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Prediction of Moisture Content of Chlorella vulgaris Microa..:

, In: 2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM),

Aquino, Heinrick L. ; Concepcion, Ronnie S. ; Mayol, Andres Philip... - p. 1-6 , 2021

Link: https://doi.org/10.1109/HNICEM54116.2021.9731926

RT 
T1 <cTitle>2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)</cTitle>: T1 <Title>Prediction of Moisture Content of Chlorella vulgaris Microalgae Using Hybrid Evolutionary Computing and Neural Network Variants for Biofuel Production</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-9731926&Exemplar=1&LAN=DE
				
A1 Aquino, Heinrick L.
A1 Concepcion, Ronnie S.
A1 Mayol, Andres Philip
A1 Bandala, Argel A.
A1 Culaba, Alvin
A1 Cuello, Joel
A1 Dadios, Elmer P.
A1 Ubando, Aristotle T.
A1 San Juan, Jayne Lois G.
YR 2021
K1 Training
K1 Computational modeling
K1 Biological system modeling
K1 Neurons
K1 Moisture
K1 Genetic programming
K1 Artificial neural networks
K1 microwave drying
K1 microalgae
K1 neural network
K1 genetic algorithm
K1 machine learning
SP 1
OP 6
LK http://dx.doi.org/https://doi.org/10.1109/HNICEM54116.2021.9731926
DO https://doi.org/10.1109/HNICEM54116.2021.9731926
SF ELIB - SuUB Bremen

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