@inproceedings{0bc8291f0219422c9283e31305b339d6,
title = "Algal growth rate modeling and prediction optimization using incorporation of MLP and CPSO algorithm",
abstract = "The cause of global warming is the existence of greenhouse gases that trap the emitted infrared wave and cause the increasing of the earth's temperature. One of the predominant greenhouse gases in the atmosphere is CO2. Biosequestration by utilizing micro algae is one of the promising method to reduce the concentration of CO2 in the atmosphere. This research focuses on the modeling of the algal growth which is one of the parameter that defines the amount of CO2 which can be fixated by algal. From the observation data, the growth behavior is modeled by regression method, Multilayer Perceptron (MLP) algorithm. To optimize the algorithm, MLP is also combined with The Canonical Particle Swarm Optimization (CPSO). The result shows that modeling using MLP-CPSO is more accurate than the original MLP and MLP-PSO respectively by 25% and 15% in RAE. MLP-CPSO also shows the best performance in RMSE with 0.091 and coefficient correlation (r) with 0.92.",
keywords = "RAE, RMSE, algal growth, coefficient correlation, microalgae, multilayer perceptron, the canonical particle swarm optimization",
author = "Wisnu Jatmiko and Purnomo, {Dwi M.J.} and Machmud Alhamidi and Ari Wibisono and Hanif Wisesa and Petrus Mursanto and Anom Bowolaksono and Dian Hendrayanti and Fajar Addana",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015 ; Conference date: 23-11-2015 Through 25-11-2015",
year = "2016",
month = mar,
day = "21",
doi = "10.1109/MHS.2015.7438293",
language = "English",
series = "2015 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015",
address = "United States",
}