Results 131 to 140 of about 4,344 (219)

Interpretable model for rockburst intensity prediction based on Shapley values-based Optuna-random forest

To address the limitation of traditional machine learning models in explaining the rockburst intensity prediction process, this study proposes an interpretable rockburst intensity prediction model.
Shunchuan Wu, Yaxi Shen, Yongbing Wang, Zhiquan Yang, Jiaxin Wang   +4 more
core   +1 more source

An Optuna-Based Metaheuristic Optimization Framework for Biomedical Image Analysis

Engineering, Technology & Applied Science Research
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 ...
openaire   +1 more source

Optuna Tuning Results PPO Reinforcement Learning Hyperparameters Performance

Systematic hyperparameter tuning using Optuna was expected to improve PPO model performance in a multi-microgrid environment. We hypothesized that optimizing hyperparameters like learning rate and network architecture would enhance model performance ...
Messlem, A (via Mendeley Data), Messlem, Abdelkader   +1 more
core   +1 more source

Forecasting Flower Prices by Long Short-Term Memory Model with Optuna

The oriental lily ‘Casa Blanca’ is one of the most popular and high-value flowers. The period for keeping these flowers refrigerated is limited.
Ping-Feng Pai, Chieh-Huang Chen, Ying-Lei Lin   +2 more
core   +1 more source

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, Li, Hao, Wang, Shenglei, Wang, Junjun, Qin, Wenqiang   +4 more
openaire   +1 more source

Machine learning models for predicting the hardness of additively manufactured Polymethyl Methacrylate (PMMA) parts for biomedical applications. [PDF]

PLoS One
Veeman D, Ponnuswamy PC, Vellaisamy M, Mangayarkarasi SAK, Katiyar JK.   +4 more
europepmc   +1 more source

Prediksi Laju Inflasi di Jawa Timur Menggunakan Model N-BEATS dan Optimasi Optuna: Prediction of Inflation Rate in East Java Using the N-BEATS Model and Optuna Optimization

Inflasi merupakan indikator penting yang memengaruhi kestabilan dan pertumbuhan ekonomi suatu wilayah. Prediksi inflasi yang akurat sangat dibutuhkan guna mendukung perumusan kebijakan ekonomi yang tepat.
Trimono, Trimono, Riswanda, Mohammad Nizar, Saputra, Wahyu Syaifullah Jauharis   +2 more
core   +1 more source

KLASIFIKASI OBAT ANTI TUBERKULOSIS MENGGUNAKAN ALGORITMA CATEGORICAL BOOSTING DENGAN OPTIMASI OPTUNA [PDF]

Penyakit tuberkulosis merupakan salah satu penyebab utama kematian global, dengan angka kematian mencapai 1,30 juta jiwa pada tahun 2022, meningkat sebesar 3,2% dibandingkan tahun sebelumnya.
Harmoni, Yosua Satria Bara
core  

Risk stratification in intermediate asymptomatic carotid artery disease: a multi-modal approach combining local flow dynamics and systemic clinical profiles. [PDF]

Front Surg
Siogkas P, Pleouras D, Potsika V, Tsakanikas V, Sigala F, Galyfos G, Charalampopoulos G, Koncar I, Fotiadis DI.   +8 more
europepmc   +1 more source

PREDIKSI HARGA DAGING AYAM BROILER DI JAWA TIMUR MENGGUNAKAN METODE XGBOOST DENGAN OPTIMASI OPTUNA

Broiler chicken meat is one of the most widely consumed poultry commodities in Indonesia due to its affordable price and abundant availability. However, broiler chicken prices often experience significant fluctuations due to various factors, such as the ...
Salsabilah, Elina
core