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This paper proposed a hybrid approach for the identification of encrypted traffic based on advanced mathematical modeling and computational intelligence. Network traffic identification is the premise and foundation of improving network management, service quality, and application security. It is also the focus of network behavior analysis, network planning and construction, network anomaly detection, and network traffic model research. With the increase in user and service requirements, many applications use encryption algorithms to encrypt traffic during data transmission. As a result, traditional traffic classification methods classify encrypted traffic on the network, which brings great difficulties and challenges to network monitoring and data mining. In our article, a nonlinear modified DBN method is proposed and applied to encrypted traffic identification. Firstly, based on Deep Belief Networks (DBN), this paper introduces the proposed Eodified Elliott (ME)-DBN model, analyzes the function image, and presents the ME-DBN learning algorithm. Secondly, this article designs an encrypted traffic recognition model based on the ME-DBN model. Feature extraction is carried out by training the ME-DBN model, and finally, classification and recognition are carried out by the classifier. The experimental results on the ISCX VPN-non-VPN database show that the MEDBN method proposed in this article can enhance the classification and recognition rate and has better robustness to encrypt traffic recognition from different software. [ABSTRACT FROM AUTHOR]

By analyzing the historical background of the times and summarizing the current situation of urban development research at home and abroad, we find that there is a lack of theoretical and practical research related to intelligent park cities. Therefore, this paper first starts with the connotation of park city theory, focuses on the improvement of planning methods, and studies the application paths of big data technology in the planning and construction of park cities. Taking Jinzhai Country as the research object, this paper further illustrates the applicability of this research method at the macrolevel. In the context of the park city, we analyze the problems of the current status of city construction in general and explore the path of "planning concept first, big data-assisted design" for innovative and intelligent city construction. According to the study, the overlook corridor control has an impact on the building height. In terms of landscape protection, overlook system simulation is the other key factor. In addition, the analytic hierarchy process is the basis for development intensity control. The results show that big data technology can assist in the landscape conservation, morphology formation, and efficient operation of Jinzhai Country Park City. Our aim is to achieve the protection and utilization of its ecological environment and natural resources and thus to comprehensively coordinate the multidimensional urban spaces and build a park city model. As an urban development model that meets the requirements of being "people-oriented, efficient, green, and aesthetic" in the new stage, park cities need to be faced by researchers in order to further realize the overall city goal and vision for the whole society to be smart. It also provides relevant design ideas and methods for the planning and construction of park cities in other similar cities or regions. [ABSTRACT FROM AUTHOR]

The construction of municipal road engineering is a complex system engineering, and its internal components are interconnected and mutually restricted, and the relationship is intricate. The quality of its construction plan directly affects the realization of the project's quality, safety, environment, progress, cost, and other goals, and the project construction plan occupies an important position in the construction of the project. The selection of construction plans for municipal road projects involves a wide range of areas. According to the characteristics of specific municipal road engineering projects, it is very important to establish a scientific construction scheme intelligent generation model and select the optimal construction scheme suitable for the project from many feasible construction schemes, which has very important theoretical research value and practical application value. After analyzing the knowledge characteristics of road construction technology and the content of road construction schemes, this study decomposes the knowledge of road construction schemes into two parts: case characteristics and solutions. Then, according to the needs of case retrieval technology, the data storage form of each subdivision index is proposed and the value range is explained, and a complete structure form of the road construction scheme case database is formed. Combined with actual engineering cases, the feasibility and applicability of the intelligent generation method of the road construction scheme based on the KNN algorithm is confirmed, which provides a new idea for the automation of road construction scheme preparation and the improvement of the scheme application effect. [ABSTRACT FROM AUTHOR]