Research of Oilfield Production Forecast Based on Least Squares Fitting and Improved BP Neural Network

2013 ◽  
Vol 333-335 ◽  
pp. 1456-1460 ◽  
Author(s):  
Wen Bo Na ◽  
Zhi Wei Su ◽  
Ping Zhang

A new method which is least squares fitting combined with improved BP neural network based on LM algorithm was put forward. In order to overcome the weak points that easy to fall into local minimum, slow convergence of traditional BP neural network, we use LM algorithm to improve it. Least-squares curve fitting can be used to reflect the overall trend of the data changes, so we adopted least squares method firstly to make curve fitting for sample data firstly. Then, we corrected the fitting error by the improved BP Neural Network which has the advantages that reflecting external factors. Finally, the fitted values and error correction values were added to get oilfield production forecast. The results show that the oilfield production forecast error is significantly lower than the single curve fitting, BP Neural Network or LMBP.

2013 ◽  
Vol 303-306 ◽  
pp. 1543-1546 ◽  
Author(s):  
Xiu Cai Guo ◽  
Sai Hua Shang

In order to solve the practical application problem, which traditional neural network takes too long and compute complexly, on the basis of the LM algorithm, combined with mathematical optimization theory, identify the three convergence Improved LM algorithm applied to BP neural network , that improved LMBP algorithm. Simulation results show that the improved LMBP algorithm in convergence time and goodness of fit both have better results, and the algorithm is general and can be produced by obtaining national sample of various scenarios, using the algorithm to predict, to better guidance on production.


2015 ◽  
Vol 713-715 ◽  
pp. 1627-1630
Author(s):  
Hong Qin Zhang ◽  
Lai Bin Gao

Based on statistical data of National Statistical Bureau of China, and given the least-squares fitting of Legendre polynomial, the data of total energy consumption from 1978 to 2012 is analyzed by least squares method and Legendre polynomial least squares method respectively. The results showed that Legendre polynomial least squares fitting method is excellent and the data of total energy consumption from 2013 to 2016 is predicted by this method.


1952 ◽  
Vol 5 (2) ◽  
pp. 238
Author(s):  
PG Guest

A method of fitting polynomials is described in which the "normal" equations are obtained much more rapidly than the corresponding equations in the least-squares method. Efficiencies are found to be about 90 per cent. The method is illustrated by an example.


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