Big data in the modern science and technology and social activities play an important role, on the one hand, a large number of new applications and technology into our lives, in the use of these new technologies to produce a large amount of data, on the other hand, big data as one of the most important digital assets, many of the development of new technologies also rely on large data as support. This paper focuses on the research and application of big data mining technology in blockchain computing. Firstly, this paper extracts the corresponding transaction data according to the Bitcoin address and constructs the transaction features to get the Bitcoin data set. Then, the data features are processed. Then, three algorithm models, SVM, Adaboost and Random Forest, are selected to model and analyze the preprocessed data combined with different sampling strategies. According to the comprehensive performance of the model and its shortcomings, the model is selected and improved.

The network data algorithm on account of association can effectively describe the development process of historical data and predict the development trend of data. Draw support from the corresponding data algorithm to ameliorate the mining efficiency and execution efficiency of association, more users pay more attention to the rules, so it has important research and utilization value. On account of this, this paper first analyzes the concept and mining process of data association, then studies the mining algorithm of data association, and finally gives the structure and utilization effect of cyber data algorithm on account of association. This research focuses on developing network data algorithms based on association rules. Association rules are widely used in data mining to identify patterns and relationships between variables. In the context of network data, association rules can be used to identify relationships between nodes or entities in a network. The proposed algorithms leverage association rules to identify important nodes in a network and to uncover hidden patterns and relationships between nodes. The research also explores the performance of the algorithms in different network structures and data scenarios. The results of this research have the potential to improve the understanding and analysis of network data, which can be applied in various fields, including social network analysis, transportation network analysis, and bioinformatics.

The purpose of this study is to compare the 3 forecasting methods Linear Regression, Exponential Smoothing and Weighted Moving Average based on the smallest error value or close to zero. From the results of this study, the Linear Regression method was obtained as the correct method with a predicted value of 502 students, the smallest error value was MAD 27.83, MSE 1152.1 MAPE 8.1%. The Tracking Signal value moves between 1 and -1, the movement is within the control limits of the tracking signal standard deviation distribution 4 and -4, meaning that the method is correct. The Moving Range value moves between 68 and -46, this value is within the MR control limits of 117.83 and -117.83, this result shows that this means that this method has been tested for truth and can be accepted as well. Thus, indicating that the Linear Regression method as a forecasting method is appropriate and acceptable as a basis for future decision making. The level of accuracy of the error and the value in control shows that there is a time series data relationship between the x variable, namely time, and the variable y, namely actual data. In addition, it produces trending data movement patterns, meaning that data movements experience a significant increase over a long period of time or for 7 periods.

In order to solve the serious problem that the injected water channeling is serious and water flooding effect is getting worse in Ansai low permeability fractured reservoir. Developed the gelling movable gel profile control displacement-agent RD which Can control the gel time and the strength. Select out the surfactant XSY-1 that can reduce water interfacial tension to ultra-low and can significantly improve oil displacement efficiency. Designed five group profiling experiments on parallel cores, optimized movable frozen rubber slug of surfactant slug best combination of 0.2 of the PV profile control agent add 0.40 PV surfactant, compared with the water flooding ways to enhance oil recovery of 22.5％ . Adjustable drive combined with technology is the effective way to improve the Ansai low permeability fractured reservoir water flooding effect.

After decades of research by researchers, there have been many mature algorithms and systems that can meet the requirements for the application of computer vision algorithms in many fields. There are applications of computer algorithms in many industries, such as car navigation, video detection, industrial production and other industries. Most industries have synchronization requirements in terms of time, that is, real-time. Because of the limitation on the amount of calculation, many realtime vision systems will use the local window algorithm, but the image quality generated by the local algorithm and the image quality generated by the global algorithm have a large gap. According to the latest research results, if you use precisely adjusted matching calculation and collection methods, the local algorithm is as good as the global algorithm in terms of matching rate. This article mainly takes UAV as the research object, and studies the UAV's processing function of graphics and image based on computer vision algorithm. The research content mainly includes the single passage of the UAV in different environments of straight lines, corners, and slopes, and the passage of the UAV in the overall process. Through the application of computer vision algorithms in the UAV's graphics and image processing process, the experimental data is analyzed and the corresponding conclusions are drawn.

The stage from the beginning of the 21st century to now is the stage of the scale development of roof greening(RG) in China. With the continuous progress of urban construction, on the one hand, the ecological environment is deteriorating, on the other hand, the available green space in the urban center area becomes more and more scarce. The development of this contradiction promotes the rapid development of RG. RG plays an important role in enriching urban landscape, increasing urban green quantity, reducing urban heat island effect, conserving rainwater and reducing temperature, and creating a new green space for the city, including leisure, entertainment and ecology, and improving urban ecological landscape. This paper mainly studies the establishment and application of spatial distribution(SD) model of RG Based on GIS technology. Through understanding the SD design of RG, the paper investigates and analyzes the status quo of green space of roof, macro layout and the integration of multiple functional spaces. This paper studies and establishes a multiobjective optimization model of SD of RG, and analyzes the purification effect of RG on rainwater pollutants and the overall performance of ecosystem service equity. The results show that 26.31% of the people think that the degree of RG is insufficient, and 5.14% think that RG is scarce. In the cognition of the status of RG space, 12.41% of people don't care about RG, 8.69% think it is face engineering, and even 9.31% think it is waste of resources, which indicates that the promotion of RG needs to be improved.

With the rapid development of Internet applications, the impact on the development of data centers is huge. Domestic data centers attach great importance to the acceptance of cloud computing technology and the construction of application systems. Nowadays, data centers can be effectively transformed into cloud computing development. The operating support environment has become the main consideration and focus of today’s data center development. Under the concept of cloud computing, this article analyzes and builds a new data center that is more in line with the needs of resource management and information construction. Taking the development of data centers based on cloud computing technology as the research object, building data centers through cloud computing technology realizes the acquisition and organization of data and makes full use of resources. A new information resource management system with functions such as classification and query of data, overall processing and analysis of data, backup of data, information management and services has been realized. Before using the cloud computing model, the network deployed a total of 40 virtual servers, and the average CPU utilization rate was less than 40%. Since the establishment of the data center model in this article, the utilization rate of the processor has stabilized at around 95%. Therefore, the data center proposed in this paper greatly improves the utilization of data and speeds up the overall construction of the data center.

Corona virus or often called COVID-19 is a virus caused by SARS CoV 2, where the incident was uploaded in the world of health or we often call WHO. Even the World Health Organization (WHO) has declared that the corona virus outbreak is a Public Health Emergency of International Concern (PHEIC) or an international public health emergency. Not only has an impact on health, but this virus outbreak has also had a major impact in various sectors such as disrupting the country's economy, disrupting the education process and so on. This impact is caused by the very fast spread of the virus. Therefore, the author will analyze the level of accuracy in the covid-19 virus by using the certainty method model which aims to make it easier for local governments to monitor the spread of the COVID-19 virus and can determine future policies so that the spread is not more easily exposed to the community. this method will produce data analysis and diagnoses regarding identifying the covid-19 virus with results in the form of accuracy, namely someone is indicated as COVID-19 POSITIVE.

At present, although the ideological and political courses in Colleges anduniversities include practical teaching, there are many problems in practical teaching. Therefore, the reform of College Students' Ideological and political practice teachingmode has become a key research issue. Through the practical teaching mode, wecanenhance the attraction of Ideological and political course, which will improvetheteaching effect. This paper first analysis the importance of practical teachingintheideological and political course. Then, this paper puts forward some problems inpractical teaching. Finally, some suggestions are put forward.