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...
Saved in:
Published in: | Applied mathematics and nonlinear sciences 2023-01, Vol.8 (1), p.749-756 |
---|---|
Main Authors: | , , , |
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 |