Water Content Prediction in Geophysical Exploration Based on BP Network
This research is adopting neural network technology for the use of a number of known geophysical testing the well Pumping test data to the geophysical parameters of aquifer discharge umts with single-hole model composed of the training sample set, establishing the err BP network forecasting model for regional geophysical methods unknown under ground water content prediction, this will be major improvement to the traditional water content prediction.
KeywordsArtificial Networks Integrated Geophysical methods Water content prediction
- 1.Hansen RO (1997) Feature recognition from potential fields using neural networks geophysical. Soc Expl Geophys 23(3):356–359Google Scholar
- 2.Dong Y, Ma YK et al (1996) Pattern recognition of the characteristics of AE source using neural. Legworks 46(90):77–79Google Scholar
- 3.Cisar D, Novotn TJ (1996) Electromagnetic data-evaluation using a neural network: initial investigation-underground storage tanks. Geophysical 15(2):67–69Google Scholar
- 4.Jonathan B, Franklin A (2004) Using spatially integrated cross well geophysics for environmental site assessment 2004 Joint Assembly of the Canadian Get Physical Union. Am Geophys Union Soc Explor Geophys Environ Eng Geophys Soc 85(17):86–88Google Scholar