This study is to discuss the application of computer simulation technology (CST) in ideological and political teaching (I&P teaching) and promote the reform of ideological and political teaching in the era of big data. In this study, a set of computer simulation system for I&P teaching is constructed, and targeted research is launched from this. The main research results are as follows: Firstly, a computer simulation system for ideological and political teaching is designed based on the Apriori algorithm and other theoretical foundations. The system includes a user layer, a business layer, and a data layer. The main modules of the system include the website (WEB) server, Mail server, and user terminal. Secondly, the system is tested accordingly. The performance test and function test results reveal that when the maximum number of concurrent users is 500, the system can run normally with the maximum response time of 6.6 s and the good condition of various functions, so it can meet the actual needs of universities. Finally, in comparison with the conventional I&P courses, the proposed system can effectively improve the attitudes towards I&P courses of students, increase their satisfaction and acceptance of I&P teaching, and contribute to the mastery of knowledge. Therefore, the designed system can realize a good actual teaching effect and show reliable application value. In addition, the results of this study can provide scientific and effective reference materials for subsequent research on I&P teaching.

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A new definition method of ramp sections is proposed. Firstly, the extreme point extraction algorithm is designed. The results show that the extreme value sequence can not only achieve data compression, but also provide data for the definition of the ramp section. Secondly, several typical recognition methods of wind power ramp are compared. The results show that the "event" as the unit of analysis is not possible to effectively distinguish between the ramp process and the transient process in the ramp event, which causes the prediction error of the ramp duration. Also, the non-representation of the threshold setting will also cause errors in the prediction and recognition of complex ramp events. In this paper, the concepts of ramp section, slope point(SP) and stagnation point(STP) are introduced to realize the segmentation processing and analysis of ramp events, which can effectively distinguish the ramp process and transient process in ramp events and provide a strong guarantee for the accurate prediction of the ramp duration. In addition, the mathematical statistics method of cumulative probability is utilized to discuss the threshold setting. The ramp situation of a wind farm in Yunnan in 2014 is further identified and analyzed, and on this basis, the characteristics of the ramp sections are investigated, whose results show the applicability of this new definition.

With the advance in the social economy, people’s life has undergone great changes, which brings additional enrichment to people’s lives and also greatly enhances their productivity. The changes brought about by this technology also affect people’s thinking. The ideological and political education in colleges and universities has also ushered in an opportunity for change. The goal of this paper is to investigate the implementation of the K -means clustering algorithm applied in a 5G-based intellectual and technical teaching database in high schools. The results of the demonstration indicate that 29 students in the laboratory group identified more with the work carried out by the school in administrative and practical teaching than the 16 students in the traditional control group, which met everyone’s needs for growth. The superiority of the K -means agglomerative categorization algorithm used for the institution’s educational resource base was verified.