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Agricultural feature information extraction method based on big data

A technology of feature information and extraction method, which is applied in the direction of knowledge expression, instrument, character and pattern recognition, etc., can solve the problem of poor utilization of nonlinear structural feature data, and facilitate analysis and evaluation, mining and analysis, and extraction more accurate effect

Inactive Publication Date: 2019-09-27
GUANGDONG KINGPOINT DATA SCI & TECH CO LTD
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a method for extracting agricultural feature information based on big data, which can avoid the problem that the existing feature extraction method cannot reflect the nonlinear structural characteristics of the data, and the problem of poor data utilization effect

Method used

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  • Agricultural feature information extraction method based on big data
  • Agricultural feature information extraction method based on big data
  • Agricultural feature information extraction method based on big data

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Embodiment

[0042] Such as figure 1 Shown: A method for extracting agricultural feature information based on big data, including the following steps:

[0043] S1: The step of establishing the attribute set, obtaining the agricultural attribute data, and establishing the knowledge system. The attribute data includes agricultural production data, soil quality data, meteorological and hydrological observation data, and the attribute set is established after collecting all the attribute data; the knowledge system is S=(U,A,V,f), U is the object set, and A is the attribute Set, V is the attribute value range, f is the mapping, and f reflects the value between the object sets.

[0044] S2: The attribute category clustering step, randomly select attribute data from the attribute set of the knowledge system as the initial attribute cluster center, establish the initial attribute category according to the initial attribute cluster center, and perform merging and separation operations on all the i...

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Abstract

The invention relates to the field of big data feature extraction, and provides an agricultural feature information extraction method based on big data for the problem that agricultural data is difficult to process, which comprises the following steps: an attribute set establishment step: obtaining agricultural attribute data, and establishing a knowledge system; an attribute class clustering step: establishing an initial attribute class according to the initial attribute clustering center, and performing combination and separation operation on all the initial attribute classes to obtain clustered attribute classes; a feature attribute calculation step: calculating the dependency degree of each attribute data in the integrated attribute category relative to other attribute data, and selecting the highest value of the dependency degree as a feature attribute value; and a feature attribute collection step: selecting and collecting feature attribute values of all attribute categories to obtain a feature attribute set. The problem that an existing feature extraction method cannot reflect nonlinear structure features of data, and consequently the data utilization effect is poor can be solved.

Description

technical field [0001] The invention relates to the field of big data feature extraction, in particular to a method for extracting agricultural feature information based on big data. Background technique [0002] Data is the basis and basis for decision-making, and agricultural data refers to various material data and energy data involved in people's agricultural production or agricultural economic activities. With the increasing computing power and the rapid development of environmental information data acquisition and analysis technology, the acquisition of large-scale agricultural data is more convenient and simpler than ever. [0003] Agricultural data are the basis for agricultural decision-making. However, agricultural big data includes agricultural spatial data such as agricultural production data, soil quality data, and meteorological and hydrological observation data. The data volume is huge and complex, which leads to difficulties in agricultural data management a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N5/02
CPCG06N5/022G06F18/23211G06F18/211G06F18/213
Inventor 简宋全赵轩秦于钦潘宇翔李青海张清瑞邹立斌赵梦思
Owner GUANGDONG KINGPOINT DATA SCI & TECH CO LTD
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