Condition monitoring based on partial discharge diagnostics using machine learning methods: A comprehensive state-of-the-art review
This paper presents a state-of-the-art review on machine learning (ML) based intelligent
diagnostics that have been applied for partial discharge (PD) detection, localization, and …
diagnostics that have been applied for partial discharge (PD) detection, localization, and …
Autoreservoir computing for multistep ahead prediction based on the spatiotemporal information transformation
We develop an auto-reservoir computing framework, Auto-Reservoir Neural Network
(ARNN), to efficiently and accurately make multi-step-ahead predictions based on a short …
(ARNN), to efficiently and accurately make multi-step-ahead predictions based on a short …
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 …
A model for particulate matter (PM2. 5) prediction for Delhi based on machine learning approaches
Abstract Particulate matter (PM 2.5) remains one of the most dominant contributors to air
pollution in Delhi and its acute or chronic exposures have exerted serious health …
pollution in Delhi and its acute or chronic exposures have exerted serious health …
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 …
Machine learning-based predictive model for tensile and flexural strength of 3D-printed concrete
The additive manufacturing of concrete, also known as 3D-printed concrete, is produced
layer by layer using a 3D printer. The three-dimensional printing of concrete offers several …
layer by layer using a 3D printer. The three-dimensional printing of concrete offers several …
Using machine learning to predict game outcomes based on player-champion experience in League of Legends
TD Do, SI Wang, DS Yu, MG McMillian… - Proceedings of the 16th …, 2021 - dl.acm.org
League of Legends (LoL) is the most widely played multiplayer online battle arena (MOBA)
game in the world. An important aspect of LoL is competitive ranked play, which utilizes a …
game in the world. An important aspect of LoL is competitive ranked play, which utilizes a …
Support vector machine as an alternative method for lithology classification of crystalline rocks
C Deng, H Pan, S Fang, AA Konaté… - Journal of Geophysics …, 2017 - academic.oup.com
With the expansion of machine learning algorithms, automatic lithology classification that
uses well logging data is becoming significant in formation evaluation and reservoir …
uses well logging data is becoming significant in formation evaluation and reservoir …