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With the continuous development of the economy and the level of science and technology, people are no longer satisfied with the old rural tourism model, and information technology is developing rapidly, which brings an opportunity for developing rural tourism innovation. As a product of the comprehensive development of the information age in recent years, “Internet+Rural Tourism” builds an intelligent cloud platform for rural information services relying on big data and other advantages and establishes a rural intelligent tourism service system to provide convenient, intelligent, and diversified services for tourists. This paper elaborates on the practical significance of “Internet + rural tourism” development opportunities”. It proposes to scientifically calculate the environmental capacity of rural eco-tourism areas, control the scale of visitors and reasonably invest in costs because of the problems of lagging infrastructure facilities and limited distribution of inputs and outputs in the process of its development. The results of this paper show that the satisfaction level of rural tourism tourists is the lowest, with the degree of “dissatisfaction” as high as 38.40%; in the rating of rural tourism indicators, the rating of rural ecological environment is only 52.41, the average rating of rural economic indicators is 60.12, and the average rating of comprehensive management indicators is 58.2. The results of this paper also illustrate that the current rural tourism development has three major problems: environment, economy, and management and that rural tourism should not blindly invest high costs if it wants to seek high-quality development but should seek long-term development of rural tourism based on its characteristics and rural ecological environment indicators.

In today’s highly developed information age, Chinese cultural heritage is gradually shrinking, and some of them are even in danger of disappearing. In this paper, the study of Chinese cultural heritage pattern information visualization from a digital perspective is based on the 3D modeling technology method, firstly, the acquisition of cultural heritage data is studied, and the principle and method of cloud data alignment are analyzed. The data of regular surface cultural heritage and heterogeneous complex surface cultural heritage patterns are processed respectively, and the basic theoretical basis of surface reconstruction is given, including data parameterization, surface interpolation method, and surface approximation method. Based on the comparison of the accuracy of three different methods for visualizing the information of Beijing cultural heritage patterns, the experimental analysis shows that the 3D model technology information visualization is highly accurate and stable, always maintaining an accuracy of 0.8, with low technical requirements, and the limitation is that it is not suitable for use in highly complex cultural heritage. The analysis shows that the information visualization of Chinese cultural heritage patterns is conducive to the protection of the dissemination and transmission of Chinese cultural heritage, and helps young people to establish correct socialist core values under the inculcation of Chinese cultural heritage.

In the Internet era, soccer teaching has gotten rid of the previous theoretical teaching mode and paid more attention to the use of video and multimedia for network teaching. In this paper, from the perspective of a fuzzy mathematical algorithm, the mathematical set algorithm is used to construct a fuzzy matrix through algorithm mapping, calculate the NMI value of the equivalent algorithm and the comprehensive rating weights of U1-U10 in the evaluation elements of soccer network teaching, and derive the fuzzy transformation value of the rating result of soccer network teaching platform as 83.7895. The probability distribution value is inferred to be 45.8% on average by creating the affiliation function and then calculating the search accuracy, platform recall, and teaching F1 metrics of the Zadeh mathematical operator. After calculating the weighted average value of B=87.6617 for the Zadeh mathematical operator through the metrics, an empirical analysis of the feasibility of invoking the fuzzy mathematical algorithm in the soccer teaching web platform was conducted. The results showed that the total number of students who wanted to continue using the platform was 36,530, accounting for 91.33% of the total number of students, indicating that the use of fuzzy mathematical algorithms to participate in the teaching of the online platform is significantly better than the traditional teaching model and is conducive to improving the effectiveness of student autonomy.

As an emerging type of large commercial building, commercial complexes play an increasingly important role in contemporary urban development and construction trends. In order to better study the organization of public space relations in commercial complex buildings, this paper selects eight commercial complexes as sample cases to analyze their spatial design in terms of both content public space and external public space based on big data technology. Regarding the design of the commercial complexes’ internal public space movement, the highest accessibility degree reached 95.3%, while the average was 82.5%. Regarding visibility, the highest level was 96.0%, and the average was 83.3%. For large complexes, better spatial relationships can be designed to improve the circulation degree and thus enhance customers’ consumption experience. Regarding the convenience of traffic connection to the external space of commercial complexes, an average of 41.4% of customers consider it very convenient, 23.1% consider it relatively convenient, 27.9% consider it somewhat inconvenient, and 18.0% consider it very inconvenient. Commercial complexes can effectively attract more repeat customers if they can improve the convenient design of transportation connections. The study of public relations of commercial complexes based on big data helps to discover the defects of their public space design and plays a significant role in optimizing spatial design and relationship organization and strengthening their integrated functions.

In the age of information technology, the communication and collision mode between folk music cultures is no longer single, and the data of information also makes the dissemination of folk music culture develop towards diversification. This paper first builds a folk music appreciation platform based on B/S model system architecture. Apriori mining algorithm is added to improve the fully automatic algorithm. After constructing the database of aesthetic elements, we select and pre-process the audio data to be mined for folk music appreciation. Convert and mine the processed aesthetic elements. Finally, the mined aesthetic elements in folk music appreciation are analyzed. The test results of the improved Apriori data mining algorithm are generally high, as verified by experiments. The folk music with the highest number of clicks was “Five Brothers Herding Sheep” with 810 clicks. The ethnic music with the least number of clicks is “Yellow River”, with 189 clicks. The ethnic music with the highest number of clicks was “Five Brothers Herding Sheep”, with 290 clicks. The folk music with the least number of clicks is “Dongfang Hong”, with 76 clicks. This confirms that the Apriori mining algorithm, after improvement, has high accuracy and outstanding advantages and can be used as the main means of mining aesthetic elements in folk music appreciation. Thus, the reliability of folk music appreciation can be further improved.

Along with the development of Chinese journalism and the continuous exploration of journalistic genres in the journalism industry, non-fiction writing has been shuttling between the two genres of literature and journalism. The development background of the times traditional non-fiction writing course teaching mode is difficult to adapt to the needs of college students, this paper around the decentralized Internet-based model of non-fiction writing in local college writing course application research, firstly, to build a non-fiction writing platform mathematical model, Markov random field, through the Bayesian network algorithm to process the characteristics of college students in the classroom data, the results show that students within the platform The results show that as the number of tests increases, the score trend from the three aspects of writing ideas and writing style and writing skills all show an upward trend, and the average score basically stays between 80-90, which is beneficial to understand the students’ writing level and performance, provide different users with suitable learning content for themselves, and contribute to the cause of Chinese literature by improving the students’ ability of non-fiction writing. It is of great value in changing the closed mode of writing courses, enhancing the practicality of writing content, and training college students to think logically and critically.

Party building and ideological and political education have received much attention in recent years, and the construction of its work practice platform is particularly important. In order to improve the level of party building and ideological and political education in colleges and universities, In this paper is based on the information fusion technique to fuse relevant factors after data, feature, and decision levels. Using sampling calculation, the percentage of relevant factors was calculated as 37%, 38%, and 25%, and the Kalman filter algorithm was used to test the information data. The two factors that accounted for more were selected as the platform construction indexes, and the information was fused with the maximum likelihood estimation and D-S algorithm to build the party construction and ideological and political education work practice platform. It is evident that the practice platform based on information fusion technology can promote the development of ideological and political education.

With the accelerated advancement of big data Internet development, people gradually realize the urgency and importance of energy saving, so the multi-objective optimization research for the performance of office buildings in cold regions is significant, and this paper focuses on the construction of a building window design model based on visual comfort supported by multi-objective evolutionary algorithm- taking office buildings in cold regions as an example, firstly, by reviewing the literature to understand the principle, algorithm, and concept of multi-objective evolution, construct the building window design model based on visual comfort according to the objective function and extract the standard model of inner corridor slab space building in office buildings in cold regions of Harbin and Shenyang. The optimized design of building window parameters was carried out using the established joint simulation and optimization work platform. The results show that for Harbin, as the window heat transfer coefficient increases, the heating energy consumption increases, the cooling energy consumption increases more slowly, and the total energy consumption increases linearly. An increase in window heat transfer coefficient by 0.1 ( ∙ ) Increases are cooling energy consumption by 0.18%, heating energy consumption by 0.78%, and total energy consumption by 0.46%. For Shenyang, as the window heat transfer coefficient increases, the heating energy consumption increases, the cooling energy consumption increases more slowly, and the total energy consumption increases linearly. If the heat transfer coefficient of the window increases by 0.1 / ( ∙ ), cooling energy consumption increases by 0.18%, heating energy consumption increases by 0.78%, and total energy consumption increases by 0.46%. This study provides a theoretical basis for extracting standard models for other building types while making the results more generalizable and improving the efficiency of sustainable office building design.

With the development of history, some folk dances are annihilated and lost in the inheritance. In order to protect and inherit national intangible cultural heritage and promote the construction of advanced socialist culture, this paper uses information fusion technology, combines national aesthetic personality, and refers to multi-factor theory, construction theory, and distillation theory to design and reform the art practice model of folk dance education. The data of dancers’ skeletal joint points are collected by using multiple Kinect sensors, and the Kalman filter algorithm is selected to establish the human skeletal motion model and fuse the data information of each joint point. Taking the hand_right and elbow_right joints as examples, it was found that the mean value of the error between the testers’ joint trajectory and the template movement was reduced from 10mm to 4mm, and the mean value of the error between the joint angle and the template movement was reduced from 90° to 35°. Comparing the dance movement training effects and scores of the experimental group and the control group, it was found that the experimental group kicked the front and side legs an average of 70 times/minute, the middle jump height was improved by 10cm, and the average score was 3.33 points higher. This indicates that the integration of information fusion technology in the art practice of dance education can realize the practical innovation of college folk dance education and improve the comprehensive level of folk dance.