Time series forecasting using ensemble learning methods for emergency prevention in hydroelectric power plants with dam
In hydroelectric plants, the responsibility for the operation of the reservoirs typically lies with
the national system operator, who controls the level of the reservoirs based on a stochastic …
the national system operator, who controls the level of the reservoirs based on a stochastic …
[HTML][HTML] Soil texture classification using multi class support vector machine
U Barman, RD Choudhury - Information processing in agriculture, 2020 - Elsevier
The objective of this study is to process the soil images to generate a digital soil
classification system for rural farmers at low cost. Soil texture is the main factor to be …
classification system for rural farmers at low cost. Soil texture is the main factor to be …
11K Hands: Gender recognition and biometric identification using a large dataset of hand images
M Afifi - Multimedia Tools and Applications, 2019 - Springer
Human hand not only possesses distinctive feature for gender information, it is also
considered one of the primary biometric traits used to identify a person. Unlike face images …
considered one of the primary biometric traits used to identify a person. Unlike face images …
Insights into water-lubricated transport of heavy and extra-heavy oils: Application of CFD, RSM, and metaheuristic optimized machine learning models
With diminishing light crude oil reserves, the focus shifts to heavy and extra-heavy crude oil,
posing challenges with high viscosity impeding flow. Water-lubricated technology addresses …
posing challenges with high viscosity impeding flow. Water-lubricated technology addresses …
[图书][B] Kernel based algorithms for mining huge data sets
This is a book about (machine) learning from (experimental) data. Many books devoted to
this broad field have been published recently. One even feels tempted to begin the previous …
this broad field have been published recently. One even feels tempted to begin the previous …
Machine learning and network analyses reveal disease subtypes of pancreatic cancer and their molecular characteristics
Given that the biological processes governing the oncogenesis of pancreatic cancers could
present useful therapeutic targets, there is a pressing need to molecularly distinguish …
present useful therapeutic targets, there is a pressing need to molecularly distinguish …
Jammer classification in GNSS bands via machine learning algorithms
R Morales Ferre, A De La Fuente, ES Lohan - Sensors, 2019 - mdpi.com
This paper proposes to treat the jammer classification problem in the Global Navigation
Satellite System bands as a black-and-white image classification problem, based on a time …
Satellite System bands as a black-and-white image classification problem, based on a time …
Predicting crash injury severity with machine learning algorithm synergized with clustering technique: A promising protocol
Predicting crash injury severity is a crucial constituent of reducing the consequences of
traffic crashes. This study developed machine learning (ML) models to predict crash injury …
traffic crashes. This study developed machine learning (ML) models to predict crash injury …
Extreme value theory inspires explainable machine learning approach for seizure detection
Epilepsy is one of the brightest manifestations of extreme behavior in living systems.
Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually …
Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually …
Data-importance aware user scheduling for communication-efficient edge machine learning
With the prevalence of intelligent mobile applications, edge learning is emerging as a
promising technology for powering fast intelligence acquisition for edge devices from …
promising technology for powering fast intelligence acquisition for edge devices from …