The innovative development of core technologies in artificial intelligence field has become a competitive focus for major economies to seize the first-mover advantage. The analysis of the competitive landscape of artificial intelligence technology from the perspective of technical intelligence plays an important role to accelerate related technology innovation layout and decision-making of responding to challenges.With the help of analysis tools like Histcite, VOSviewer, and the “Science Headlines” big data collection tool of the Beijing Academy of Science and Technology, the development trend of artificial intelligence technology was identified based on data from the Web of Science database, global patent database. Combined with the analysis of the United States’ restrictive measures on China’s science and technology, the international competition situation, opportunities and challenges facing the development of China’s artificial intelligence technology were analyzed. The countermeasures and suggestions for the development of China’s artificial intelligence technology are proposed, which can provide reference for promoting the rapid iterative development of AI technology in China

The state of health(SOH) and remaining useful life(RUL) of a battery are core indicators for evaluating battery performance degradation and potential lifespan. Accurately predicting the SOH and RUL of batteries is crucial in practical applications. To capture changes in battery performance and make predictions, operational data of the battery is typically relied on to train machine learning algorithms, such as neural networks or deep learning methods. However, traditional machine learning models often adopt a single architecture to adapt to the entire dataset, which is insufficient when dealing with complex and highly heterogeneous big data. Such models generally have the risk of insufficient generalization ability and overfitting, and are inefficient in big data processing. Therefore, Hierarchical sparse mixture of experts(HS-MoE) and multi head mixture of experts(MH-MoE) models were used to construct predictive models for battery State of Health(SOH) and Remaining Useful Life(RUL), respectively. Comparative experiments were conducted on publicly available datasets from NASA and EIS, and the results showed that the MH-MoE model outperformed the HS-MoE model in predicting SOH and RUL on both datasets.

As the forefront of technological innovation, industry occupies a central position in promoting the development of productive forces. Accelerating new industrialization is an inevitable choice for generating new productivity, shaping new competitive advantages and stimulating new economic momentum. From the perspective of qualitative reconstruction, new industrialization leads the improvement of the efficiency of labor materials, promotes the expansion of the scope of labor objects, stimulates the ability of workers to leap, reshapes the basic elements of productivity, and promotes the leap and qualitative change of its optimized combination, giving birth to new quality productivity. From the perspective of base support, new industrialization builds a solid base for the development of new quality productivity in five dimensions, namely, market, industry, numerical intelligence, safety and greenness, and empowers the emergence of new quality productivity in an omni-directional way.The process of new industrialization can be pushed forward from the network layer, innovation layer, application layer and linkage layer to accelerate the formation and development of new productivity.

Technological innovation serves as a significant driving force for economic growth. Taking the nine provinces in the Yangtze River Basin as the research object and based on panel data from 2011 to 2022, the impact of technological innovation factors on industrial economic development was studied. Empirical findings reveal that the level of technological innovation factors has an overall positive influence on regional industrial economic development. Technological innovation significantly impacts industrial economic development through various means, such as optimizing industrial structure, enhancing production efficiency, driving consumption structure upgrading, and creating new economic growth points. After conducting numerous robustness tests, this conclusion remains valid. Finally, based on the research findings, policy suggestions are proposed to promote the coordinated development of science, technology, and the economy in the region.

Since feature point matching and optical flow estimation are closely related to the image texture, a standalone visual approach for video stabilization may not be suitable for all scenarios was used. A tightly coupled attitude-sensor-based video stabilization method was proposed. By adaptively adjusting weights, the optimal homography between images relies more on the attitude sensor in low-texture areas or more on feature matching in rich-texture areas. After obtaining the optimal transformation, a robust elastic warping method was applied to further align consecutive image frames. Experimental results demonstrate that the proposed video stabilization method achieves better performance and robustness.

A layout optimization model was constructed to address the issues of multiple material handling intersections, high handling costs, and low area utilization caused by the unreasonable layout of KF Company’s general valve workshop. The model considers the direction of material flow in both directions and aims to minimize material handling costs, maximize non logistics relationships, and workshop area utilization. The system layout planning (SLP) method was used to optimize the workshop layout and obtain a preliminary layout plan. Based on the traditional nondominated sorting genetic algorithm II(NSGA-II), the initial layout plan obtained by the SLP method was encoded as part of the initial population to improve the diversity of the algorithm. The adaptive control strategy was introduced into the crossover and mutation operations, and the simulated annealing algorithm was added. Finally, the analytic hierarchy process(AHP) was used to optimize the workshop layout. Process, AHP make optimization decisions on a set of Pareto optimal solutions obtained by the algorithm. The results show that this method can reduce material handling costs by 38.83%, increase non logistics relationships by 44.83%, and optimize workshop area utilization by 19.50%, demonstrating the effectiveness of the model in workshop layout optimization.

In response to the technical difficulties of the deep exploration and evaluation well FG119 in the Xujiahe Formation of the Sichuan Basin, an “S” shaped wellbore trajectory was designed, with limited ground conditions, resulting in increased difficulty in trajectory controlling and high safety risks of drilling tools. The implementation plan of the ϕ165.1 mm slimming well was adopted, and the development of fractures in the Xujiahe Formation and the high and low pressure interlayers led to high well controlling risks. Therefore, optimization technology for slimming well wellbore structure, complex trajectory optimization design, establishment of four pressure profiles in fractured formations, and supporting technologies such as pre bending dynamic drilling tool combination, fine pressure control, and friction reduction were carried out. This ensured the smooth completion of the first deep “S” shaped slim well in the work area, providing technical reference for the subsequent construction of complex wellbore track wells in the block.

In response to the problem of insufficient accuracy of the traditional Sadovski model, based on vibration monitoring data from the soft rock tunnel blasting construction site of the West Chongqing high-speed railway, the variation trend of the model parameters of the traditional Sadovski model at different footage was explored, and the Sadovski model was improved accordingly. The fitting accuracy of the traditional model and the improved model was compared. The results show that the peak vibration velocity during blasting construction generally decreases exponentially with the increase of blasting center distance, and the traditional model has a large degree of data dispersion after fitting. In the traditional Sadovski model, the parameters k(coefficient of association)and α(attenuation index)exhibit linear and exponential functional relationships with the footage, respectively. The prediction accuracy of the modified model is improved by about 23% compared to the traditional model.

In response to the demand for reservoir protection during well maintenance of low-pressure gas wells in the South China Sea L gas field, the optimal evaluation of the system types and concentrations of foaming agents and foam stabilizers in the laboratory was carried out. A set of foam workover fluid system and preparation process suitable for L gas field were constructed. The system has a half-life of 60~72 h under reservoir conditions of 80~90 ℃ and a maximum temperature resistance of 100 ℃, demonstrating good temperature resistance and stability. The foam density can be as low as 0.5 g/cm³, matching with the pressure coefficient of the target reservoir, and effectively reducing the leakage. Through core damage test, the recovery rate of permeability of high permeability core after being polluted by foam workover fluid can reach 95.1%, indicating that the system has excellent reservoir protection performance.

With the intensification of global climate change, low-carbon economy has become a key goal for economic transformation in various countries. Financial support is crucial for promoting low-carbon economic development. Based on provincial data of China from 2012 to 2021, a spatial Durbin model(SDM) was constructed to analyze the impact of financial structure, vitality, efficiency, and density on low-carbon economy. The results indicate that financial structure and density have a negative impact on the development of low-carbon economy, while financial vitality plays a positive role. In addition, the development level of low-carbon economy in various provinces shows spatial correlation. Based on this, it is proposed to strengthen regional policy coordination, enhance the vitality of financial markets, and promote coordinated development of low-carbon economy regions.