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

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 Network Modelling

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 ◽

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 ◽

Artificial Neural 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 Network Modelling

Artificial Neural ◽

Feed-Forward Neural Network Modelling

Perspectives in Neural Computing - Intelligent Systems and Financial Forecasting ◽

10.1007/978-1-4471-0949-5_3 ◽

1997 ◽

pp. 37-53

Author(s):

Jason Kingdon

Keyword(s):

Neural Network ◽

Feed Forward Neural Network ◽

Network Modelling ◽

Feed Forward ◽

Neural network modelling for accurate prediction of thermal efficiency of a flat plate solar collector working with nanofluids

International Journal of Ambient Energy ◽

10.1080/01430750.2018.1525576 ◽

2018 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Mohsen Mirzaei ◽

Mostafa Zamani Mohiabadi

Keyword(s):

Neural Network ◽

Flat Plate ◽

Thermal Efficiency ◽

Solar Collector ◽

Accurate Prediction ◽

Network Modelling ◽

Flat Plate Solar Collector