@inbook{3b025c4d9bab419a992899637c69fc8d,
title = "Parameter estimation of vertical two-layer soil model via brain storm optimization algorithm",
abstract = "A practical soil model is derived mathematically based on the measurement principles of Wenner{\textquoteright}s method. The Wenner{\textquoteright}s method is a conventional approach to measuring the apparent soil resistivity. This soil model constitutes two-soil layer with different properties vertically. Thus this model is called the vertical two-layer soil model. The motivation for the mathematical model is to estimate relevant parameters accurately from the data obtained from site measurements. This parameter estimation is in fact a challenging optimization problem. From the plotted graphs, this problem features a continuous but non-smooth landscape with a steep alley. This poses a great challenge to any optimization tool. Two prominent algorithms are applied, namely Gauss-Newton (GN) and Brain Storm Optimization (BSO). Results obtained conclude that the GN is fast but diverges due to bad starting points. On the contrary, the BSO is slow but it never diverges and is more stable.",
keywords = "Brain storm optimization, Grounding, Parameter estimation, Soil model",
author = "Ting, {Tiew On} and Yuhui Shi",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.",
year = "2016",
doi = "10.1007/978-3-319-41000-5_50",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "500--511",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
}