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- Jiang Li, Liang-Chi Shen
- IEEE Trans. Geoscience and Remote Sensing
- 1993

- Kou-Yuan Huang, Liang-Chi Shen, Kai-Ju Chen, Ming-Che Huang
- The 2012 International Joint Conference on Neural…
- 2012

Well log data inversion is important for the inversion of true formation. There exists a nonlinear mapping between the measured apparent conductivity (C<sub>a</sub>) and the true formation conductivity (C<sub>t</sub>). We adopt the multilayer perceptron (MLP) to approximate the nonlinear input-output mapping and propose the use of particle swarm… (More)

- Kou-Yuan Huang, Liang-Chi Shen, Li-Sheng Weng
- IGARSS
- 2011

- Kou-Yuan Huang, Liang-Chi Shen, Chun-Yu Chen
- 2008 IEEE International Joint Conference on…
- 2008

Multilayer perceptron is adopted for well log data inversion. The input of the neural network is the apparent resistivity (Ra) of the well log and the desired output is the true formation resistivity (Rt). The higher order of the input features and the original features are the network input for training. Gradient descent method is used in the back… (More)

- Kou-Yuan Huang, Liang-Chi Shen, Kai-Ju Chen, Ming-Che Huang
- IGARSS
- 2013

- Kou-Yuan Huang, Liang-Chi Shen, Li-Sheng Weng
- The 2011 International Joint Conference on Neural…
- 2011

We adopt the radial basis function network (RBF) for well log data inversion. We propose the 3 layers RBF. Inside RBF, the 1-layer perceptron is replaced by 2-layer perceptron. It can do more nonlinear mapping. The gradient descent method is used in the back propagation learning rule at 2-layer perceptron. The input of the network is the apparent… (More)

- Kou-Yuan Huang, Liang-Chi Shen, Jiun-Der You
- 2015 International Joint Conference on Neural…
- 2015

In the multilayer perceptron (MLP), there was a theorem about the maximum number of separable regions (M) given the number of hidden nodes (H) in the input d-dimensional space. We propose a recurrence relation in the high dimensional space and prove the theorem using the expansion of recurrence relation instead of proof by induction. The MLP model has input… (More)

- Kuang-Fu Han, Chalmers M. Butler, Liang-Chi Shen, Helen Y. He, Mark A. Harris
- IEEE Trans. Geoscience and Remote Sensing
- 1991

- Kou-Yuan Huang, Kai-Ju Chen, Ming-Che Huang, Liang-Chi Shen
- IGARSS
- 2012

- Kou-Yuan Huang, Liang-Chi Shen, Chun-Yu Chen
- IGARSS
- 2008