To enhance the accuracy of customer churn prediction, an improved Stacking ensemble learning method with Bayesian optimization(BO) incorporated was introduced. First, base learners were selected based on their predictive performance and inter-model correlations. Noticing the fact that the performance variation among base learners was neglected in the traditional Stacking methods, the Bayesian optimization was introduced to fine-tune the weights of each base learner for minimizing prediction errors. Finally, the weighted predictions from the base learners were combined, and the Logistic Regression serves as the meta-learner for the final prediction. The results demonstrate that the proposed BO-Stacking model outperforms both the single models and the traditional Stacking methods in terms of recall rate, F1-score, and AUC(area under the curve) value, which validates the effectiveness of the proposed approach. This provides a reliable reference for enterprises to develop effective customer retention strategies.

:In view of the existing problems of limited development and lack of experience of tourism electronic map products, based on the Kano model and Better-Worse four-quadrant analysis, in-depth interview method, questionnaire survey method and other research methods were comprehensively used to discuss the quality needs of users’ information. From the three dimensions of technical function, aesthetic emotion and utility value, user’s information quality demand type and satisfaction of tourism electronic map products were analyzed. In order to improve the design strategy of continuously optimizing technical function experience, some strategies are proposed, including deeply mining aesthetic emotional experience and focusing on utility value experience in the tourism electronic map experience, so as to improve tourists’ satisfaction and happiness experience index for the electronic map.

Revealing the effect of particle size distribution (PSD) to the stiffness characteristics of the red stratum soil-rock mixture (RS S-RM) has significant implications for the subgrade construction, with Sichuan Basin as a representative. 20 large-scale triaxial tests with different PSDs were conducted. Introducing the concept of effective dominant skeleton size ( d_{\mathrm{e}\mathrm{d}}), digital image processing technology was utilized to collect the d_{\mathrm{e}\mathrm{d}}. The relative dominance ratio ( D_{\mathrm{d}}) describing the structural skeleton changes after the test was defined. The response of the stiffness characteristics of the RS S-RM regarding confining pressure ( {\sigma }_3) and D_{\mathrm{d}} were investigated. Validation experiment and related research verify the credibility of the formation mechanism of stiffness. The results indicate that as the shearing process, more and more particles near the shear plane transition from their initial interlocking state to sliding friction. Consequently, the soil-stone framework evolves from a suspended-dense structure to a skeleton-dense structure, and finally transforms into a skeleton-void structure; the initial deformation modulus ( E_0) relationship with {\sigma }_3 and D_{\mathrm{d}} follows: E_0 = 14.50 + ( 1 + 36.33 {{\sigma }_3}^{0.1} ) {\mathrm{e}}^{1.06D_{\mathrm{d}}}. The relationship between the tangent deformation modulus ( E_{\mathrm{t}}) of the specimen at failure {\epsilon }_1 = 15 \mathrm{\%} is E_{\mathrm{t}} = - 6.06 + ( 1 + 0.08 {\sigma }_3 ) {\mathrm{e}}^{-0.09D_{\mathrm{d}}}. Validation experiment and related research confirmed the response of E_0 and E_{\mathrm{t}} to {\sigma }_3 and D_{\mathrm{d}}. The stiffness characteristics of the RS S-RM can be predicted solely based on the PSD and {\sigma }_3.

Bedding slope is an easy-to-slide structure often encountered in mountain highway construction, and weak interlayer is a typical potential sliding surface. Taking the bedding slope of expansion project of Guangyuan-Mianyang section of G5 Beijing-Kunming highway as an example, the physical and mechanical parameters of the weak interlayer and the water content and strength parameters under different saturation time were obtained through laboratory tests. The continuous-discontinuous numerical simulation was carried out by using the finite element-smooth particle dynamics method to study the instability evolution and failure mode of the bedding slope. The results show that with the saturation softening of the weak interlayer, the water content increases and the strength decreases, and the plastic zone of the bedding slope continues to extend to the trailing edge of the slope. When the water content is higher than the liquid limit of the weak interlayer, the plastic zone range increases sharply to the first instability length, and the slope shows traction slip-crack failure. The horizontal displacement of the bedding slope has a displacement peak point at the foot of the slope at the slope line slope position, and there is a maximum displacement at the first-level slope platform ; with the increase of the water content of the weak interlayer, the horizontal displacement of the slope increases continuously, and the maximum point of the horizontal displacement appears after 1 h of saturation and begins to undergo large-scale instability deformation.

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

To study the deformation patterns of wet-sinking loess widely distributed in the alluvial plains of the northern Tianshan Mountains in Xinjiang, experimental studies were carried out to differentiate the effects of soluble salts on the wet-sinking and dissolving effects of loess. Through the ‘three-line method’ compression test of original water content saturated with Na₂SO₄ salt solution and pure water on the original loess samples with five kinds of soluble salt contents, the influence of soluble salt content and its state of existence on the characteristics of loess wet subsidence and subsidence was obtained, and the calculation model of the amount of loess wet subsidence and subsidence deformation with different salt contents was constructed. The results show that there is a critical value for the salt content change to improve the skeleton effect between particles, and wet subsidence is the main mode of deformation when it is less than 8‰ and more than 23‰, while dissolution subsidence is the main mode of deformation when it is between 8‰~23‰; mathematical relationship between each salt content and deformation coefficients under the step-by-step pressure has been fitted by using the Giddings and Extreme model function. The FreundlichEXT regression model was used to construct the starting pressure function equation for different salt contents of soil samples in the study area. The research results can provide scientific basis for the study of the mechanism of joint action of wet subsidence and dissolution subsidence of eolian salt in the region, the design of structural loads and the calculation of deformation.

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.

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.

In order to investigate the characteristics of karst pipeline in Dongcun, Xinyu, Jiangxi Province, rationally develop and utilize Karst water resources and scientifically protect karst water environment, two kinds of fluorescence tracers, sodium fluorescein and Rhodamine, were selected for quantitative tracing test research on Karst pipeline. The distribution, morphology and hydraulic characteristics of the Karst pipeline through the penetration curve and clarifies the connectivity of groundwater recharge, runoff and discharge characteristics were analyzed. The test results show that Zhangmuqiao water-dissipation cave is connected to Niulang Zhinv cave underground river. The Karst development of the underground river is extremely developed, with large-scale Karst pipeline as the main Karst pipeline. The pipeline is single-like and the underground runoff path of the main Karst pipeline is short. Some parts of the groundwater has the characteristic of pressure-bearing. The direction of the underground runoff is from east to west. Its flow rate is fast, and so is the solute migration rate. There’s small possibility of other drainage outlets. However, there is no hydraulic connection between the Zhangmuqiao water-dissipation cave and Shenniu cave underground river outlet.

Exploring the best method of regional landslide susceptibility assessment is of great importance for accomplishing regional hazard prevention and mitigation work.Taking Xishan mining area in Shanxi Province as the study area, nine assessment factors were selected including elevation, slope, aspect, relief, normalized vegetation index(NDVI), the engineering rock group, distance from faults, distance from roads, distance from drainages, the susceptibility of landslide hazard was evaluated and verified in certainty factor(CF) model, logistic regression model and CF-Logistic coupling model respectively, the location of landslide prone area in the study area is obtained, which provides reference for the prevention and control of geological disasters in this area.