Check patentability & draft patents in minutes with Patsnap Eureka AI!

Optimization method of cotton production process based on hierarchical clustering of big data

A hierarchical clustering and production process technology, which is applied in the field of cotton production process optimization based on big data hierarchical clustering, can solve problems such as mixed rolling and lower lint grades

Active Publication Date: 2018-12-18
UNIV OF JINAN
View PDF4 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Optimization method of cotton production process based on hierarchical clustering of big data
  • Optimization method of cotton production process based on hierarchical clustering of big data
  • Optimization method of cotton production process based on hierarchical clustering of big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0070] A cotton production process optimization method based on hierarchical clustering of big data, which performs data distribution statistics on the original data, and uses the method of association mapping to divide the types, obtains the change law of each key production parameter, and obtains the regularity knowledge hidden in the data , optimizing the process flow by adjusting and predicting parameters, including the following steps:

[0071] S1: Perform data preprocessing on the acquired production monitoring raw data; including:

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

[0073] S12: Reduce the size of the data, and repair the wrong and missing data at the same time; among them, repair the wrong and repeated cotton bales, and fill 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 of attributes in the data are missing blanks, delet...

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. Data acquisition interfaces are deployed throughout the cotton production and processing links, which can store real-time detection data. In the database, the original production monitoring data obtained in the centralized database usually has a large amount of noise data and missing information, and the mutual influence relationship between links cannot be directly reflected in the data, and has the characteristics of distribution, asynchronous and discrete, which cannot Directly used for big data processing, it is necessary to clean the data with disordered cotton bales and a large number of missing attribute data to clean the data, remove noise, eliminate redundant and conflicting data, reduce the scale of data, and at the same time repair the wrong and missing data to form internal...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a cotton production process optimization method based on hierarchical clustering of big data, which comprises the following steps: data preprocessing is carried out on the obtained production monitoring original data; the key parameters describing the parameter attributes for the pre-processed raw data are determined; numerical statistics of the determined key parameters isused to obtain the numerical distribution grouping of the distribution statistical attributes. According to the numerical distribution grouping obtained from distribution statistics, the attribute data in the sample are mapped into each attribute grouping interval to form a new data set. The optimization objective is determined and the production process parameters are optimized. Cotton processingprocess analysis is combined. It can be used for the analysis and adjustment of process parameters so as to optimize cotton production, improve cotton quality and safeguard the production safety of enterprises.

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 big data hierarchical clustering. Background technique [0002] Among the crops, cotton is an important strategic resource related to the national economy and the people's livelihood, and has been widely used in industry, medical treatment and people's daily life. Cotton is mainly involved in the two major industries of agriculture and textiles. 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] The cotton picked from the mature barley is called seed cotton, and the processed fiber of seed cotton becomes lint cotton. After the process of growth and development, receiving, processing, ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
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
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com