Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network

Maolin Cheng

doi:doi:10.11648/j.mcs.20160103.15

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Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network

Maolin Cheng

Published in Mathematics and Computer Science (Volume 1, Issue 3)

Received: 5 September 2016 Accepted: 18 September 2016 Published: 9 October 2016

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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.

Published in	Mathematics and Computer Science (Volume 1, Issue 3)
DOI	10.11648/j.mcs.20160103.15
Page(s)	61-65
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Data Fitting, Simulated Annealing, Neural Network, Algorithm, Least Absolute Integral Method

References

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Maolin Cheng. (2016). Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network. Mathematics and Computer Science, 1(3), 61-65. https://doi.org/10.11648/j.mcs.20160103.15

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ACS Style

Maolin Cheng. Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network. Math. Comput. Sci. 2016, 1(3), 61-65. doi: 10.11648/j.mcs.20160103.15

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AMA Style

Maolin Cheng. Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network. Math Comput Sci. 2016;1(3):61-65. doi: 10.11648/j.mcs.20160103.15

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@article{10.11648/j.mcs.20160103.15,
  author = {Maolin Cheng},
  title = {Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network},
  journal = {Mathematics and Computer Science},
  volume = {1},
  number = {3},
  pages = {61-65},
  doi = {10.11648/j.mcs.20160103.15},
  url = {https://doi.org/10.11648/j.mcs.20160103.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mcs.20160103.15},
  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.},
 year = {2016}
}

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TY  - JOUR
T1  - Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network
AU  - Maolin Cheng
Y1  - 2016/10/09
PY  - 2016
N1  - https://doi.org/10.11648/j.mcs.20160103.15
DO  - 10.11648/j.mcs.20160103.15
T2  - Mathematics and Computer Science
JF  - Mathematics and Computer Science
JO  - Mathematics and Computer Science
SP  - 61
EP  - 65
PB  - Science Publishing Group
SN  - 2575-6028
UR  - https://doi.org/10.11648/j.mcs.20160103.15
AB  - 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.
VL  - 1
IS  - 3
ER  -

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Author Information

Maolin Cheng

School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, China

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APA Style

Maolin Cheng. (2016). Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network. Mathematics and Computer Science, 1(3), 61-65. https://doi.org/10.11648/j.mcs.20160103.15

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ACS Style

Maolin Cheng. Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network. Math. Comput. Sci. 2016, 1(3), 61-65. doi: 10.11648/j.mcs.20160103.15

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AMA Style

Maolin Cheng. Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network. Math Comput Sci. 2016;1(3):61-65. doi: 10.11648/j.mcs.20160103.15

Copy | Download

@article{10.11648/j.mcs.20160103.15,
  author = {Maolin Cheng},
  title = {Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network},
  journal = {Mathematics and Computer Science},
  volume = {1},
  number = {3},
  pages = {61-65},
  doi = {10.11648/j.mcs.20160103.15},
  url = {https://doi.org/10.11648/j.mcs.20160103.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mcs.20160103.15},
  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.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Least Absolute Integral Method of Data Fitting Based on Algorithm of Simulated Annealing and Neural Network
AU  - Maolin Cheng
Y1  - 2016/10/09
PY  - 2016
N1  - https://doi.org/10.11648/j.mcs.20160103.15
DO  - 10.11648/j.mcs.20160103.15
T2  - Mathematics and Computer Science
JF  - Mathematics and Computer Science
JO  - Mathematics and Computer Science
SP  - 61
EP  - 65
PB  - Science Publishing Group
SN  - 2575-6028
UR  - https://doi.org/10.11648/j.mcs.20160103.15
AB  - 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.
VL  - 1
IS  - 3
ER  -

Copy | Download