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A Genetic Programming Classification Method Based on Geometric Semantics

A technology of genetic programming and classification method, which is applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problems of low classification accuracy, early convergence, and high classification accuracy, and achieve the effect of high accuracy

Active Publication Date: 2018-08-28
HOHAI UNIV
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Problems solved by technology

[0003] In order to solve the above defects and deficiencies in the prior art, the present invention provides a genetic programming classification method based on geometric semantics, which overcomes the problems of premature convergence and low classification accuracy in the existing genetic programming algorithm. High accuracy, and individual formulas can be stored

Method used

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  • A Genetic Programming Classification Method Based on Geometric Semantics
  • A Genetic Programming Classification Method Based on Geometric Semantics
  • A Genetic Programming Classification Method Based on Geometric Semantics

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Embodiment

[0067] In order to better illustrate the technical effect of the present invention, the classification of slope stability and the prediction of safety factor are used for further illustration.

[0068] The collected slope data are shown in Table 1:

[0069] Table 1 Experimental data set

[0070]

[0071]

[0072] Among them, the bulk density (γ), cohesion (c), internal friction angle (Φ), slope angle (β), slope height (H), and pore pressure ratio (ru) are used as input variables, and the output variable is slope Stable state (S), when it is 1, it is stable, when it is -1, it is unstable, and S1 indicates the stable state of the slope. Samples 1-40 are used as the training set, and samples 41-52 are used as the test set. In the calculation process of the present invention, the number of genetic individuals is set to 500, and the number of genetic algebra is set to 50. After calculation, the predicted values ​​of slope stability and safety factor in the training set and...

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Abstract

The invention provides a genetic programming classification method based on geometric semantics. A training process and a prediction process are separated, so as to complete classification of tested samples; the training process comprises the steps of: solving an optimal individual through the geometric semantics, extracting a classifier formula of the optimal individual, and storing the classifier formula of the optimal individual in a magnetic disk; the prediction process comprises the steps of: invoking the classifier formula, which is stored in the magnetic disk, of the optimal individual, recovering the classifier formula through loading and calculation, and outputting classification results according to the classifier formula, so as to classify a plurality of individuals. The problems of too early convergence, low classification accuracy and the like of an existing genetic programming algorithm are solved, the classification accuracy is high, and the individual formula can be stored.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, and in particular relates to a genetic programming classification method based on geometric semantics. Background technique [0002] Genetic algorithm is the most mature algorithm among evolutionary algorithms. Since it was proposed by Professor Holland, it has been widely used in industrial technology and has become a key technology in modern intelligent computing because it is a general algorithm. On the basis of genetic algorithm, American scholar Koza proposed genetic programming algorithm, which expresses the characteristics of the problem through layered tree structure. According to the evolution of genetic algorithm, genetic programming algorithm has wider applicability than genetic algorithm, because of its versatility and It has good robustness and strong search ability, and is widely used in artificial intelligence, structural optimization design, and complex system anal...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
Inventor 许军才任青文张卫东沈振中
Owner HOHAI UNIV
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