Tingmei Wang’s scientific contributions

Highway travel time, defined as the time difference between a vehicle entering and exiting the highway, is primarily influenced by factors such as the highway's characteristics, current road conditions, and the driver's behavior. Travel time is a crucial parameter for assessing the operational state of a highway and serves as an important reference for both drivers when selecting routes and for traffic managers in implementing control measures. Therefore, predicting highway travel time is of significant importance. Long Short-Term Memory (LSTM) is a type of recurrent neural network, an improved version of the traditional recurrent neural network, known for its excellent performance in predicting sequential data, such as time-series data on highway travel times. In operations research, search optimization algorithms have been a key area of focus in conjunction with machine learning. The Sparrow Search Algorithm (SSA), a relatively new search optimization algorithm, boasts high convergence speed and accuracy, along with strong global search capabilities, reducing the risk of getting trapped in local optima. This study utilizes vehicle entry and exit data collected by the ETC system at the Jin-Gang Expressway toll stations to analyze the highway's basic information. Building upon the traditional LSTM model, we integrate the SSA to optimize the LSTM model parameters. By using SSA to search for the optimal parameters, we form a new SSA-LSTM model. Finally, we apply this model to predict travel time data, showing a 120% improvement in prediction accuracy compared to the original LSTM model.

Developing cultural tourism is a vital approach to promoting traditional culture, enhancing cultural confidence, and fostering economic development. This study focuses on the Temple of Heaven as its research subject, utilizing valid tourist reviews collected from the travel website "Trip.com Group". Based on the "cognition-emotion" model, the study employs text analysis and comparative analysis to conduct an image analysis of tourists' cognition and emotions, determining the overall image and analyzing the revisit intention. The findings reveal that: firstly, the "cognition-emotion" model is highly applicable to the study of perception of cultural tourism destination image; secondly, in the construction of image perception of cultural tourism destination image, emphasis is placed on the attraction of the scenic area's culture to tourists; thirdly, there is a lack of awareness of the cultural resources at the Temple of Heaven, along with inadequate facilities and insufficient quantity.

Virtual reality technology, as a new educational model supported by modern information technology, has the potential to enhance the quality and rationality of education continuously. Starting from the application potential of virtual reality technology in education, this paper, combined with constructivist theory, explores the integration advantages, challenges, and planning of virtual reality technology and education. Constructivist theory emphasizes that learners acquire knowledge through context, collaboration, and meaning construction, while virtual reality technology provides learners with immersive learning environments, promotes exploratory activities, facilitates collaborative communication, personalized learning, and practical operations, thereby deepening understanding and application of knowledge. However, virtual reality technology still faces challenges in education such as a lack of teaching resources, inadequate teacher training, and equipment stability. To address these challenges effectively, it is suggested to establish unified standards to promote resource sharing, build high-quality teacher teams, address equipment technical issues, and enrich user practical experience. These measures will help promote the development and application of virtual reality technology in the field of education.

With urban traffic congestion and parking issues becoming increasingly severe, the emergence of smart parking systems offers a solution. This research designs and implements an Android-based intelligent parking reservation management system. It aims to provide convenient and efficient parking services by combining mobile technology with intelligent management. The system includes core functions such as user management, parking facility information retrieval, parking space reservation, and driving navigation, catering to diverse needs in urban parking scenarios. Through rigorous system testing, this solution demonstrates excellent performance in user experience, functionality, and efficiency. The Android-based parking reservation management system proposed in this study offers an innovative solution to address urban parking challenges. It paves the way for new possibilities in smart city transportation management.