Search Results - "Bayesian optimization"
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Reinforcement Learning-Based Augmentation of Data Collection for Bayesian Optimization Towards Radiation Survey and Source Localization
Published 2025-04-01Subjects: Get full textSafer and more efficient characterization of radioactive environments requires exploring intelligently, utilizing robotic systems which use smart strategies and physics-based statistical models. Bayesian Optimization (BO) provides one such statistical framework to explainably find the global maximum...
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A data-driven framework for conceptual cost estimation of infrastructure projects using XGBoost and Bayesian optimization
Published 2025-03-01Subjects: Get full textCost estimation is a key component of project plans, yet it is challenging to provide reliable and efficient estimations using conventional methods in the conceptual phase of infrastructure projects. This study proposes a framework that integrates feature selection, extreme gradient boosting (XGBoos...
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Mathematical Optimization in Machine Learning for Computational Chemistry
Published 2025-07-01Subjects: Get full textMachine learning (ML) is transforming computational chemistry by accelerating molecular simulations, property prediction, and inverse design. Central to this transformation is mathematical optimization, which underpins nearly every stage of model development, from training neural networks and tuning...
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Satellite Image Price Prediction Based on Machine Learning
Published 2025-06-01Subjects: Get full textThis study develops a comprehensive, data-driven framework for predicting satellite imagery prices using four state-of-the-art ensemble learning algorithms: XGBoost, LightGBM, AdaBoost, and CatBoost. Two distinct datasets—optical and Synthetic Aperture Radar (SAR) imagery—were assembled, each charac...
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Damping profile learning for human-robot collaboration using Bayesian optimization with a task success rate model
Published 2025-04-01Subjects: Get full textIn the realm of human-robot collaboration, impedance and admittance control are widely utilized techniques to regulate the interaction dynamics between humans and robots. This study proposes a novel approach to enhance the performance of human-robot collaboration by adapting the damping profile used...
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization
Published 2025-12-01Subjects: Get full textOptimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South Africa. We implemented machine learning (ML), op...
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BOL-LPP: A Bayesian-Optimized LSTM Model for Day-Ahead Load Price Forecasting in the ERCOT Market
Published 2025-01-01Subjects: Get full textPrecise short-term load price forecasting is critical for uninterrupted and efficient powersystem operation and energymarket performance. Although machinelearning techniques have been widely employed to predict market prices, achieving reliable dayahead load price forecasts remains challenging in pr...
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Multi-objective Bayesian optimization of eco-friendly gas mixtures for resistive plate chambers
Published 2025-01-01Subjects: Get full textDeveloping environmentally friendly gas mixtures for resistive plate chambers (RPCs) has been a research focus for the last few years. This study presents a novel approach for autonomous optimization of the detector performance and environmental impact of gas mixtures and enabling a more efficient e...
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Achieving Efficient Prompt Engineering in Large Language Models Using a Hybrid and Multi-Objective Optimization Framework
Published 2025-06-01Subjects: “…bayesian optimization…”Prompt optimization is crucial for enhancing the performance of large language models. Traditional Bayesian Optimization (BO) methods face challenges such as local refinement limitations, insufficient parameter tuning, and difficulty handling multi-objectives. This study introduces a hybrid multi-ob...
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Personalized Human Thermal Sensation Prediction Based on Bayesian-Optimized Random Forest
Published 2025-07-01Subjects: “…Bayesian optimization…”Establishing a predictive model for human thermal sensation serves as the fundamental theoretical basis for intelligent control of building HVAC systems based on thermal comfort. The traditional Predicted Mean Vote (PMV) model exhibits low accuracy in predicting human thermal sensation and is not we...
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Data-driven command shaping for improved torque control accuracy of torsional dampers
Published 2025-05-01Subjects: Get full textAutomotive torsional dampers are designed to absorb torque fluctuations generated by the engine and deliver a smoother torque to the components located toward the rear. During the torsion evaluation test of these dampers, torsional torque is repeatedly applied while the damper rotates. Given that to...
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Interpretable machine learning approach for TBM tunnel crown convergence prediction with Bayesian optimization
Published 2025-06-01Subjects: Get full textAccurate prediction of crown convergence in Tunnel Boring Machine (TBM) tunnels is critical for ensuring construction safety, optimizing support design, and improving construction efficiency. This study proposes an interpretable machine learning method based on Bayesian optimization (BO) and SHapley...
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Autonomous materials search using machine learning and ab initio calculations for L10-FePt-based quaternary alloys
Published 2025-12-01Subjects: Get full textThe efficient exploration of expansive material spaces remains a significant challenge in materials science. To address this issue, autonomous material search methods that combine machine learning with ab initio calculations have emerged as a promising solution. These approaches offer a systematic a...
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Accelerated Bayesian optimization for CNN+LSTM learning rate tuning via precomputed Gaussian process subspaces in soil analysis
Published 2025-08-01Subjects: “…Bayesian optimization…”PurposeWe propose an accelerated Bayesian optimization framework for tuning the learning rate of CNN+LSTM models in soil analysis, addressing the computational inefficiency of traditional Gaussian Process (GP)-based methods. This work bridges the gap between computational efficiency and probabilisti...
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Artificial intelligence-based Bayesian optimization and transformer model for tennis motion recognition
Published 2025-06-01Subjects: Get full textBecause the traditional methods are used to analyze human motion behavior, there are large errors and serious over-fitting phenomenon, so a novel tennis motion recognition based on Bayesian optimization and transformer model is proposed in this paper. First, we use an improved generative adversarial...
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Enhancing Multi-Class Classification of Non-Functional Requirements Using a BERT-DBN Hybrid Model
Published 2025-07-01Subjects: Get full textBackground: Software requirements classification is essential to group Non-Functional Requirements (NFR) into several aspects, such as security, usability, performance, and operability. The main challenges in NFR classification are data limitations, text complexity, and high generalization needs. O...
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Machine learning alloying design of biodegradable zinc alloy for bone implants using XGBoost and Bayesian optimization
Published 2025-09-01Subjects: Get full textDeveloping implants using biodegradable materials eliminates the need for secondary surgery, improves both mechanical and biological properties, and enhances biocompatibility. This study proposes a machine learning approach based on Bayesian optimization (BO) and an eXtreme Gradient Boosting (XGBoos...
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AI-aided short-term decision making of rockburst damage scale in underground engineering
Published 2025-08-01Subjects: Get full textRockbursts pose severe risks to underground engineering projects, including mining and tunnelling, where sudden rock failures can lead to substantial infrastructure damage and loss of human lives. An accurate assessment of rockburst damage is essential for safety and effective risk mitigation. This...
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Novel Airfoil-Shaped Radar-Absorbing Inlet Grilles on Aircraft Incorporating Metasurfaces: Multidisciplinary Design and Optimization Using EHVI–Bayesian Method
Published 2025-07-01Subjects: Get full textAircraft, as electromagnetically complex targets, have radar cross-sections (RCSs) that are influenced by various factors, with the inlet duct being a critical component that often serves as a primary source of electromagnetic scattering, significantly impacting the scattering characteristics. In li...
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Monte Carlo Thompson sampling-guided design for antibody engineering
Published 2023-12-01Subjects: Get full textAntibodies are one of the predominant treatment modalities for various diseases. To improve the characteristics of a lead antibody, such as antigen-binding affinity and stability, we conducted comprehensive substitutions and exhaustively explored their sequence space. However, it is practically unfe...
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