Macro-invertebrates in a dynamic river environment: analysis of time series from artificial substrates, using a ‘white box’ neural network modelling method

Modelling Method ◽

Analysis Of Time Series

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

Atmospheric Environment ◽

10.1016/j.atmosenv.2014.04.051 ◽

2014 ◽

Vol 94 ◽

pp. 106-116 ◽

Cited By ~ 70

Author(s):

M.A. Elangasinghe ◽

N. Singhal ◽

K.N. Dirks ◽

J.A. Salmond ◽

S. Samarasinghe

Keyword(s):

Neural Network ◽

Time Series ◽

Time Series Analysis ◽

Coastal Site ◽

Network Modelling ◽

Complex Time ◽

Series Analysis ◽

Artificial neural network modelling for biodecolorization of Basic Violet 03 from aqueous solution by biochar derived from agro-bio waste of groundnut hull: Kinetics and thermodynamics

Chemosphere ◽

10.1016/j.chemosphere.2021.130191 ◽

2021 ◽

Vol 276 ◽

pp. 130191

Author(s):

Saravanan Praveen ◽

Josephraj Jegan ◽

Thillainayagam Bhagavathi Pushpa ◽

Ravindiran Gokulan

Keyword(s):

Neural Network ◽

Aqueous Solution ◽

Network Modelling ◽

Kinetics And Thermodynamics ◽

Artificial Neural ◽

Optimization of genetic algorithm parameter in hybrid genetic algorithm-neural network modelling: Application to spray drying of coconut milk

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/991/1/012139 ◽

2020 ◽

Vol 991 ◽

pp. 012139

Author(s):

J L K Ming ◽

F S Taip ◽

M S Anuar ◽

S B M Noor ◽

Z Abdullah

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

Spray Drying ◽

Hybrid Genetic Algorithm ◽

Coconut Milk ◽

Network Modelling ◽

Modelling Application ◽

Genetic Algorithm Parameter

Neural network modelling for determining the priority areas of regional development

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/986/1/012017 ◽

2020 ◽

Vol 986 ◽

pp. 012017

Author(s):

A K Moskalev ◽

A E Petrunina ◽

N S Tsygankov

Keyword(s):

Neural Network ◽

Regional Development ◽

Network Modelling ◽

Priority Areas ◽

Support Vector Machine and Artificial Neural Network Modelling of Orogenic Gold Prospectivity Mapping in the Swayze greenstone belt, Ontario, Canada

Ore Geology Reviews ◽

10.1016/j.oregeorev.2020.103968 ◽

2020 ◽

pp. 103968

Author(s):

Francisca Maepa ◽

Richard S. Smith ◽

Abera Tessema

Keyword(s):

Neural Network ◽

Support Vector Machine ◽

Greenstone Belt ◽

Orogenic Gold ◽

Support Vector ◽

Network Modelling ◽

Artificial Neural Network Modelling ◽

Prospectivity Mapping

Online dynamic prediction of potassium concentration in biomass fuels through flame spectroscopic analysis and recurrent neural network modelling

Fuel ◽

10.1016/j.fuel.2021.121376 ◽

2021 ◽

Vol 304 ◽

pp. 121376

Author(s):

Xinli Li ◽

Changxing Han ◽

Gang Lu ◽

Yong Yan

Keyword(s):

Neural Network ◽

Recurrent Neural Network ◽

Spectroscopic Analysis ◽

Potassium Concentration ◽

Biomass Fuels ◽

Network Modelling ◽

Dynamic Prediction ◽

Positioning and focusing of light sources in light concentrating systems using convolutional neural network modelling

Solar Energy ◽

10.1016/j.solener.2021.03.002 ◽

2021 ◽

Vol 218 ◽

pp. 445-454

Author(s):

Daniel Haseler ◽

Arshad M. Ali ◽

Konstantinos E. Kakosimos

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Light Sources ◽

Network Modelling ◽

Towards a mathematical framework to inform neural network modelling via polynomial regression

Neural Networks ◽

10.1016/j.neunet.2021.04.036 ◽

2021 ◽

Author(s):

Pablo Morala ◽

Jenny Alexandra Cifuentes ◽

Rosa E. Lillo ◽

Iñaki Ucar

Keyword(s):

Neural Network ◽

Polynomial Regression ◽

Mathematical Framework ◽

Network Modelling ◽

Artificial Neural Network Modelling for Short Term Load Forecasting

10.1109/ict-pep53949.2021.9601105 ◽

2021 ◽

Author(s):

Mahshooq Abdul Majeed ◽

Soumya Mudgal ◽

Lalit Tak ◽

Janavi Popat ◽

Harsh Kakadiya ◽

...

Keyword(s):

Neural Network ◽

Load Forecasting ◽

Short Term ◽

Network Modelling ◽

Short Term Load Forecasting ◽

Artificial Neural ◽

Artificial neural network modelling of Cr(VI) surface adsorption with NiO nanoparticles using the results obtained from optimization of response surface methodology

Neural Computing and Applications ◽

10.1007/s00521-017-3172-8 ◽

2017 ◽

Vol 29 (10) ◽

pp. 969-979 ◽

Cited By ~ 3

Author(s):

Saber Khodaei Ashan ◽

Nasim Ziaeifar ◽

Rana Khalilnezhad

Keyword(s):

Neural Network ◽

Response Surface Methodology ◽

Response Surface ◽

Surface Adsorption ◽

Nio Nanoparticles ◽

Network Modelling ◽

Artificial Neural ◽