The 12345 hotline service has become a widely accepted smart city governance system of citizen contact with the local authorities in Beijing and has enabled leaders to handle public complaints more effectively. However, there have been few studies on the performance of the 12345 hotline. This study, taking Beijing city as the study area, explains how this system improved urban problem management and the degree of improvement in different urban problem categories. First, we studied the quantity distribution of 12345 cases and the public’s top concerns. Then, based on the VAR model, we analyzed the specific dynamic influence process and degree of 12345 cases on UGMS cases, which reflect urban public problems. The main findings of this research are as follows: (1) Illegal parking/charging problems and issues with the city’s dirty conditions were the two primary concerns of the public. (2) The 12345 system hampered the increase in urban public problems with a lag of 3–5 days. (3) Exceptionally, for the construction management and market regulation categories, the hotline cases had no active effect on urban problem management. This paper can help city authorities to assess the strength and weakness of the 12345 system and decide on improvement plans for urban management.

Research on land use change is helpful to better understand the processes and mechanisms of land use changes and provide a decision base for reasonable land development. However, studies on LUCC were mainly conducted for megalopolises and urban agglomerations in China, but there is a gap in the scholarly community when it comes to shrinking small cities where the population decreased sharply under the influence of the urban expansion of megacities. Hence, it is necessary to investigate the evolution rule of land use in these regions. This study takes Qishan County in Shanxi Province as the research subject and analyzes the land use change over the last 20 years with remote sensing technology. Comparing the two LUCC models of the CA-Markov Model and the LCM Model, an optimal model is used to predict and simulate land use change under three potential scenarios in 2030. The conclusions are stated as follows: (1) From 2000 to 2020, the cultivated land area increased originally and subsequently decreased, and forest land continued to decrease at a progressively slower speed. In contrast, the urban land area expanded significantly. (2) The comprehensive dynamic change in water land is the most significant, indicating that this is an unstable land resource in the region and more attention should be given to this matter. (3) The scenario of water area protection indicates that the inhibition of the transition of water areas can protect their vulnerable ecological environment without negatively impacting economic development. Furthermore, the ongoing focus on economic development in the region is related to the rapid disappearance of cultivated land, which is not an optimistic perspective for the area’s ecosystem. The results of this study implied land transition features and mechanisms in Qishan County, providing novel insights for decision support for county-level land use planning.

Traditional Chinese medicine has a long history and plays an important role in China's social development. With the continuous improvement of living standards and the development of medical technology, people put forward higher and higher requirements for medical level. This paper uses artificial intelligence technology to design an intelligent platform for traditional Chinese medicine detection information. The design goal is to solve the problems of uneven distribution of medical resources, residents' difficulties in seeking medical treatment, and limited medical resources in China. The system adopts BP network algorithm. Through simulation experiments, it can be seen that the BP neural network structure and relevant parameters adopted by the system for TCM diagnosis and treatment are reasonable and can meet the requirements of target accuracy. The design of this system is divided into three subsystems according to functions, namely, the Chinese medicine management subsystem, the patient information management subsystem, and the user information management subsystem. By using artificial intelligence technology, the system helps doctors identify and diagnose disease information, complete information detection, and record and manage relevant information of patients. By saving and accumulating diagnosis and treatment knowledge, the system can deal with different conditions, effectively reduce consultation time and improve doctors' work efficiency. The design of this platform has been tested and evaluated repeatedly, and the test process has been recorded and iterated, so as to ensure the stable and trouble free operation of the system. This paper designs an effective TCM detection information platform by using artificial intelligence technology.

Traditional Chinese medicine has a long history and plays an important role in China's social development. With the continuous improvement of living standards and the development of medical technology, people put forward higher and higher requirements for medical level. This paper uses arti cial intelligence technology to design an intelligent platform for traditional Chinese medicine detection information. The design goal is to solve the problems of uneven distribution of medical resources, residents' di culties in seeking medical treatment, and limited medical resources in China. The system adopts BP network algorithm. Through simulation experiments, it can be seen that the BP neural network structure and relevant parameters adopted by the system for TCM diagnosis and treatment are reasonable and can meet the requirements of target accuracy. The design of this system is divided into three subsystems according to functions, namely, the Chinese medicine management subsystem, the patient information management subsystem, and the user information management subsystem. By using arti cial intelligence technology, the system helps doctors identify and diagnose disease information, complete information detection, and record and manage relevant information of patients. By saving and accumulating diagnosis and treatment knowledge, the system can deal with different conditions, effectively reduce consultation time and improve doctors' work e ciency. The design of this platform has been tested and evaluated repeatedly, and the test process has been recorded and iterated, so as to ensure the stable and trouble free operation of the system. This paper designs an effective TCM detection information platform by using arti cial intelligence technology.