Loading…

Employment and Professional Education Training System of College Graduates Based on the Law of Large Numbers

The article uses the law of large numbers to analyze and uses the equivalence relationship on the data set to measure the degree of uncertainty of knowledge. In this way, we can analyze the relationship between the employment of graduates from colleges and universities and professional education tra...

Full description

Saved in:
Bibliographic Details
Published in:Applied mathematics and nonlinear sciences 2023-01, Vol.8 (1), p.749-756
Main Authors: Shang, Zhe, Wang, PengYuan, Ebrahim, Ragab, Rashid, Audil
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c358t-cee2ac59723f8df62521a8449038bd1fa8043216ed9030e1c6d1222d4da9799e3
container_end_page 756
container_issue 1
container_start_page 749
container_title Applied mathematics and nonlinear sciences
container_volume 8
creator Shang, Zhe
Wang, PengYuan
Ebrahim, Ragab
Rashid, Audil
description The article uses the law of large numbers to analyze and uses the equivalence relationship on the data set to measure the degree of uncertainty of knowledge. In this way, we can analyze the relationship between the employment of graduates from colleges and universities and professional education training. The article describes several collective category models of college graduates’ employment rate and enrollment scale. This can provide an important theoretical reference for solving the actual social problems related to employment and enrollment.
doi_str_mv 10.2478/amns.2022.2.0062
format article
fullrecord <record><control><sourceid>walterdegruyter_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_5151d379fa264879b5591eaa2d2f06e9</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_5151d379fa264879b5591eaa2d2f06e9</doaj_id><sourcerecordid>10_2478_amns_2022_2_006281749</sourcerecordid><originalsourceid>FETCH-LOGICAL-c358t-cee2ac59723f8df62521a8449038bd1fa8043216ed9030e1c6d1222d4da9799e3</originalsourceid><addsrcrecordid>eNp1kDFv2zAQhYWiARo42TvyD9gljxRFDh1Sw3EDGGmBpDNxFo-uDEk0SAmG_32lOiiydLqHw3vf8BXFZ8FXoCrzBbs-r4ADrGDFuYYPxS0opZZGl_rju_ypuM_5yDkHKaTWcFu0m-7UxktH_cCw9-xnioFybmKPLdv4scZhyuw1YdM3_YG9XPJAHYuBrWPb0oHYNqEfcaDMvmEmz6b28JvYDs9za4dp6jyP3Z5SvituAraZ7t_uovj1uHldf1_ufmyf1g-7ZS1LMyxrIsC6tBXIYHzQUIJAo5Tl0uy9CGi4kiA0-enDSdTaCwDwyqOtrCW5KJ6uXB_x6E6p6TBdXMTG_X3EdHCYhqZuyZWiFF5WNiBoZSq7L0srCBE8BK7JTix-ZdUp5pwo_OMJ7mb5bpbvZvkO3Cx_mny9Ts7YDpQ8HdJ4mYI7xjFNXvN_p0ZUyso_uGeMUQ</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Employment and Professional Education Training System of College Graduates Based on the Law of Large Numbers</title><source>DOAJ Directory of Open Access Journals</source><creator>Shang, Zhe ; Wang, PengYuan ; Ebrahim, Ragab ; Rashid, Audil</creator><creatorcontrib>Shang, Zhe ; Wang, PengYuan ; Ebrahim, Ragab ; Rashid, Audil</creatorcontrib><description>The article uses the law of large numbers to analyze and uses the equivalence relationship on the data set to measure the degree of uncertainty of knowledge. In this way, we can analyze the relationship between the employment of graduates from colleges and universities and professional education training. The article describes several collective category models of college graduates’ employment rate and enrollment scale. This can provide an important theoretical reference for solving the actual social problems related to employment and enrollment.</description><identifier>ISSN: 2444-8656</identifier><identifier>EISSN: 2444-8656</identifier><identifier>DOI: 10.2478/amns.2022.2.0062</identifier><language>eng</language><publisher>Sciendo</publisher><subject>03E20 ; Employment rate ; Evaluation model ; Law of large numbers ; Professional education ; Set category</subject><ispartof>Applied mathematics and nonlinear sciences, 2023-01, Vol.8 (1), p.749-756</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c358t-cee2ac59723f8df62521a8449038bd1fa8043216ed9030e1c6d1222d4da9799e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,2096,27901,27902</link.rule.ids></links><search><creatorcontrib>Shang, Zhe</creatorcontrib><creatorcontrib>Wang, PengYuan</creatorcontrib><creatorcontrib>Ebrahim, Ragab</creatorcontrib><creatorcontrib>Rashid, Audil</creatorcontrib><title>Employment and Professional Education Training System of College Graduates Based on the Law of Large Numbers</title><title>Applied mathematics and nonlinear sciences</title><description>The article uses the law of large numbers to analyze and uses the equivalence relationship on the data set to measure the degree of uncertainty of knowledge. In this way, we can analyze the relationship between the employment of graduates from colleges and universities and professional education training. The article describes several collective category models of college graduates’ employment rate and enrollment scale. This can provide an important theoretical reference for solving the actual social problems related to employment and enrollment.</description><subject>03E20</subject><subject>Employment rate</subject><subject>Evaluation model</subject><subject>Law of large numbers</subject><subject>Professional education</subject><subject>Set category</subject><issn>2444-8656</issn><issn>2444-8656</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp1kDFv2zAQhYWiARo42TvyD9gljxRFDh1Sw3EDGGmBpDNxFo-uDEk0SAmG_32lOiiydLqHw3vf8BXFZ8FXoCrzBbs-r4ADrGDFuYYPxS0opZZGl_rju_ypuM_5yDkHKaTWcFu0m-7UxktH_cCw9-xnioFybmKPLdv4scZhyuw1YdM3_YG9XPJAHYuBrWPb0oHYNqEfcaDMvmEmz6b28JvYDs9za4dp6jyP3Z5SvituAraZ7t_uovj1uHldf1_ufmyf1g-7ZS1LMyxrIsC6tBXIYHzQUIJAo5Tl0uy9CGi4kiA0-enDSdTaCwDwyqOtrCW5KJ6uXB_x6E6p6TBdXMTG_X3EdHCYhqZuyZWiFF5WNiBoZSq7L0srCBE8BK7JTix-ZdUp5pwo_OMJ7mb5bpbvZvkO3Cx_mny9Ts7YDpQ8HdJ4mYI7xjFNXvN_p0ZUyso_uGeMUQ</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Shang, Zhe</creator><creator>Wang, PengYuan</creator><creator>Ebrahim, Ragab</creator><creator>Rashid, Audil</creator><general>Sciendo</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20230101</creationdate><title>Employment and Professional Education Training System of College Graduates Based on the Law of Large Numbers</title><author>Shang, Zhe ; Wang, PengYuan ; Ebrahim, Ragab ; Rashid, Audil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-cee2ac59723f8df62521a8449038bd1fa8043216ed9030e1c6d1222d4da9799e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>03E20</topic><topic>Employment rate</topic><topic>Evaluation model</topic><topic>Law of large numbers</topic><topic>Professional education</topic><topic>Set category</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shang, Zhe</creatorcontrib><creatorcontrib>Wang, PengYuan</creatorcontrib><creatorcontrib>Ebrahim, Ragab</creatorcontrib><creatorcontrib>Rashid, Audil</creatorcontrib><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Applied mathematics and nonlinear sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shang, Zhe</au><au>Wang, PengYuan</au><au>Ebrahim, Ragab</au><au>Rashid, Audil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Employment and Professional Education Training System of College Graduates Based on the Law of Large Numbers</atitle><jtitle>Applied mathematics and nonlinear sciences</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>8</volume><issue>1</issue><spage>749</spage><epage>756</epage><pages>749-756</pages><issn>2444-8656</issn><eissn>2444-8656</eissn><abstract>The article uses the law of large numbers to analyze and uses the equivalence relationship on the data set to measure the degree of uncertainty of knowledge. In this way, we can analyze the relationship between the employment of graduates from colleges and universities and professional education training. The article describes several collective category models of college graduates’ employment rate and enrollment scale. This can provide an important theoretical reference for solving the actual social problems related to employment and enrollment.</abstract><pub>Sciendo</pub><doi>10.2478/amns.2022.2.0062</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2444-8656
ispartof Applied mathematics and nonlinear sciences, 2023-01, Vol.8 (1), p.749-756
issn 2444-8656
2444-8656
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_5151d379fa264879b5591eaa2d2f06e9
source DOAJ Directory of Open Access Journals
subjects 03E20
Employment rate
Evaluation model
Law of large numbers
Professional education
Set category
title Employment and Professional Education Training System of College Graduates Based on the Law of Large Numbers
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-13T06%3A17%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-walterdegruyter_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Employment%20and%20Professional%20Education%20Training%20System%20of%20College%20Graduates%20Based%20on%20the%20Law%20of%20Large%20Numbers&rft.jtitle=Applied%20mathematics%20and%20nonlinear%20sciences&rft.au=Shang,%20Zhe&rft.date=2023-01-01&rft.volume=8&rft.issue=1&rft.spage=749&rft.epage=756&rft.pages=749-756&rft.issn=2444-8656&rft.eissn=2444-8656&rft_id=info:doi/10.2478/amns.2022.2.0062&rft_dat=%3Cwalterdegruyter_doaj_%3E10_2478_amns_2022_2_006281749%3C/walterdegruyter_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c358t-cee2ac59723f8df62521a8449038bd1fa8043216ed9030e1c6d1222d4da9799e3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true