Search Results - (( rendering optimization method algorithm ) OR ( _ implication tree algorithm ))
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Optimization Of 3d Reconstruction Surface Rendering Algorithm For Osferion Bone Void Filling
Published 2023“…Among the 3D reconstruction algorithms, surface rendering algorithms are more suitable for effectively visualizing the bones’ structure and shape. …”
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Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti
Published 2024“…The project involves data collection, data preparation, and the implementation of the decision tree algorithm for price prediction. The decision tree's effectiveness and accuracy in predicting laptop prices are evaluated through rigorous testing and validation. …”
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Diagnosis and recommender system for diabetes patient using decision tree / Nurul Aida Mohd Zamary
Published 2024“…The phase of this project is divided into data preprocessing, implementation of the decision tree algorithm, and evaluation of the algorithm and prototype. …”
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Success history moth flow optimization for multi-goal generation dispatching with nonlinear cost functions
Published 2023“…The valve-point loading causes oscillations in the input-output characteristics of generating units, hence rendering the CEED problem an imperfect optimization problem. …”
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Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems
Published 2024“…These traditional methods in the standalone form are characterized by some drawbacks which render the method ineffective. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm
Published 2025“…The safe experimentation dynamics algorithm (SEDA) is one such method that optimizes controller parameters using data-driven techniques. …”
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Performance of 2-DOF PID controller in AGC of two area interconnected power system using PSO algorithm
Published 2022“…Therefore, in this work, particle swarm optimization (PSO) algorithm is formulated for tuning the gain values of the suggested controllers in multi-area interconnected system. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Practical implications In terms of managerial implications, the findings in this research help to frame the adoption of a more advanced analytical approach to forecasting, using a Machine Learning algorithm, in solving a newsvendor problem. …”
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Cuckoo optimised 2DOF controllers for stabilising the frequency changes in restructured power system with wind-hydro units
Published 2021“…Different types of metaheuristic optimisation methods like teaching–learning-based optimisation (TLBO) and cuckoo search algorithms are suggested to acquire the optimal gain values of the proposed controllers. …”
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Intelligent traffic lights using Q-learning
Published 2022“…The conventional traffic light system contributes to the safety of the road but is not an effective method of traffic control. The failure of traffic intersections to learn from their past mistakes has rendered them incapable of adapting to the dynamic changes in traffic flow. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…After conducting stepwise experiments and comparing with three benchmark methods - a baseline FL method and two PFL approaches in similar optimization scheme - the results shows that POLA not only systematically optimizes its internal outputs but also outperforms the comparison methods. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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Automated fault detection and extraction under gas chimneys using hybrid discontinuity attributes
Published 2021“…The data optimization and conditioning processes are applied to suppress random and coherent noise first, and then a combination of seismic attributes is generated and co-rendered to enhance the discontinuities. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar
Published 2021“…To overcome these limitations, this research has proposed five machine learning algorithms namely Linear Regression, Lasso, Ridge, Random Forest and Decision Tree. …”
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