Automatic tuning of hyperparameters using Bayesian optimization

AH Victoria, G Maragatham - Evolving Systems, 2021 - Springer
Deep learning is a field in artificial intelligence that works well in computer vision, natural
language processing and audio recognition. Deep neural network architectures has number …

[图书][B] Dimensionality reduction with unsupervised nearest neighbors

O Kramer - 2013 - Springer
The growing information infrastructure in a variety of disciplines involves an increasing
requirement for efficient data mining techniques. Fast dimensionality reduction methods are …

[HTML][HTML] Maize disease identification based on optimized support vector machine using deep feature of DenseNet201

A Dash, PK Sethy, SK Behera - Journal of Agriculture and Food Research, 2023 - Elsevier
In recent times, maize diseases have become widespread globally, adversely impacting
agricultural productivity and causing significant financial losses. Recognizing these …

Co‐optimization of CO2‐EOR and storage processes in mature oil reservoirs

W Ampomah, RS Balch, RB Grigg… - … Gases: Science and …, 2017 - Wiley Online Library
This paper presents an optimization methodology for CO2 enhanced oil recovery in partially
depleted reservoirs. A field‐scale compositional reservoir flow model was developed for …

[HTML][HTML] Enhancing Land Cover/Land Use (LCLU) classification through a comparative analysis of hyperparameters optimization approaches for deep neural network …

A Azedou, A Amine, I Kisekka, S Lahssini… - Ecological …, 2023 - Elsevier
Sustainable natural resources management relies on effective and timely assessment of
conservation and land management practices. Using satellite imagery for Earth observation …

Bayesian optimization with support vector machine model for parkinson disease classification

AM Elshewey, MY Shams, N El-Rashidy, AM Elhady… - Sensors, 2023 - mdpi.com
Parkinson's disease (PD) has become widespread these days all over the world. PD affects
the nervous system of the human and also affects a lot of human body parts that are …

A reinforcement learning approach for waterflooding optimization in petroleum reservoirs

F Hourfar, HJ Bidgoly, B Moshiri, K Salahshoor… - … Applications of Artificial …, 2019 - Elsevier
Waterflooding optimization in closed-loop management of the oil reservoirs is always
considered as a challenging issue due to the complicated and unpredicted dynamics of the …

Novel performance metrics for robust multi-objective optimization algorithms

S Mirjalili, A Lewis - Swarm and Evolutionary Computation, 2015 - Elsevier
Performance metrics are essential for quantifying the performance of optimization algorithms
in the field of evolutionary multi-objective optimization. Such metrics allow researchers to …

Insight into automatic image diagnosis of ear conditions based on optimized deep learning approach

HM Afify, KK Mohammed, AE Hassanien - Annals of biomedical …, 2024 - Springer
Examining otoscopic images for ear diseases is necessary when the clinical diagnosis of
ear diseases extracted from the knowledge of otolaryngologists is limited. Improved …

Development of an intelligent tool condition monitoring system to identify manufacturing tradeoffs and optimal machining conditions

WJ Lee, GP Mendis, JW Sutherland - Procedia Manufacturing, 2019 - Elsevier
Smart manufacturing has leveraged the evolution of a sensor-based and data-driven
platform to improve manufacturing outcomes. As a result of increased use of sensors and …