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Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network
Mathematics and Computer Science
Volume 1, Issue 3, September 2016, Pages: 61-65
Received: Sep. 5, 2016; Accepted: Sep. 18, 2016; Published: Oct. 9, 2016
Author
Maolin Cheng, School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, China
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Abstract
There are many methods related to data fitting, and each method has its distinctive features. The article discusses the method of data fitting function under integral criterion. Since the estimate fitting parameters are complicated, the article combines algorithm of simulated annealing and neural network algorithm to solve the integral with neural network algorithm and solve the unknown parameters with simulated annealing algorithm. By case analog computation of household per capita consumption expenditure of urban and the rural residents in China, it proves that the combination of simulated annealing algorithm and neural network algorithm has strong reliability and high accuracy in terms of new method for least absolute integral data fitting.
Keywords
Data Fitting, Simulated Annealing, Neural Network, Algorithm, Least Absolute Integral Method
Maolin Cheng, Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network, Mathematics and Computer Science. Vol. 1, No. 3, 2016, pp. 61-65. doi: 10.11648/j.mcs.20160103.15
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