Prediction of Cu(II) biosorption performances on wild mushrooms Lactarius piperatus using Artificial Neural Networks (ANN) model
Sign Up to like & getrecommendations! Published in 2017 at "Canadian Journal of Chemical Engineering"
DOI: 10.1002/cjce.22703
Abstract: This work investigates the possible usage of edible mushrooms as support for metabolic quantities of copper. Biosorption potential of natural and biodegradable matrix formed from wild Lactarius piperatus mushrooms, in suspension (LP) and alginate immobilized… read more here.
Keywords: lactarius piperatus; biosorption; artificial neural; ann model ... See more keywords
Computer vision-based method for classification of wheat grains using artificial neural network.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of the science of food and agriculture"
DOI: 10.1002/jsfa.8080
Abstract: BACKGROUND A simplified computer vision-based application using artificial neural network (ANN) depending on multilayer perceptron (MLP) for accurately classifying wheat grains into bread or durum is presented. The images of 100 bread and 100 durum… read more here.
Keywords: computer vision; wheat; ann model; wheat grains ... See more keywords
Impact of Normalization and Input on ARMAX-ANN Model Performance in Suspended Sediment Load Prediction
Sign Up to like & getrecommendations! Published in 2017 at "Water Resources Management"
DOI: 10.1007/s11269-017-1842-z
Abstract: The suspended sediment load in rivers is an important parameter in watershed planning and management. Since daily suspended sediment time series contain linear and nonlinear components, existing prediction models are associated with limitations. Therefore, this… read more here.
Keywords: ann model; input; suspended sediment; model ... See more keywords
Capability assessment of conventional and data-driven models for prediction of suspended sediment load
Sign Up to like & getrecommendations! Published in 2022 at "Environmental Science and Pollution Research"
DOI: 10.1007/s11356-022-18594-4
Abstract: Information about suspended sediment concentration (SSC) in the stream is vital for sustainability of water conservation and erosion control planning, designing and monitoring. In this research, prediction of SSC has been done using artificial neural… read more here.
Keywords: ann model; pare; prediction; suspended sediment ... See more keywords
The Optimal ANN Model for Predicting Bearing Capacity of Shallow Foundations trained on Scarce Data
Sign Up to like & getrecommendations! Published in 2018 at "KSCE Journal of Civil Engineering"
DOI: 10.1007/s12205-018-2636-4
Abstract: This study is focused on determining the potential of using Deep Neural Networks (DNNs) to predict the ultimate bearing capacity of shallow foundation in situations when the experimental data which may be used to train… read more here.
Keywords: bearing capacity; optimal ann; ann model; capacity ... See more keywords
Biodiesel production from castor oil: ANN modeling and kinetic parameter estimation
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Industrial Chemistry"
DOI: 10.1007/s40090-017-0122-3
Abstract: This research work concerns with the transesterification of castor oil with methanol to form biodiesel. As the free fatty acid content in castor oil is more than 1%, an acid catalyst namely, H2SO4 has been… read more here.
Keywords: ann model; biodiesel; oil; castor oil ... See more keywords
A prediction on structural stress and deformation of fish cage in waves using machine-learning method
Sign Up to like & getrecommendations! Published in 2019 at "Aquacultural Engineering"
DOI: 10.1016/j.aquaeng.2019.01.003
Abstract: Abstract Generally, the hydrodynamics of a fish cage are investigated using numerical simulation, physical model experiments, and field measurements. However, these traditional research methods are time consuming and low in efficiency. In this study, an… read more here.
Keywords: ann model; fish cage; model; cage waves ... See more keywords
Modeling and optimization of chlorophenol rejection for spiral wound reverse osmosis membrane modules.
Sign Up to like & getrecommendations! Published in 2020 at "Chemosphere"
DOI: 10.1016/j.chemosphere.2020.129345
Abstract: This study shows an artificial neural network (ANN) model of chlorophenol rejection from aqueous solutions and predicting the performance of spiral wound reverse osmosis (SWRO) modules. This type of rejection shows complex non-linear dependencies on… read more here.
Keywords: ann model; wound reverse; spiral wound; rejection ... See more keywords
On-the-fly artificial neural network for chemical kinetics in direct numerical simulations of premixed combustion
Sign Up to like & getrecommendations! Published in 2021 at "Combustion and Flame"
DOI: 10.1016/j.combustflame.2020.12.038
Abstract: Abstract In this study, an on-the-fly artificial neural network (ANN) framework has been developed for the tabulation of chemical reaction terms in direct numerical simulations (DNS) of premixed and igniting flames. The procedure does not… read more here.
Keywords: ann model; neural network; fly artificial; numerical simulations ... See more keywords
Hydrogen purification layered bed optimization based on artificial neural network prediction of breakthrough curves
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Hydrogen Energy"
DOI: 10.1016/j.ijhydene.2018.12.142
Abstract: Abstract Artificial neural network has generally been used for a quantity of tasks such as classification, prediction, clustering and association analysis in different application fields. To the best of our knowledge, there are few researches… read more here.
Keywords: optimization; neural network; artificial neural; ann model ... See more keywords
Leveraging artificial intelligence for more accurate and reliable predictions of anchors shear breakout capacity in thin concrete members
Sign Up to like & getrecommendations! Published in 2021 at "Structures"
DOI: 10.1016/j.istruc.2021.03.074
Abstract: Abstract Understanding the shear behavior of post-installed anchors embedded in thin concrete members is considered complicated due to the many parameters involved including embedment depth, edge distance, concrete strength, anchor diameter, and member thickness. This… read more here.
Keywords: concrete members; study; ann model; model ... See more keywords