Learning-by-examples techniques as applied to electromagnetics
There is a wide number of problems in electromagnetic (EM) engineering that require a real-
time response or in which the input–output relationship is not a-priori known or cannot be …
time response or in which the input–output relationship is not a-priori known or cannot be …
Forecasting and trading cryptocurrencies with machine learning under changing market conditions
H Sebastião, P Godinho - Financial Innovation, 2021 - Springer
This study examines the predictability of three major cryptocurrencies—bitcoin, ethereum,
and litecoin—and the profitability of trading strategies devised upon machine learning …
and litecoin—and the profitability of trading strategies devised upon machine learning …
[HTML][HTML] Explainable machine learning model and reliability analysis for flexural capacity prediction of RC beams strengthened in flexure with FRCM
This paper presents a data-driven approach to determine the load and flexural capacities of
reinforced concrete (RC) beams strengthened with fabric reinforced cementitious matrix …
reinforced concrete (RC) beams strengthened with fabric reinforced cementitious matrix …
Semi‐automatic leaf disease detection and classification system for soybean culture
Development of automatic disease detection and classification system is significantly
explored in precision agriculture. In the past few decades, researchers have studied several …
explored in precision agriculture. In the past few decades, researchers have studied several …
Shear capacity prediction of FRP-RC beams using single and ensenble ExPlainable Machine learning models
Corrosion in steel reinforcement is a central issue behind the severe deterioration of existing
reinforced concrete (RC) structures. Nowadays, fiber-reinforced polymer (FRP) is …
reinforced concrete (RC) structures. Nowadays, fiber-reinforced polymer (FRP) is …
Innovative and rapid analysis for rice authenticity using hand-held NIR spectrometry and chemometrics
Rice is the second most important food staple worldwide and the demand will continue to
increase with the growth of the world population. As reports grow that frauds is prevalent in …
increase with the growth of the world population. As reports grow that frauds is prevalent in …
A comparative study of machine learning algorithms for the prediction of compressive strength of rice husk ash-based concrete
The cementitious behavior of Rice Husk Ash (RHA) has caused its possible addition as a
replacement material for cement which has been proven to influence the strength of …
replacement material for cement which has been proven to influence the strength of …
Spatial mapping of groundwater springs potentiality using grid search-based and genetic algorithm-based support vector regression
In this study, groundwater springs potentiality maps were prepared using a novel integrated
model, support vector regression (SVR) with genetic algorithm (GA), for the Jerash and …
model, support vector regression (SVR) with genetic algorithm (GA), for the Jerash and …
Explainable machine learning based efficient prediction tool for lateral cyclic response of post-tensioned base rocking steel bridge piers
This study presents a novel explainable machine learning (ML) based predictive model for
the lateral cyclic response of post-tensioned (PT) base rocking steel bridge piers. The PT …
the lateral cyclic response of post-tensioned (PT) base rocking steel bridge piers. The PT …
[HTML][HTML] FAI: Fast, accurate, and intelligent approach and prediction tool for flexural capacity of FRP-RC beams based on super-learner machine learning model
Fiber-reinforced polymer (FRP) composites have recently been considered in the field of
structural engineering as one of the best alternatives to conventional steel reinforcement …
structural engineering as one of the best alternatives to conventional steel reinforcement …