2018年APMCM亚太地区大学生数学建模竞赛 B题 Talents and Urban Development

2018年APMCM亚太地区大学生数学建模竞赛 B题

Talents and Urban Development

摘要部分：
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 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

1 Introduce
1.1Problem 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.

1.2Restatement 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.

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 the use of analytic hierarchy process (AHP) to establish a model for quantifying the diversity of college students’ employment choices.

部分建模求解过程：

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