Search Results - (( based regulated learning algorithm ) OR ( java application stemming algorithm ))
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Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…In this work, the optimal base pressure is determined using the PCA-BAS-ENN-based algorithm to modify the base pressure presetting accuracy, thereby regulating the base drag required for the smooth flow of aerodynamic vehicles. …”
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Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants
Published 2023“…The research elaborates on the design and implementation of machine learning models based on three algorithms: Decision Tree, Gradient Boosted Tree, and Support Vector Machine. …”
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Novel direct and self-regulating approaches to determine optimum growing multi-experts network structure
Published 2004“…However, GMN is not ergonomic due to too many network control parameters. Therefore, a self-regulating GMN (SGMN) algorithm is proposed. SGMN adopts self-adaptive learning rates for gradient-descent learning rules. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Conference or Workshop Item -
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A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications
Published 2025“…To address this challenge, the paper proposed XGB5hmC, a machine learning algorithm based on a robust gradient boosting algorithm (XGBoost), with different residue based formulation methods to identify 5hmC samples. …”
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Nonlinear dynamic system identification and control via self-regulating modular neural network
Published 2003“…In addition, the Fully Self-Organized Simplified Adaptive Resonance Theory (FOSART) is modified and adopted to generate an induced Delaunay triangulation that is highly desired for optimal function approximation. Self-adaptive learning rates Gradient Descent learning rules are employed in a supervised learning phase. …”
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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin
Published 2023“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Base pressure control through micro jets at supersonic Mach numbers using experimental and machine learning approach
Published 2026“…Furthermore, machine learning (ML) algorithms were utilized to predict base pressure outcomes and optimize control strategies. …”
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Performance comparison of feedforward neural network training algorithms in modeling for synthesis of polycaprolactone via biopolymerization
Published 2018“…This paper compares mean absolute error, mean square error, and mean absolute percentage error (MAPE) in the PCL biopolymerization process for 11 different training algorithms that belong to six classes, namely (1) additive momentum, (2) self-adaptive learning rate, (3) resilient backpropagation, (4) conjugate gradient backpropagation, (5) quasi-Newton, and (6) Bayesian regulation propagation. …”
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Deep learning framework for hierarchical-based object identification and description
Published 2024“…Hence, DL approaches lack of global generalization, hierarchical learning, and correlation learning. In addition, DL-based CV approaches only depend on extracting high-level features which are not semantic to recognize parts or subsets of an object. …”
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Understanding the sentiment on gig economy: good or bad?
Published 2022“…Then, the comments were further classified into three machine learning algorithms: Support Vector Machine, Light Gradient Boosted Machine, and Logistic Regression. …”
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Enhancing Aquilaria species classification using agarwood oil analysis and k-Nearest Neighbors (KNN) as machine learning / Amir Hussairi Zaidi ... [et al.]
Published 2024“…This study employs machine learning, specifically the k-Nearest Neighbors (kNN) algorithm, to classify Aquilaria species based on chemical compounds features extracted from agarwood oil. …”
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Depression Detection in Tweets from Urban Cities of Malaysia using Deep Learning
Published 2021“…Therefore, the research entails on how the problem statement of this project on developing an algorithm that can predict text- based depression symptoms using deep learning and Natural Language Processing (NLP) can be achieved. …”
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Conference or Workshop Item -
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An acquisition and a modulated recognition system for driver profiling in Malaysia / Ward Ahmed Alaulddin Al-Hussein
Published 2022“…Following that, three deep-learning-based algorithms, namely, Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), were modulated to classify the recorded driving data according to the established profiles. …”
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Application of Artificial Intelligence In Smart City
Published 2021“…Proposals on AI application trends in the Economic dimension are regulated Unmanned Aerial Vehicle (UAV) application, create open resources of data sources, algorithms, and sources of economic AI machines, and assist in financial analysis of the smart city. …”
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Final Year Project / Dissertation / Thesis -
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