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2018年APMCM亚太地区大学生数学建模竞赛 B题 Talents and Urban Development
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2018年APMCM亚太地区大学生数学建模竞赛 B题 Talents and Urban Development 完整论文
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Team B81364
2018 APMCM summary sheet
Urban Development and Talent Demand
Summary
In recent years, attracting talents to develop cities is one of the hot spots in many cities.
In the process of talent demand, mainly through the Internet recruitment, based on A city
talent demand data, to solve the following problems.
For the first problem, this paper makes statistical analysis on the quantity of talent
demand, the quantity of job demand, the number of job types, the educational background and
so on, and makes full use of the data given in the annex. Through analysis, it is found that the
demand for talents in A city is characterized by the decrease of total demand, the increase
of post types and the increase of educational requirements.
For the second question , making first three years of existing data demand trends,
demand change and the close time, using the SPSS software analysis and establish the talent
demand data of the three years since the correlation ARIMA to fitting of talent demand, draw
a Stationary R-squared 0.840, the fitting effect is good. Therefore, we forecast the future
talent demand based on the ARIMA model. First, we got the change trend of the next year.
After iterative prediction, we finally got the change trend of the talent demand of city A in the
next three years.
For the third question, the data of A city is cleaned, considering the attached data is the
largest city employment market in A city, the industry proportion information of A city is
analyzed and compared with the urban industrial structure of 297 cities in China. It is found
that the tertiary industry in A city is relatively developed, which is manifested in the top five
industries in finance, tourism, sales, catering and high-tech industries. It is similar to the
industrial structure of Beijing, similar to the financial center and political center. The
Team Number : 81364
Problem Chosen : B
Team B81364
status of a cultural centre By using the ARIMA method in question 2 to forecast the
high-tech industry, it is known that its job demand growth rate is slowing down, and its
high-tech industry alone is developing. A slowdown in growth, increased competition in the
industry and increased demand for high-end talent
For the fourth question, in view of the factors affecting college students' employment
choices, the AHP is used to model and calculate, taking into account income, stability,
personal value and other factors as the criterion layer, starting a business, civil servants, etc.
After comprehensive calculation, the consistency is very good. It is concluded that college
students tend to choose employment for civil servants and enterprises. According to this
model, some suggestions on A city development and talent attraction are put forward.
For the fifth question, we evaluated the computer science and technology major we
studied, analyzed the employment situation of the computer major in recent years, and
combined the training plan and curriculum system of our school. This paper puts forward the
advantages and disadvantages of computer major in the present employment situation, and
puts forward some solutions which are more reasonable and accord with the present
employment situation.
Keywords: Statistical Analysis、ARIMA、Analytic、Hierarchy Process,、Talent demand、
SPSS、Employment Analysis
Team B81364
Contents
1 Introduce................................................................................................................................................. 1
1.1 Problem Background................................................................................................................... 1
1.2 Restatement of the Problem.........................................................................................................1
2 Problem Analysis.................................................................................................................................... 2
2.1 Analysis of Problem 1................................................................................................................. 2
2.2 Analysis of Problem 2................................................................................................................. 2
2.3 Analysis of Problem 3................................................................................................................. 2
2.4 Analysis of Problem 4................................................................................................................. 2
3 Model Assumptions................................................................................................................................ 3
4 Notation...................................................................................................................................................3
5 Modeling Establishment and Solution.................................................................................................... 3
5.1 Model establishment and solution of problem 1......................................................................... 3
5.1.1 Talent demand analysis.................................................................................................... 3
5.1.2 Occupational demand analysis......................................................................................... 8
5.1.3 Educational background analysis..................................................................................... 9
5.2 Model establishment and solution of problem 2....................................................................... 10
5.2.1 Establish forecast model.................................................................................................10
5.2.2 Validate ARIMA Model.................................................................................................12
5.2.3 ARIMA model was used for prediction......................................................................... 14
5.3 Model establishment and solution of problem 3....................................................................... 16
5.4 Model establishment and solution of problem 4....................................................................... 21
5.4.1 Modeling by using Analytic hierarchy process.............................................................. 21
5.4.2 Using AHP to solve the Model.......................................................................................22
5.4.3 Suggestions on City Development and Talent introduction in A City........................... 25
5.5 Model establishment and solution of problem 5....................................................................... 26
6 Advantages and Disadvantages.............................................................................................................27
6.1 Advantages................................................................................................................................ 27
6.2 Disadvantages............................................................................................................................27
References....................................................................................................................................... 28
Appendix......................................................................................................................................... 28
Team B81364 Page 1 of 35
1 Introduce
1.1 Problem Background
Inviting wits and attracting talents is one of the highlights for many cities over the past couple
of years. Beijing, Shanghai, Wuhan, Chengdu, Xi'an, and Shenzhen are actually competing
for talents with various attractive policies. Talents represent the motive power for the
innovative development of cities because of their ability to learn better skills, make better
products, and master better management methods within a shorter time. Talents are the major
driver for urban innovation diffusion, since innovation diffusion is achieved by promoting
new processes and technologies through high-quality talents are the media. In cities today,
talents are recruited via the internet,on-campus job fairs, and open recruitment events in
addition to local talent markets.
1.2 Restatement of the Problem
In order to study the talent demand, the following problems need to be solved around
the historical talent demand data of A city and other necessary data:
Analysis of city A’s job demand,the desired profession, and the desired educational
background based on annex data to.
Combined with the employment situation of students and the necessary data, to establish
a model of talent demand in A city . Forecast A City's Talent demand in the next three
years
Try to infer a city's administrative category, geographical location, economic status.
Using the talent demand model of A city to analyze the development of high-tech
industry in A city.
To establish a model according to the diverse employment choices of college students,
and to provide suggestions for the development of A city.
According to the results of the analysis and the current market for talent demand. Write a
letter to the school. To the talented person training, the university student development
and so on aspect provides own opinion.
Team B81364 Page 2 of 35
2 Problem Analysis
2.1 Analysis of Problem 1
The attachment "data of A city's employment market" contains information such as total
market demands, market posts and education background of the position.There are three
requirements for problem 1: job demand,the desired profession, and the desired educational
background. The correlation among the three can be analyzed by statistical and visualization
methods such as line chart and pie chart to analyze the talent demand of A city.
2.2 Analysis of Problem 2
For question two, we are required to predict the potential talent demand of A city in the next
three years through the data attached to the talent market of A city. For the prediction of talent
demand, we can first determine whether we can use the time series model to predict by testing
the autocorrelation and autocorrelation coefficient. Then, ARIMA model was used to
iteratively predict the employment demand in the next three years year by year based on the
existing three-year data.
2.3 Analysis of Problem 3
According to the forecast data and statistical results of question 2, it is found that the size of A
city is large. This paper compares the employment data of 297 cities in China in the past 10
years with that of A city. Through the type of its industrial structure to find its close to the city.
Then the ARIMA method used in question 2 is used to predict the future job demand of city A
to infer the development of high and new technology industry in city A.
2.4 Analysis of Problem 4
The employment choice of college students tends to be diversified with the development of
society.In order to build a model to quantify the employment choice of college students, the
factors influencing the employment choice of college students are first considered, including
income, self-value, stability, difficulty, and life security [1].Second, consider the more popular
employment methods: entrepreneurship, admission (domestic admission, study abroad), civil
servants, enterprise employment.Based on the above analysis, this problem is very suitable for
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