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115 results for “Potential Accuracy”
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Research ArticleOpen accessIn the keywordsTracking Algorithm for Estimating the Orientation Angles of the Object Based on the Signals of Satellite Radio Navigation SystemAlexandr PerovIn the article, the theory of optimal filtering of information processes is used to synthesize optimal one-stage estimation algorithm for the object orientation angles using the signals of the satellite navigation system. The article also provides equations of optimal filtering, as well as their representation in the form of the tracking system comprising of an orientation angles discriminator and a … …American Journal of Applied Sciences, Vol. 12, Issue 12 · 7 Dec 2015 · 6,474 accessesView PDFCite
Research ArticleOpen accessIn the abstractBenchmarking Lightweight Deep Learning Models for Field Based Sorghum Leaf Disease DetectionPrince Daughin Ngqabutho NcubeSorghum is a climate-resilient cereal crop central to food and livelihood security across Southern Africa, yet its productivity is frequently reduced by foliar diseases that smallholder farmers struggle to diagnose reliably in the field. While deep learning has demonstrated strong potential for automated plant disease identification, sorghum remains underrepresented in the literature, and no prior study has provided a comprehensive, … …Journal of Computer Science, Vol. 22, Issue 10 · 29 Sep 2026 · 535 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Analysis of Drug Reviews: Identifying Patient Conditions, Predicting Drug Ratings, and Sentiment AnalysisRafat Hammad, Mohammad Ashraf Ottom, Ayah Bani BakerUnderstanding patients' experiences with medications is essential for improving drug effectiveness, detecting potential side effects, and enhancing overall patient satisfaction. This research investigates applying machine learning to patient drug reviews across three main tasks: Identifying patient conditions, predicting drug ratings, and performing sentiment analysis. We implemented and evaluated Convolutional Neural Networks (CNNs), Artificial Neural Networks (ANNs), and Recurrent Neural Networks … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 736 accessesView PDFCite
Research ArticleOpen accessIn the abstractCoupling Analysis of Thermodynamic Equilibrium of Mass Transfer and Microbial Community Succession in Multiphase System of Dark Tea Solid-State FermentationZhanjun Liu, Jiawei Sun, Taotao Li et al.During the solid-state fermentation of dark tea, the limited material migration, the dynamic evolution of the thermodynamic equilibrium state, and the highly dynamic succession of the microbial community make it difficult to analyze the quality formation mechanism systematically. Traditional research has focused on microbial diversity or sensory quality analysis, lacking a systematic discussion on the regulatory effects of material migration … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,004 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Prediction Model for Information Anxiety of CSs Based on CMA-ES and XGBoostBin Wang, Li ShaoWith the rapid advancement of information technology, college students are increasingly facing the problem of information overload. Information anxiety, an emerging mental health issue, significantly impacts their studies, daily lives, and mental well-being. Given the limitations of existing methods in handling complex nonlinear relationships and high-dimensional data, this study proposes an efficient and accurate prediction model for college students’ information … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 1 · 21 Apr 2026 · 1,695 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of a Machine Learning Based Mobile and Web Crop Recommendation System for Precision Farming in WardhaAishwarya Kadu, KTV ReddyAgricultural productivity is crucial for economic growth of a nation, especially for countries like India which is highly dependent on agriculture. This study addresses the need for cutting-edge technology to enhance crop productivity by proposing a Mobile/Web-based precision farming system. Leveraging Machine Learning (ML) algorithms, the proposed system recommends optimal crops based on several factors such as environmental parameters (Nitrogen … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine-Tuned and Optimized Transformer-Based Model for EEG Seizure DetectionPuspanjali Mallik, Ajit Kumar Nayak, Kumar Janardan Patra et al.Epilepsy, a widely recognized neurological disorder, results from irregularities in the transmission of electrical impulses among neurons in the brain. Over the last two decades, significant efforts have been made by researchers and clinicians to develop effective methods for its early detection and management. The electroencephalogram (EEG), a non-invasive tool used to monitor brainwave activity, has become a central device … …Journal of Computer Science, Vol. 21, Issue 11 · 11 Feb 2026 · 1,412 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Neural Network Models for Predicting EUR/USD Direction: An Empirical StudyEl Badaoui Mohamed, Raouyane Brahim, El Moumen Samira, Bellafkih MostafaThis paper presents a rigorous comparative analysis of six feedforward neural network models for predicting the directional movement of the EUR/USD currency pair. The evaluated models include the Learning Vector Quantization, Cascade Neural Network, Feedforward Neural Network, Single Layer Perceptron, Multi-Layer Perceptron, and Radial Basis Function network. Utilizing daily historical data from April 2009 to May 2024, each model was … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Study on Factors Influencing MBA Decision After Bachelor’s Using Hybrid Model Combining ANN With Principal Component AnalysisKittipol Wisaeng, Benchalak MuangmeesriThis study comprehensively examines the complex relationship between various individual characteristics and individuals’ expectations after obtaining a bachelor’s degree, particularly in determining whether to pursue a Master of Business Administration (MBA). Utilizing a well structured, hypothesized framework, we examine several key variables directly influencing this critical decision-making process. The examined variables include, but are not limited to, demographic information, academic … …Journal of Computer Science, Vol. 21, Issue 9 · 13 Oct 2025 · 2,242 accessesView PDFCite