The occurrence of natural fractures is an important parameter affecting the normal stress and tangential stress of the fracture wall,and the stress state of natural fractures is an important factor determining the magnitude of the ground construction pressure.Accurate calculation and prediction of the construction pressure plays an important role in hydraulic fracturing design and construction.According to the natural fracture occurrence and formation stress state,based on the criterion for fracture initiation and extension,a calculation model of the ground construction pressure is established.Using the actual fractured reservoir for calculation and analysis,it is found that:in normal fault and strike-slip fault,the smaller the dip angle is,the smaller the construction pressure is,and the smaller the construction pressure is when the azimuth angle is closer to 0°,180°,360° in normal fault,and the smaller the construction pressure is when the azimuth angle is closer to 90°,270° in strike-slip fault.In the reverse fault,when the azimuth angle is 0°～45°,135°～225°,315°～360°,the larger the inclination angle,the larger the construction pressure,when the azimuth angle is 45°～135°,225°～315°,the larger the inclination angle,the smaller the construction pressure,under the same inclination angle,when the azimuth angle is in the range of 0°～90°,180°～270°,the construction pressure is reduced with the increase of azimuth angle.For the same inclination angle,when the azimuth angle is within the range of 90°～180° and 270°～360°,the construction pressure increases with the increase of azimuth angle.Accurate calculation of the construction pressure according to the occurrence of natural fractures can provide a theoretical basis for the selection and optimization of field fracturing parameters.
In recent years, with the rapid impact of the internet economy on the traditional economy, online shopping has become increasingly popular among contemporary consumers compared to offline shopping. Particularly during the pandemic in recent years, when people were restricted from going outside, online shopping became the primary method of purchasing goods. A large volume of e-commerce review data contains consumers’ emotional tendencies toward products or services. This data not only provides valuable information about consumer preferences to businesses but also offers opportunities for improving products and services to maintain a competitive edge in the market. For businesses, gaining a deep understanding of consumer sentiment regarding their products or services, and responding with corresponding improvements or adjustments, is of critical importance. However, traditional sentiment analysis methods have significant limitations when processing complex long texts. Sentiment analysis based on sentiment lexicons is time-consuming and labor-intensive, and single machine learning methods often fail to achieve satisfactory performance in feature extraction and semantic understanding. To address these challenges, this paper proposes a deep learning model for e-commerce review sentiment analysis based on a Convolutional Neural Network (CNN)-Bidirectional Long Short-Term Memory (BiLSTM) network architecture, incorporating the multi-head self-attention mechanism from the transformer model. This model aims to enhance the robustness and generalization of semantic relationships in long-distance dependencies and emotional information in the text, compensating for the shortcomings of traditional methods. Comparative analysis with several traditional machine learning feature extraction algorithms and mainstream deep learning methods shows that the proposed model outperforms these methods across various metrics and exhibits excellent portability and scalability.
Based on the energy storage characteristics of phase change energy storage device,the optimal scheduling model of the integrated energy system with phase change energy storage heat pump considering the thermal inertia characteristics was established in view of the thermal delay and thermal attenuation in the heat transfer process,the PMV index was used to quantify the thermal load elasticity.Using Dymola and MATLAB to establish the model,taking the total cost of economic operation as the objective function,the capacity of peak-shaving and valley-filling,the capacity of renewable energy consumption,the environmental benefit and the safety in three different scenarios was compared and analyzed,and the 24-hour operation strategy on typical days in winter was optimized.The results show that the integrated energy system with phase change energy storage heat pump considering thermal inertia and thermal load elasticity has better economy and fault resistance.
Taking the data of Chinese a-share listed companies in Shanghai and Shenzhen from 2009 to 2021 as the research sample,the effect of government subsidies on ESG performance was empirically analyzed by using two-way fixed effect model.The results show that government subsidies have a significant effect on the improvement of ESG performance.The mechanism test shows that government subsidies can improve ESG performance through three mediating paths which are R&D Innovation driving effect,financing constraint easing effect,and analyst dis-closure supervision effect.The intermediary role of R&D Innovation is the strongest,financing constraints and analyst disclosure supervision of the intermediary role,for the government to guide the practice of ESG provides a reference basis.
Rural human settlement environment is an important part of the 13th Five-Year Plan and the National Beautiful Countryside Plan.Based on the background of rural revitalization strategy,taking Zhangye City as the research object,16 evaluation indicators from four aspects:ecological environment,economic development,infrastructure and public service according to the basic principles of rural human settlement en-vironment evaluation index selection were constructed.By using the entropy method,16 indicators of system layer and index layer were compre-hensively weighted to measure the development level of rural human settlement environment in Zhangye City from 2016 to 2020.The results are as follows.The development level of rural human settlements in Zhangye City presents a"W"shaped development trend,which has experienced four stages of descending-ascending-descending-ascending,with an overall upward trend.In Zhangye City,as an agricultural city,the inten-sity of use of mulch film is the most critical index affecting the development level of rural human settlements,and the recycling and utilization of mulch film has a high efficiency.The proportion of administrative villages that treat domestic sewage is relatively low,which indicates that Zhangye City has great defects in daily domestic sewage treatment,resulting in serious non-point source pollution of village environment.The weight of economic development indicators is relatively small,the main reason is that Zhangye City has a single rural economic income channel and has not formed a multi-industry integration development model.
