Ananth Prabhu G., Melwin DsouzaAgriculture is changing with the aid of new technologies, particularly in several Asian countries. This research applies Artificial Intelligence (AI) and the Internet of Things (IoT) to traditional farming, particularly focusing on saffron cultivation using hydroponics. Hydroponics is especially useful as a city grows, because it not only saves space but also nourishes the plants directly through the roots - … …Journal of Computer Science, Vol. 22, Issue 7 · 28 Jul 2026 · 852 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 abstractComparative Analysis of Five Decomposition Techniques for Monthly Rainfall Time Series from 1991 to 2020 in Guinea (West Africa)Noukpo Médard Agbazo, Oumar Keita, Alpha Oumar Baldé et al.The selection of an optimal time series decomposition’ technique is crucial for enhancing rainfall prediction by using sophisticated methods as deep learning hybrid approaches. This study evaluates the effectiveness of five times series decomposition techniques in analyzing monthly rainfall datasets across Guinea geographical regions (Lower-Guinea (Boké, Conakry, Kindia), Middle-Guinea (Labé, Mamou), Upper-Guinea (Faranah, Kankan) and Forest-Guinea (Nzérékoré)) and identifies the … …American Journal of Applied Sciences, Vol. 22, Issue 1 · 27 Jan 2026 · 3,040 accessesView PDFCite
Review ArticleOpen accessIn the abstractComparative Analysis of Classical Feature Detection Methods for UAV-Based Tomato DetectionMuhammad Sarwar Jahan Morshed, Md. Nasim Adnan, Md. Rafiqul IslamRemote sensing technologies, especially Unmanned Aerial Vehicles (UAVs), become crucial for Precision Agriculture (PA) to perform different tasks such as crop detection, yield prediction, leaf disease diagnosis, weed detection, and harvest forecasting to ensure higher productivity. Therefore, using various image analytics methods feature detection from the UAV-captured images plays a vital role for conducting these PA tasks. To enhance the … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,404 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Disease Index Based on Multi-Spectra of UAV to Estimate Cotton DiseaseBing Chen, Jing Wang, Qiong Wang et al.Verticillium wilt is a significant disease that affects cotton plants, which can lead to stunted growth and reduced yield. To address this, a multi-spectral comprehensive monitoring disease index model is developed using an Unmanned Aerial Vehicle (UAV) to monitor the severity of cotton Verticillium wilt. First, multi-spectral dates were collected from Hexacopter (HY-6X) and the phenotype disease grade of cotton … …American Journal of Biochemistry and Biotechnology, Vol. 19, Issue 4 · 25 Mar 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of Artificial Neural Network Point Forecasting Models and Prediction Intervals for Solar Irradiance EstimationAntônio Fabrício Guimarães de Sousa, Helaine Cristina Moraes Furtado, Wilson Negrão Macêdo, Anderson Alvarenga de Moura MenesesAn accurate knowledge on solar irradiance prediction is particularly required for proper development and planning of Photovoltaic (PV) energy systems. The main purpose of the present research is to assess the accuracy of Artificial Neural Networks (ANN) short-term forecast of univariate solar irradiance time series, with conventional point prediction and Prediction Intervals (PIs), comparing models. The Lower Upper Bound Estimation … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 17 Jul 2020 · 7,440 accessesView PDFCite
Research ArticleOpen accessIn the abstractIn Silico Prediction and Functional Characterization of Genes Related to Abiotic and Biotic Stresses in Chickpea (Cicer arietinum)Sukhdeep Kaur, Satendra Singh, Gitanjali Tandon et al.Chickpea (Cicer arietinum L.) is second largest grown legumes worldwide contributing 75% of total pulse production. It is a cool season legume crop and grown in tropical and subtropical areas. Due to drastic climatic changes, chickpea suffers from many biotic (blight and wilt) and abiotic (salinity, drought, cold) stresses that directly impact the growth and yield. In our study, we … …Current Research in Bioinformatics, Vol. 7, Issue 1 · 25 Sep 2017 · 14,188 accessesView PDFCite