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A Cotton Production Process Optimization Method Based on Big Data Hierarchical Clustering

A hierarchical clustering and production technology technology, applied in data processing application, prediction, calculation, etc., can solve the problems of reducing lint grade, mixed rolling, etc., and achieve the goal of improving cotton quality, wide application prospects, and improving the effect of impurity removal processing Effect

Active Publication Date: 2022-03-29
UNIV OF JINAN
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to use a single ginning mode for the impurity removal processing of cotton, or manually adjust it on the spot by operators only based on experience, resulting in mixed grades of seed cotton of different grades, and the phenomenon of mixed ginning is serious, reducing the grade of lint cotton, providing A cotton production process optimization method based on big data hierarchical clustering to solve the above technical problems

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  • A Cotton Production Process Optimization Method Based on Big Data Hierarchical Clustering
  • A Cotton Production Process Optimization Method Based on Big Data Hierarchical Clustering
  • A Cotton Production Process Optimization Method Based on Big Data Hierarchical Clustering

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Embodiment 1

[0070] A cotton production process optimization method based on hierarchical clustering of big data, data distribution statistics are carried out on the original data, and the method of correlation mapping is used to classify the types, and the change rules of each key production parameter are obtained, and the knowledge of the regularity hidden in the data is obtained. , through the adjustment and prediction of parameters to optimize the process flow, including the following steps:

[0071] S1: Data preprocessing is performed on the obtained production monitoring raw data; including:

[0072] S11: Perform data cleaning to eliminate redundant and conflicting data;

[0073] S12: Reduce the data scale, and repair the wrong and missing data at the same time; among them, repair the wrong and repeated cotton bale number, and fill in the blank attribute data in the cotton data; by filling the blank data, the data can be guaranteed. Stability, including:

[0074] If a large number ...

Embodiment 2

[0091] In the process of cotton processing and production, the data has the characteristics of typical process objects. The entire production process includes multiple related links or procedures before and after. The data acquisition interface is deployed in the entire cotton production and processing link, which can store real-time detection data. In the database, the production monitoring raw data obtained in the centralized database usually contains a large amount of noise data and wrong information, and the interaction relationship between the links cannot be directly reflected in the data, and has the characteristics of distribution, asynchronous and discrete. Directly used for big data processing, it is necessary to clean the data with disordered cotton bale numbers and a large number of missing attribute data, clean the data, remove noise, eliminate redundant and conflicting data, reduce the data scale, and at the same time repair the wrong and missing data to form inter...

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Abstract

The invention provides a cotton production process optimization method based on big data layered clustering, comprising the following steps: performing data preprocessing on the acquired production monitoring raw data; determining key parameters describing parameter attributes for the preprocessed raw data ; Perform numerical statistics on the determined key parameters to obtain distribution statistical attribute numerical distribution grouping; according to the numerical distribution grouping obtained in distribution statistics, each attribute data in the sample is mapped to each attribute grouping interval to form a new data set; determine Optimize the target and optimize the production process parameters. Combined with cotton processing process technology analysis. It can be used for analysis and adjustment of process parameters by enterprises. In order to optimize cotton production, improve cotton quality, and maintain enterprise production safety.

Description

technical field [0001] The invention relates to the technical field of process optimization algorithms, in particular to a cotton production process optimization method based on hierarchical clustering of big data. Background technique [0002] Among crops, cotton is an important strategic resource related to the national economy and people's livelihood. It has been widely used in industry, medical care and people's daily life. Cotton is mainly involved in agriculture and textile industry. It is the main pillar of agricultural economic development in cotton-producing areas, the key raw material for textile enterprises, and an important source of foreign exchange earnings from exports. It is valued by major cotton-producing countries in the world. [0003] Cotton plucked from mature highland barley is called seed cotton. The processed fiber of seed cotton becomes lint cotton. After growth and development, receipt, processing, transportation and other links, cotton contains a ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06
CPCG06Q10/04G06Q10/063
Inventor 李国昌杜韬曲守宁张宝国李卫涛张瑞牟国栋
Owner UNIV OF JINAN
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