Classifying method of crop data based on fuzzy C mean value utilizing improved gene expression programming

A data classification and expression technology, applied in the field of agricultural informatics, can solve problems such as failure to consider individual repetition and validity, unsatisfactory segmentation results, and no accuracy evaluation of clustering results.

Active Publication Date: 2016-08-31
ANHUI AGRICULTURAL UNIVERSITY
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Problems solved by technology

However, the literature "Gu Linglan. Effective Clustering Algorithms for Large Datasets [J]. Computer Engineering and Design, 2014, 35(6): 2183-2187." adopts GEP and FCM hybrid algorithm to carry out large data subsets Clustering, but the algorithm does not take into account the repetition and validity of individuals, and does not evaluate the accuracy of the clusteri

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  • Classifying method of crop data based on fuzzy C mean value utilizing improved gene expression programming
  • Classifying method of crop data based on fuzzy C mean value utilizing improved gene expression programming
  • Classifying method of crop data based on fuzzy C mean value utilizing improved gene expression programming

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Embodiment Construction

[0063] In this embodiment, the process of an improved gene expression programming-fuzzy C-means crop data classification method is as follows: combine the Iris data set in the UCI database to describe the implementation of the present invention in detail, figure 1 It is an overall flow chart, and the implementation process is realized by MATLAB programming.

[0064] Step 1: Record the crop data set to be classified as X={x 1 ,x 2 ,...,x i ,...,x n};x i Indicates the i-th crop data; and x i ={x i1 ,x i2 ,...,x ik ,...,x ip};x ik Indicates the k-th attribute of the i-th crop data; 1≤i≤n; 1≤k≤p; the Iris data set is recorded as X, since the Iris data set is divided into 150 sets of data of Setosa, Versicolour and Virginica, and Each set of data is described by four attributes of petal length, width and sepal length and width, so X={x 1 ,x 2 ,...,x i ,...,x 150}, and x i ={x i1 ,...,x ik ,...,x i4}. Combine below figure 2 The self-defined distance measurement ...

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Abstract

The invention discloses a classifying method of crop data based on fuzzy C mean value utilizing improved gene expression programming. The method comprises following steps: using customized similarity to measure a calculating formula and combining with information entropy to calculate weight vector of data attribute; and using a weighed distance calculating formula to replace conventional Euclidean distance and combining a gene expression program with a fuzzy C mean value algorithm to solve a optimal cluster center for classification of crop data. The classifying method of crop data based on fuzzy C mean value utilizing improved gene expression programming has following beneficial effects: on one hand, distance between crop data can be measured so that accuracy of the classification result is increased; and on the other hand, the optimal classification result can be obtained by lower iteration frequency.

Description

technical field [0001] The invention relates to the field of agricultural informatics, in particular to an improved gene expression programming-fuzzy C-mean crop data classification method, which is suitable for the classification or identification of various crop information whose features are described by real numbers. Background technique [0002] The classification or identification of crop data samples is of great significance to crop science research and agricultural production management. Clustering is the main method to achieve classification and identification, and among many clustering algorithms, fuzzy C-means clustering (FCM) "Dunn J C.Afuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters[ J].1973,3(3):32-57” is widely used because of its simple algorithm and fast convergence speed, but the Euclidean distance cannot be used to measure the distance of multidimensional data, and it is easy to fall into local extremum, so th...

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Application Information

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IPC IPC(8): G06F19/24
CPCG16B40/00
Inventor 江朝晖李婷婷闵文芳饶元马友华
Owner ANHUI AGRICULTURAL UNIVERSITY
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