Based on the 151 ancient city sites from the Western Han Dynasty to the Ming and Qing Dynasties in the Hexi Corridor of Gansu Province, GIS(geographic information system) spatial analysis method was used to study the spatial and temporal evolution of ancient city sites and their distribution characteristics in the Hexi Corridor. The results show that the city sites in Zhangye City have the highest distribution numbers, and county-level city sites are the most numerous grade.They are concentrated in Zhangye City, Jiuquan City, and Wuwei City, the distribution of city sites in each period exists certain unevenness and concentration, which is mainly manifested in the Ming and Qing Dynasties, and may be related to the better preservation of the period. Zhangye has experienced multiple periods of high density nucleus of city sites,the directional trend and concentration trend of the distribution orientation of city sites become increasingly obvious with the distribution of time, showing a tendency of “east-southwest-northwest”.

The methods, tools, technical frameworks, and application practices for knowledge mining were explored using AIGC (artificial intelligence generated content)in combination with the RAG (search enhanced generation) and stable diffusion models, as well as AI Agents, in order to development and application an AIGC-based intelligent management assistant for libraries, contributing to industrial development and knowledge dissemination.The research focuses on the development process, model principles, and utilization of AIGC technology to expand library knowledge services of the AIGC-based intelligent management assistant for libraries. Furthermore, the demands of industrial development and envisions future service expansion capabilities were integrated.Through the development and practice of this project, an efficient, intelligent, and personalized intelligent management assistant for libraries has been constructed. The innovative application of AIGC technology in library knowledge services was explored, aiming to provide some references for the specialized and scenario-based application of large models in the library and information science field.

Overriding sand bodies of Jurassic Shaximiao Formation in Tianfu gas field are developed vertically, and the formation pressure of gas-producing layer varies greatly from shallow to deep. There are distributions of pressure coefficients from ultra-low pressure, low pressure to normal pressure. Due to the multiple influences of storage, gas-bearing property and formation pressure, the error of gas reservoir productivity prediction is always great. For this problem, taking the tight gas of Tianfu gas field as an example, gas reservoir production levels were divided according to the main factors of productivity firstly, and the equivalent cylinder model of gas reservoir under different production levels was established. According to the characteristics of gas reservoir, Redlich-Kwong equation of state was selected to deduce and calculate the total mass of methane in equivalent cylinder under formation conditions. Then, according to the total mass, a gas production prediction model was established to realize the productivity prediction of gas reservoir of multi-pressure system. And the following research results were obtained.The equivalent cylinder model of gas reservoir integrates the main factors of productivity in the study area, and a semi-theoretical and semi-empirical productivity prediction model is constructed through theoretical derivation and statistical analysis, which is more meaningful than mathematical statistics. Based on Redlich-Kwong equation of state, the model fully refers to the formation conditions and fluid characteristics in the study area, which is helpful to improve the prediction accuracy. Using actual data, compared with multiple regression method to predict gas production, the productivity prediction method based on equivalent cylinder model has smaller error.

The state of health(SOH) and remaining useful life(RUL) of a battery are key indicators for measuring battery performance degradation and remaining useful time. Predicting battery SOH and RUL is of great importance in practical applications. Usually, battery operation data is used to train machine learning algorithms, such as neural networks or deep learning, to capture the changing patterns of battery SOH and RUL and make predictions. Traditional machine learning models often use a single model to adapt to the entire dataset, which is inadequate when dealing with complex and highly heterogeneous data. Building a model for each prediction target incurs high training and maintenance costs. Sparse mixture of experts (SMoE) was used to construct a joint prediction model for battery SOH and RUL, and battery fusion data was used to simultaneously predict battery SOH and RUL. The results of testing on NASA’s public dataset show that the proposed joint prediction model can effectively predict battery SOH and RUL, with a mean square error of 0.069 for SOH prediction and 2.042 for RUL prediction. Tested on the EIS public dataset, the mean square error of the SOH prediction value of the joint prediction model was 0.118, and the mean square error of the RUL prediction value was 3.072, indicating a significant improvement in accuracy. The models and methods proposed in the text have certain reference and application value.

To solve the problems of poor branching and red light strip in the track circuit of Daqin Railway, a cable transmission scheme combining axle counting technology and track circuit is proposed. The potential application of axle counting technology in solving track circuit problems was analyzed, the overall architecture of the system was designed, key modules are identified, and the system workflow was clarified; Then the key components were designed and corresponding renovation plans were proposed based on the on-site situation; Finally, overall testing on the system was conducted to verify its stability and reliability, and test results that meet expectations were obtained. This plan can provide technical reference for related circuits with issues such as poor branching and red light bands.

The safe operation of the airport is the cornerstone of civil aviation safety. An airport operation risk assessment system was constructed to assess the safety risks of airport operation. It also identifies and eliminates the risk factors and safety hazards in advance. Firstly, using the theory of man-machine-environment-management, the airport operation safety evaluation system was established. Then, using the analytic hierarchy process and the entropy method, the data obtained from the two methods was analyzed and compared, and the weighted comprehensive calculation was carried out to obtain the comprehensive weight of each indicator. Finally, the risk assessment method established in the paper was used to conduct a risk assessment test of the operation of Yuncheng Yanhu Airport. The test results show that the research method in this paper is feasible and effective.

Technological innovation leading the construction of a modern industrial system has become a key task at present. As an important component of the modern industrial system, how technological innovation lead the development of future industries has become an important research topic. On the basis of sorting out the concept, content, and characteristics of future industries, the path of technological innovation leading the development of future industries was explored from a theoretical perspective, including strengthening top-level planning and layout, increasing the supply of original scientific and technological innovation achievements, and strengthening the synergy of technological innovation elements. Finally, taking Jiangsu, Beijing, and Shanghai as cases, the practical exploration of promoting future industrial development in three provinces and cities was explored, in order to provide theoretical and practical references for other provinces and cities to promote future industrial development.

Local urbanization, as an important strategic means to promote the transformation and upgrading of the manufacturing industry and regional coordinated development, not only promotes the rapid growth of the local economy, but also profoundly affects the transfer trend of the manufacturing industry. Aiming to explore the impact of local urbanization on the transfer of China’s manufacturing industry, based on the dual perspectives of output value and labor factors, an indicator system for local urbanization, manufacturing output value transfer, and labor factor transfer was constructed. The local urbanization, manufacturing output value transfer, and labor factor transfer indices of 30 provinces in China from 2013 to 2021 were measured, and the coordination between manufacturing output value and labor factor transfer was calculated. A fixed effects model was used to empirically test the impact of local urbanization on the transfer of China’s manufacturing industry. The results indicate that on-site urbanization can promote the transfer of labor factors in medium tech industries, inhibit the transfer of labor factors in high-tech industries, and have a significant inhibitory effect on the transfer of output value in different types of manufacturing industries. At the same time, on-site urbanization has a significant inhibitory effect on the coordination between output value and labor factor transfer in primary and high-tech industries.

“A new development pattern with domestic circulation as the mainstay, domestic and international circulation mutually promoting”is a clear development blue print of the current and future. In this context, the development of local traditional pillar industries are confronted with opportunities and challenges. In order to achieve the transition from quantity catch-up to quality improvement, from factor-driven to all-factor upgrading, and from industrial scale expansion to industrial structure upgrading and transformation, some path were proposed, including the establishment of regional industry alliances, the setting of local industry quality certification standards, the enhancement of product quality, the improvement of assessment and risk control, and the soft power-driven flexible coupling of high-quality development momentum.

Based on China’s provincial panel data from 2012 to 2022, a two-way fixed effects model, spatial Durbin model, and moderation effect model were used to empirically test the impact of innovation factor agglomeration on the high-quality development of the manufacturing industry. The results show that the agglomeration of innovation factors can promote the high-quality development of manufacturing industry, and at the same time, hinder the high-quality development of manufacturing industry in neighboring areas while promoting the high-quality development of local manufacturing industry. The positive regulatory effect of digital transformation on the agglomeration of innovative factors and the promotion of high-quality development in the manufacturing industry was significant in the eastern region, but not significant in the central and western regions. The digital transformation positively regulated the relationship between the agglomeration of innovation factors and the high-quality development of manufacturing industry in the local area, with weak regulatory effects on geographically adjacent regions and strong regulatory effects on economically adjacent regions. The agglomeration of innovative factors in high marketization areas can promote the high-quality development of the manufacturing industry more significantly, compared to low marketization areas. Finally, policy suggestions are put forward, including promoting regional innovation cooperation,strengthen the construction of digital infrastructure, and facilitate the appropriate aggregation of innovation factors.