Nonlinear inversion algorithm of geological forecast in induced polarization method

The linear inversion of hydro-geological prospecting relies on the initial model deeply and its accuracy is poor, so the paper applies the hybrid algorithm of ant colony algorithm (ACO) and BP neural network. Through the MATLAB programming to verify the classical model of the stone with different po...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Chinese Control and Decision Conference S. 1154 - 1158
Hauptverfasser: Yao, Li, Chen, Feng-chao
Format: Tagungsbericht Journal Article
Sprache:Englisch
Veröffentlicht: IEEE 01.05.2016
Schlagworte:
Advanced Exploration
Algorithms
Ant Colony Optimization
Biological neural networks
Conductivity
Conferences
Electrodes
Geology
Inversions
Joint Inversion
Mathematical models
Matlab
Neural networks
Polarization Method
Testing
Training
ISSN:1948-9447
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The linear inversion of hydro-geological prospecting relies on the initial model deeply and its accuracy is poor, so the paper applies the hybrid algorithm of ant colony algorithm (ACO) and BP neural network. Through the MATLAB programming to verify the classical model of the stone with different position date. The inversion results are in agreement with the actual models. In order to highlight the advantages of the joint inversion, the BP algorithm is compared with the ACO-BP algorithm, The results show that the ACO-BP algorithm has its advantages in the inversion occurrence of the abnormal body, it can achieve the goal of advance warn in geological engineering.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Conference-1
ObjectType-Feature-3
content type line 23
SourceType-Conference Papers & Proceedings-2
ISSN:1948-9447
DOI:10.1109/CCDC.2016.7531157