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

机译:基于模拟退火和神经网络算法的数据拟合的最小绝对积分方法

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摘要

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.
机译:与数据拟合相关的方法很多,每种方法都有其独特的功能。本文讨论了在积分准则下数据拟合函数的方法。由于估计拟合参数复杂,本文将模拟退火算法与神经网络算法结合起来,用神经网络算法求解积分,用模拟退火算法求解未知参数。通过对中国城乡居民家庭人均消费支出的模拟计算,证明了模拟退火算法与神经网络算法相结合的方法在最小绝对积分数据拟合的新方法方面具有较强的可靠性和准确性。

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