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.
The renewal of collective industrial land with the transformation of village industrial park as the main object is an important force for the development of stock land and the transformation of urban economy.Based on the logical model evaluation framework,a four-dimension evaluation conceptual model of resource input-action response-outcome output-comprehensive benefit was constructed.Qualitative analysis was adopted to evaluate the overall effectiveness of village level industrial park renewal by comprehensively using departmental statistical data,liter-ature and field research data.Based on the evaluation conclusion,policy recommendations are proposed as follows.In order to promote the transformation of village-level industrial parks to achieve high-quality development,investment channels should be expanded,long-term overall planning should be strengthened,precise investment should be implemented,governance mechanisms should be innovated,and disordered com-petition should be restrained by policy guidance.
The traditional optimization method of the internal space design of rail transit station directly calculates the passenger flow distribu-tion without zoning the internal function of the station,which results in long delay time of passenger flow.A discrete Firefly algorithm approach to the design optimization of the internal space of rail transit station buildings was proposed.The internal function of the station was partitioned and the passenger flow was further distributed based on the discrete firefly algorithm according to the rail transit station partition,so as to rea-lize the optimal design of the internal space of the rail transit station building.The experimental results show that this method has better capaci-ty of passenger flow in the inner space of rail transit station and is worth popularizing.
With the acceleration of the coordinated development of smart city infrastructure and intelligent connected vehicles,the rapid deve-lopment of smart transportation,urban governance,5 G communication,driverless and other fields has made the phenomenon of complex poles and scattered boxes at traffic crossings.The systematic layout of smart city infrastructure and intelligent network equipment were accomplished by innovating the first"double intelligent standard intersection"design method of multi-pole integration,multi-sense integration and multi-box integration.The design concept has been implemented in the high-level unmanned driving demonstration zone in Beijing,and the integrated function of vehicle-road-cloud coverage has been achieved on urban roads within 60 square kilometers.
Through using a sample of listed companies in the A-share market companies from 2010 to 2021,the impact of digital transformation on enterprise value and the boundary role of information disclosure quality were explored.The results show that digital transformation is posi-tively correlated with enterprise value.The quality of information disclosure plays a positive moderating role in the relationship between digital transformation and enterprise value.Further research shows that the positive impact of digital transformation on enterprise value is more significant in non-state-owned enterprises and enterprises in the eastern region.Some empirical evidences for enterprises to accelerate digital transformation and government departments to guide enterprises to develop in high quality are put forward.
Digitalization is an important direction for the upgrading of China's industrial structure,which plays an important role in promoting the value-added of new industries,the reorganization of factor allocation and the development of new markets.Two kinds of manufacturing up-grading evaluation index from the output structure and employment structure was constructed,and Dagum Gini coefficient was used to analyze the regional differences and spatio-temporal pattern of industrial structure upgrading in China.At the same time,the influencing factors of in-dustrial structure upgrading into internal factors and external factors were divided,and spatial panel data model was used to analyze the mecha-nism of industrial structure upgrading in China based on two kinds of spatial weights.The results show that the upgrading level of China's in-dustrial structure has been continuously improved from 2011 to 2020,and the upgrading index of industrial structure has increased from 0.886 to 1.434,with an annual growth rate of 5.42%.The regional difference is decreasing,and the regional difference mainly comes from the inter-group difference,and the intra-group difference is the largest in North China,East China and South China.Spatial econometric model estimates show that digitalization has a significant role in promoting the upgrading of industrial structure.Technological innovation,factor endowment,ownership structure and export level contribute to the upgrading of industrial structure,while human capital and foreign technology spillover have inhibitory effects on the upgrading of industrial structure.
At present,with the rapid development of breeding enterprises in our country and the continuous improvement of large-scale breed-ing enterprises,the amount of pollution produced by large-scale farming is increasing rapidly and relatively concentrated,resulting in increasing-ly prominent environmental pollution problems.Aiming at the environmental pollution problem of large-scale farming enterprises,the dynamic model of the environmental behavior system of large-scale farming enterprises by using the basic flow rate tree modeling method was firstly es-tablished,and then the minimal feedback schema step by step by step by using the minimal feedback schema generation method was obtained.On the basis of the minimal feedback schema,a feedback schema of the growth ceiling with practical significance was constructed.Finally,some practical suggestions are put forward to enhance the environmental behavior of enterprises.
This study aims to promote the green development of China's civil aviation and achieve carbon peak and carbon neutrality goals.By constructing an evolutionary game model involving the government,airport enterprises,and civil aviation transport enterprises,different sce-narios were investigated to identify stable evolutionary strategies for each party.Numerical simulations were used to analyze the impact of key parameter changes on strategic choices.The research indicates that government incentive measures and penalty strength can facilitate green de-velopment,but excessively high or low subsidies are detrimental to the adoption of green strategies by civil aviation transport enterprises.Therefore,tailored incentive policies should be formulated by the government based on the cost structures of airport enterprises and civil avia-tion transport enterprises to support the sustainable development of green civil aviation.
Based on the industrial life cycle theory and decision-making model,1 239 listed high-tech enterprises from 2017 to 2021 were used as research samples to examine the impact of market competition on enterprise R&D investment and the regulating effect of internal control.The empirical results show that for high-tech enterprises,the intensification of market competition promotes the increase of R&D investment to a certain extent,and the internal control of enterprises has a nonlinear regulating effect on the relationship between the two.When the quality of internal control is low,the improvement of internal control will inhibit the positive impact of market competition on R&D investment.When the quality of internal control breaks through the critical point,the improvement of internal control will promote in turn the positive impact of market competition on R&D investment.
Taking the"Environmental Protection Tax Law of the People's Republic of China"implemented in 2018 as an exogenous impact,and taking the data of manufacturing listed enterprises and provinces from 2015 to 2020 as samples,whether environmental regulation could promote the improvement of corporate financial performance was explored.The results are as follows.Environmental regulation has a significant effect on corporate financial performance,and it improves financial performance by stimulating enterprises to carry out technological innovation.Heterogeneity analysis finds that the promotion is more remarkable for non-state enterprises and enterprises in the eastern region.These are helpful to understand the internal mechanism between the two,and strong empirical evidence for promoting the coordinated development of ecology and economy are put forward.
It can provide effective evidence for expressway traffic control and construction planning by effectively identifying congestion of ex-pressway.A methodology of congestion discrimination was proposed based on travel time threshold.The travel time collections of all vehicles were extracted based on toll gantry data.The travel time collection was clustered and analyzed by clustering algorithm,and the travel time threshold of different congestion levels was calibrated according to the clustering results.The congestion condition will be discriminated based on the congestion travel time thresholds.The results indicates that the overall operation of Guangzhou expressways is good,with 80%of peri-ods and sections being in a smooth state.
The implementation of Solvency Ⅱ of Phase Ⅱ project has put forward higher requirements for insurers'risk management,and the calculation of economic capital has received attention from insurers.Nested stochastic simulation method is the traditional method for calculating economic capital,but most companies cannot afford the time cost and computing power required by this method.A neural network algorithm-based economic capital calculation method was proposed.The results show that the computation time is reduced by about two-thirds compared with the nested stochastic simulation method,and the error rate can be controlled within 3%.
Under the background of"dual-carbon"target,cities as the important subjects of low-carbon strategy implementation,have intro-duced many challenges.In order to help the sustainable development of urban ecology,the evaluation index system was constructed,the data was qualified and the reliability and validity were analyzed,PCA algorithm was used to degrade the data and extract the features,and the key influencing factors were determined by interpreting and analyzing the weights of the principal components.The result shows that the key factors affecting the construction of low-carbon cities are grouped into eight categories,including environment,energy and buildings,with a total of 11 indicators.Accordingly,the optimal path and feasible strategies for the construction of low-carbon cities are explored to promote the construc-tion of"dual-carbon"goals.
Aiming at the problem of multi-attribute evaluation with triangular intuitionistic fuzzy number,a multi-attribute evaluation method based on triangular intuitionistic fuzzy cloud model was proposed,which reflected the degree of support,non-support and hesitation of uncertain information.Firstly,considering the fuzziness and hesitation of decision makers in the evaluation process,the evaluation information of decision makers was transformed into triangular intuitionistic fuzzy numbers.Secondly,the triangular intuitionistic fuzzy decision matrix was constru-cted by calculating the numerical characteristics based on cloud model theory.Thirdly,the decision matrix was integrated to get the evaluation synthetic cloud and draw the three-dimensional cloud map.Finally,the results were analyzed by computing cloud similarity,and reasonable suggestions were put forward for the evaluation object.An example shows that the method based on triangular intuitionistic fuzzy cloud model can be effectively applied to the multi-attribute evaluation problem.
From the perspective of FDI quality,the provincial panel data from 2007 to 2020 were selected to study the relationship between en-vironmental regulation and industrial structure optimization in the Yellow River Basin.First,the influence mechanism of the three variable was revealed.Secondly,the impact of environmental regulation on industrial structure optimization through FDI quality intermediary effect was em-pirically tested.Finally,through the nonlinear model,the essence of the mediating effect of FDI quality was clarified.The results are as follows.Environmental regulation hinders the optimization of industrial structure through the mediating effect of FDI quality.There is a U-shaped rela-tionship between environmental regulation and FDI quality.Therefore,in the process of high-quality development of the Yellow River Basin,The choice of environmental regulation intensity plays a key role in improving the quality of FDI and then optimizing the industrial structure.
Taking China's movie theme parks as an example,the visitor review data of multiple tourism websites were collected,and the LDA theme model method,co-occurrence network analysis method and sentiment analysis method was used to study the tourist review text.The results show that the domestic movie theme park visitor reviews can be divided into four themes:tourism service theme,tourism landscape theme,overall perception theme and activity experience theme.Combined with the results of co-occurrence network analysis and sentiment analysis,the current situation and pain points of the prospect area are identified,which provides more accurate tourist preference information for cultural tourism enterprise operators,and also provides rele-vant theoretical and data support for the subsequent management and decision-making of enterprises.
