Search Results - blended ((learning algorithm) OR (learning algorithms))
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Octane number prediction for gasoline blends using convolution neural network / Zhu Yue
Published 2021“…In the project three commonly use algorithm are used for prediction of octane number for gasoline blends, which describes the behavior of the fuel in the engine at lower temperatures and speeds, and is an attemp to simulate acceleration behavior.These tree algorithm are back propagation (BP), radial basis funtion (RBF) and Extreme learning machine (ELM) algorithm. …”
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Thesis -
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Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches
Published 2024“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
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Perceptions and practices of blended learning in foreign language teaching at USIM
Published 2024journal::journal article -
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Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives
Published 2025Subjects:Article -
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Kodepoly: an engaging approach to blended futuristic learning in coding
Published 2024“…This blended learning is designed to facilitate the tracking of learner progress, provide additional pedagogical challenges, and share hints and educational resources, thus catering to various learning styles and environments. …”
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Proceeding Paper -
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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LinguaBridge – academic digital scaffold
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Conference or Workshop Item -
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A Symbol Recognition System for Single-Line Diagrams Developed Using a Deep-Learning Approach
Published 2023“…Featured Application: The present study is among the first research efforts to generate augmented datasets of complex single-line diagrams to detect symbols using deep-learning-based algorithms. The work determines the impacts of augmented datasets on model performance and indicates future directions in the field of engineering drawings. …”
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Immersive AR pet game with hand motion
Published 2023“…ManoMotion is a hand-tracking software that uses machine learning algorithms to track and recognise hand movements in real-time. …”
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Final Year Project / Dissertation / Thesis -
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Loss minimization DTC electric motor drive system based on adaptive ANN strategy
Published 2020“…It is expected that with the proposed online learning Artificial Neural Network controller efficiency optimization algorithm can achieve better energy saving compared with traditional blended strategies…”
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Loss minimization DTC electric motor drive system based on adaptive ANN strategy
Published 2020“…It is expected that with the proposed online learning Artificial Neural Network controller efficiency optimization algorithm can achieve better energy saving compared with traditional blended strategies.…”
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Ultrasound-assisted process optimization and tribological characteristics of biodiesel from palm-sesame oil via response surface methodology and extreme learning machine - Cuckoo s...
Published 2020“…The purpose of this study was the improvement of cold flow and lubricity characteristics of biodiesel produced from the palm-sesame oil blend. Extreme learning machine (ELM) and response surface methodology (RSM) techniques were used to model the production process and the input variables (time, catalyst amount, methanol to oil ratio, and duty cycle) were optimized using cuckoo search algorithm. …”
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An improved hybrid learning approach for better anomaly detection
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Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education
Published 2025journal-article -
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Loss minimization DTC electric motor drive system based on adaptive ANN strategy
Published 2020“…It is expected that with the proposed online learning Artificial Neural Network controller efficiency optimization algorithm can achieve better energy saving compared with traditional blended strategies…”
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Particulate matter and nitrogen oxide emissions prediction using artificial neural network for diesel engine running on biodiesel-diesel fuel with nano-additive
Published 2023“…This work therefore uses artificial neural network (ANN) feed forward back propagation as learning algorithm to predict PM and NOx emissions using experimental data from test conducted on a single cylinder diesel engine running on palm oil biodiesel blended with conventional diesel and Iron (II) oxide (Fe2O3) nano-additive stabilized in isopropyl as surfactant at three engine loads (25%, 50%, 75%). …”
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Conference or Workshop Item
