Results 101 to 110 of about 2,998 (192)
An Optuna-Based Metaheuristic Optimization Framework for Biomedical Image Analysis
The success of Deep Learning (DL) in biomedical imaging heavily relies on optimal hyperparameter selection, which remains a complex and computationally intensive challenge. This paper introduces a metaheuristic-inspired Optuna framework for efficient hyperparameter optimization and validates its effectiveness using U-Net as a case study for brain MRI ...
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PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA MENGGUNAKAN MODEL SARIMA-XGBOOST DENGAN OPTIMASI OPTUNA
The Indonesian tourism sector has experienced significant changes following the COVID-19 pandemic, highlighting the need for accurate forecasting systems to support data-driven policy decisions.
Malva, Maisie Yunita
core
Machine learning, a subset of artificial intelligence (AI) is vital for its ability to learn from data and improve system performance. In Indonesia, advancements in ML have significant potential to boost competitiveness and foster sustainable development.
Fitri, Iskandar +2 more
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Leukemia is one of the cancers with the highest mortality rate worldwide; therefore, identifying its subtypes is crucial to support accurate diagnosis and effective treatment.
Cahyaningrum, Rosalia Deviana +1 more
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Heart disease prediction using rough neutrosophic sets and dual-attention neural networks: RNS-OptiDANet. [PDF]
Ashika T, Hannah Grace G.
europepmc +1 more source
Prediction of Ligand Binding to Transthyretin Using Machine Learning Algorithms and Low-Dimensional Molecular Descriptors: A Tox24 Challenge Study. [PDF]
Stefaniak F.
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Prediksi akurat degradasi Compressor Discharge Pressure (PCD) krusial untuk keandalan operasional dan optimalisasi pemeliharaan turbin gas di Central Processing Plant.
Pratama, Andika
core
Accelerating photonic gas sensor design: machine learning-driven inverse optimization of silicon photonics Bragg gratings. [PDF]
Khafagy M, Khafagy M, Swillam MA.
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Forecasting financial anomalies in emerging markets is critical for informed investment and risk management. This study proposes a novel machine learning framework that integrates an OPTUNA-optimized Isolation Forest algorithm with K-Means clustering to ...
Seyed Pendar Toufighi +4 more
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Random Forest Models with Optuna and VMD in Predicting Resistor Resistance Value
Resistors play an indispensable role in modern electronic devices. The variation of resistor values is often nonlinear and influenced by multiple factors, and changes in resistor values directly affect the performance of electronic components. Accurately predicting resistor value changes has thus become a research focus.
Zhang, Jianjun +4 more
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