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24 results for “Hybrid Machine Learning Models”
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Research ArticleOpen accessAll words, across the recordHybrid Deep Learning Models for Text Classification: Performance Evaluation of TriDistilBERT and BiGRU ArchitecturesAmira Samy TalaatText can be a valuable source of information, but its unstructured nature makes analysis challenging and time-consuming. Machine Learning (ML) algorithms can efficiently analyze and structure text, enabling organizations to automate processes and uncover insights that support better decision-making. This study focuses on applying ML to a classification problem using two datasets. Four deep learning models are introduced, combining Bi … …Journal of Computer Science, Vol. 21, Issue 9 · 10 Oct 2025 · 2,792 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdvanced Facial Emotion Recognition Using DCNN-ELM: A Comprehensive Approach to Preprocessing, Feature Extraction and Performance EvaluationBoopalan K., Satyajee Srivastava, K. Kavitha et al.As a subfield of affective computing, Facial Emotion Recognition (FER) teaches computers to read people's facial expressions to determine their emotional state. Because facial expressions convey 55% of an individual's emotional and mental state in the whole range of face-to-face communication, Facial Emotion Recognition is crucial for connecting humans and computers. Improvements in the way computer systems (robotic systems) interact … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,899 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordFeasibility of Hybrid Neuro-Fuzzy (ANFIS) Machine Learning Model with Classical Multi-Linear Regression (MLR) For the Simulation of Solar Radiation: A Case Study Abuja, NigeriaNajashi B. Gafai, Asia'u Talatu BelgoreThe extremely variable nature of solar radiation makes it difficult for solar power plants to keep up with predicted power output and demand curves. As a result, solar radiation simulation is crucial to the efficient design, administration, and operation of any solar power plant. With only partially satisfactory results, empirical models have been routinely employed in Nigeria to predict solar … …Energy Research Journal, Vol. 13, Issue 1 · 21 Jul 2022 · 10,032 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordParticle Swarm and Neural Network Approach for Fault Clearing of Multilevel InvertersR. M.S. Parvathi, M. SivakumarThis study presents a machine learning technique for fault diagnostics in induction motor drives. A normal model and an extensive range of faulted models for the inverter-motor combination were developed and implemented using a generic commercial simulation tool to generate voltages and current signals at a broad range of operating points selected by a Particle Swarm Optimization (PSO) based machine … …American Journal of Applied Sciences, Vol. 10, Issue 6 · 8 Jun 2013 · 6,486 accessesView PDFCite