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  • 标题:Optimising noise intervened data processes for inverse geoelectrical problem using adaptive neuro fuzzy inference system (ANFIS)
  • 本地全文:下载
  • 作者:A. Stanley Raj ; D. Hudson Oliver ; Y. Srinivas
  • 期刊名称:NRIAG Journal of Astronomy and Geophysics
  • 印刷版ISSN:2090-9977
  • 电子版ISSN:2090-9985
  • 出版年度:2021
  • 卷号:10
  • 期号:1
  • 页码:138-154
  • DOI:10.1080/20909977.2021.1900525
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Geoelectrical inversion has some problems in inverting data due to the heterogeneous behaviour of Earth. One of the major concerns in inverting the data is due to the influence of noises, which comes from the disturbance due to human interventions, atmospheric variations, and electromagnetic disturbance, etc. . In this paper, we have presented a concept of Neuro Fuzzy algorithm which can interpret the noisy data successfully. Moreover, the data were tested with artificially generated random noise, gaussian noise and missing data. Kanyakumari field region having complex geological structures and its performance is validated with a maximum threshold. Kanyakumari field region having complex geological structures is used and the performance is validated with a maximum threshold. Neuro fuzzy technique has the dominant feature of training and testing the data with utmost accuracy. These implications are made to create the specific Graphical User Interface (GUI) for the algorithm and it works well for all types of Vertical Electrical Sounding (VES) data with good performance results.
  • 关键词:Adaptive Neuro Fuzzy Inference System;resistivity inversion;subsurface modelling;noise intervened processing;layer model
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