Results 61 to 70 of about 173,823 (173)

A Hybrid Brain Stroke Prediction Framework: Integrating Feature Selection, Classification, and Hyperparameter Optimization

Engineering Reports
Stroke is a leading cause of death and disability worldwide, requiring accurate and early prediction to ensure timely medical intervention. This study proposes a hybrid system that combines optimal feature selection and advanced classification techniques
Mohammad Amin, Khalid M. O. Nahar, Hasan Gharaibeh, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Nesrine Atitallah, Ali Gharaibeh, Raneem Hamad, Raed Abu Zitar, Aseel Smerat, Laith Abualigah   +10 more
doaj   +1 more source

Exploration-Driven Genetic Algorithms for Hyperparameter Optimisation in Deep Reinforcement Learning

Applied Sciences
This paper investigates the application of genetic algorithms (GAs) for hyperparameter optimisation in deep reinforcement learning (RL), focusing on the Deep Q-Learning (DQN) algorithm.
Bartłomiej Brzęk, Barbara Probierz, Jan Kozak   +2 more
doaj   +1 more source

Short-Term Load Forecasting in Power Systems Based on the Prophet–BO–XGBoost Model

Energies
To tackle the challenges of limited accuracy and poor generalization in short-term load forecasting under complex nonlinear conditions, this study introduces a Prophet–BO–XGBoost-based forecasting framework.
Shuang Zeng, Chang Liu, Heng Zhang, Baoqun Zhang, Yutong Zhao   +4 more
doaj   +1 more source

Multi-aircraft collaborative batching method based on self-organizing clustering

工程科学学报
This article addresses the bathing problem in multi-machine collaborative operations, proposing a method based on improved self-organizing iterative clustering.
Shihui ZHANG, Tongqing JIN, Yunjie ZHANG, Rui ZHOU, Huaming RAN, Liliang ZHOU   +5 more
doaj   +1 more source

A Photosynthetic Rate Prediction Model for Cucumber Based on a Machine Learning Algorithm and Multi-Factor Environmental Analysis

Horticulturae
Plant photosynthetic rate prediction models have the potential to enhance production efficiency and advance intelligent control in protected agriculture.
Yanxiu Miao, Liyuan Liu, Miaoyu Wang, Zhihao Zeng, Jun Zhang, Yongsan Cheng, Bin Li   +6 more
doaj   +1 more source

Collaborative hyperparameter tuning

, 2013
Hyperparameter learning has traditionally been a manual task because of the limited number of trials. Today's computing infrastructures allow bigger evaluation budgets, thus opening the way for algorithmic approaches. Recently, surrogate-based optimization was successfully applied to hyperparameter learning for deep belief networks and to WEKA ...
Bardenet, R., Brendel, M., Kégl, Balázs, Sebag, Michèle   +3 more
openaire   +1 more source

Enhancing Short-Term Load Forecasting Using Hyperparameter-Optimized Deep Learning Approaches

Energies
The reliability and efficiency of power system operations, especially in smart grid scenarios, depend on accurate load demand forecasting. Electrical load forecasting is crucial for power system design, fault protection and diversification as it reduces ...
Nazmun Nahar Karima, Shameem Ahmad, Amirul Islam, A.S. Nazmul Huda, Lilik Jamilatul Awalin, Syahirah Abd Halim, Hazlie Mokhlis, Mohd Syukri Ali, Syahril Mubarok   +8 more
doaj   +1 more source

Interpretable Ensemble Models for Lifestyle-Based Sleep Disorder Prediction

Journal of Applied Informatics and Computing
Sleep disorders are a major global health concern that affect cognitive performance, mental well-being, and long-term physiological health. Conventional diagnostic methods such as polysomnography are time-consuming and resource-intensive, limiting their ...
Farhan Rahardian, Sindhu Rakasiwi
doaj   +1 more source

Vision-Based Smart Wearable Assistive Navigation System Using Deep Learning for Visually Impaired People

Automation
People affected by vision impairment experience significant challenges in mobility and daily life activities. In this paper, a smart assistive navigation system is proposed to address mobility challenges and to enhance the independence of visually ...
Syed Salman Shah, Abid Imran, Saad-Ur-Rehman, Arsalan Arif, Khurram Khan, Muhammad Arsalan, Sajjad Manzoor, Ghulam Jawad Sirewal   +7 more
doaj   +1 more source

Fairness-Aware Hyperparameter Optimization

, 2020
In recent years, increased usage of machine learning algorithms has been accompanied by several reports of machine bias in areas from recidivism assessment, to job-applicant screening tools, and estimating mortgage default risk. Additionally, recent advances in machine learning have prominently featured so-called "black-box" models (e.g.
openaire   +2 more sources