bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Biomechanical Application of Fracture Reduction Fixator Based on Finite Element Analysis
Authors: Wu Kai , Ma Jianxiong , Du Yuren
Published: April 2021

This article uses CAXA 3D solid design software to model the fracture reduction fixator, and assemble the model according to the requirements of clinical medicine. Obviously apply 50N, 100N, 150N, 200N axial load to the model, and obtain the relationship between axial load force and displacement. The stiffness of the model calculated by SPSS23.0 statistical analysis software is 88.5N/mm. The stiffness of the fracture reducer measured by the biomechanical model was 85.4N/mm, and the ratio between the two was 1.037, which was within the error range. Prove that the model and calculation method established in this study can provide reference for clinical medicine.
RETRACTED: Research on Innovation of Ideological and Political Teaching Mode for Chemical Engineering Courses Based on Big Data Technology
Authors: Xia Haoyun
Published: April 2021

Aiming at the current application of big data technology, this paper proposes a micro-video-based ideological and political teaching and learning system for chemical engineering courses. In order to realize the system, relying on the course of “Light Chemical Equipment and Design”, part of the main content of the micro video is designed, and the ideological and political content is run through the entire course; Then, design the system network topology, client and server functions, and finally deploy the system on the Alibaba Cloud server, and design an evaluation method to explore the application effect of the system.
Design of Multi-mode Heterogeneous Fusion Terminal for Power System
Authors: Xiao Yunjie
Published: April 2021

With the increasing demand of users and power supply quality in the power grid market, this puts forward higher requirements on the power system. However, the traditional power system has many limitations. People need to be able to upgrade on the basis of the traditional power grid to adapt to changing requirements. The purpose of this paper is to study the design of multi-mode heterogeneous fusion terminal in power system. This article is based on two wireless network technology solutions, GPRS wireless public network and LTE-230 wireless private network, a hardware development platform with STM32F107VCT6 microprocessor as the core, and a μ C/OS-III embedded real-time operating system software development platform, has designed the multi-mode heterogeneous fusion terminal of the electricity information collection system. This article deeply analyzes the demand for multi-mode heterogeneous fusion terminals of the electricity consumption information collection system, which is mainly used for the collection of electricity consumption information and the marketing and distribution automation management of power services; then it analyzes the work of the GPRS network and the LTE-230 network Principle and network system structure. This article designs the communication driver and application program, and analyzes the software architecture in detail. According to the logic processing structure of the internal data of the multi-mode heterogeneous fusion terminal, this article designs the data forwarding process in detail. In this paper, protocol conversion test, interface test and communication test are carried out on multi-mode heterogeneous fusion terminal. The test results show that when the system buffer K is 2 or 4, that is, if the average size of each message in the system is 100 Bytes, and the buffer is set to 800 Bytes, the system loss rate will approach zero.
Research on Smart Learning System Model
Authors: Xu Jian
Published: April 2021

With the development of computer science in our country, more and more intelligent products appear in people’s daily lives, bringing convenience to people’s lives. In the education industry, an intelligent learning system has also emerged. After learning the relevant knowledge of the construction of the intelligent learning system and the Apriori algorithm, this article builds the intelligent learning system based on the Apriori algorithm, and take the university physics department as an example to study and analyse the function and realization of the system.
Research on Information Encryption Algorithm under the Power Network Communication Security Model
Authors: Yang ChunYan , Ling Ying , Li Xin
Published: April 2021

With the continuous development of current high-tech, network communication is quickly popularized in power automation monitoring systems, and colleagues have also brought many hidden dangers in communication security. This paper proposes a model that adapts to the security of power network communication. Based on the information encryption algorithm, this model can fully guarantee the security of both ends of the data transmission and can be applied to other network communication modes. Based on the power network communication security model, this article can use high-strength information encryption algorithms to encrypt data in the network to prevent the data transmitted in the network from being stolen or modified. The power network communication security model studied in this article mainly includes information encryption and decryption algorithms, client environment, and an SSL-based information encryption transmission protocol. Through analysis, it can be understood that the encryption and decryption algorithm is to perform MD5 transformation on key data and key strings, and the other is to use DES as the encryption algorithm before transmission. The experimental research results show that in the construction of power network communication, the power communication network is one of the most basic facilities in the development of the power grid. It is necessary to ensure the safety and economic operation of the power grid, and to improve the information level of the power grid enterprises and the network security protection system.
Research on SVM Remote Sensing Image Classification Based on Parallelization
Authors: Yang Qiuhong
Published: April 2021

With the development of technology, the feature dimension and data volume of remote sensing image classification have increased rapidly. However, when remote sensing image classification based on support vector machine (SVM) is used for large-scale data calculation, there are significant limitations in training time. This paper focuses on the parallel processing method of support vector machine (SVM). Based on the popular hybrid parallel support vector machine, a hybrid parallel support vector machine based on sample cross combination is proposed, and carried on the simulation experiment analysis in the stand-alone environment.
Power Load Forecasting Model Based on Deep Neural Network
Authors: Yuan Jian , Wang Jiaying , Cheng Qing , Sun Jianqiao
Published: April 2021

Aiming at the problems of the traditional power load forecasting model, based on the analysis of the traditional DNN neural network model, a PSO dual improvement and optimization power load forecasting model is proposed. In this model, the discrete particle swarm algorithm is used to determine the DNN network architecture, and then the particle swarm algorithm is used to optimize the parameters of the neural network to obtain a model with the best structure and parameters. Finally, it is verified by simulation, and the results show that the above method is feasible and has high prediction accuracy.
Research on Talent Cultivation Methods of Public Art Courses in Universities Based on Information Technology
Authors: Zhang Jing
Published: April 2021

In recent years, under the development of information technology(IFT), the work of high-efficiency education reform has been gradually carried out. IFT is widely used in various courses of higher education. However, art courses are no exception, and IFT is also highly effective talents. The training model has a great effect. Based on the blessing of IFT, this article studies the talent training model of public art courses in my country’s colleges and universities(CAU), and proposes some innovative talent training models, which have greatly promoted the training of IFT in the public art courses of universities. Application in the pattern. Based on years of practical work experience in CAU, this article attempts to analyze the existing problems and specific solutions of IFT teaching in the current information teaching of university public art courses. Therefore, this article first analyzes the advantages of IFT in the teaching of public art courses in CAU, then analyzes the shortcomings in the teaching process of public art courses in CAU, and finally discusses the application strategies of IFT in college public art courses. Carry out the teaching of public art courses in CAU, and cultivate high-quality talents who keep pace with the times. The teaching advantages of public art education courses from the perspective of IFT are discussed, and then the problems and countermeasures in the teaching of public art courses from the IFT perspective are discussed. Result analysis statement, Continue to deepen the informatization of teaching reform and give full play to the application of informatization technology in the teaching of public art courses in CAU.
Research on the Application of Artificial Intelligence Technology in Island Tourism
Authors: Zhang Yingchao , Pei Yingying
Published: April 2021

In this paper, the specific application of artificial intelligence technology in the field of island tourism is launched, and an intelligent recommendation system for island tourism is designed. The system considers the data characteristics of island tourism activities and the influence of geospatial factors. First, the relationship between the data is clarified by constructing the island tourism information ontology, and then geographic information data system (GIS) is added to the system architecture design. In terms of algorithm, artificial intelligence algorithm is used in combination with different recommendation methods. Finally, the feasibility of the scheme is proved through experiments.
A Study on the Integrated Development of Artificial Intelligence and Tourism from the Perspective of Smart Tourism
Authors: Pei Yingying , Zhang Yingchao
Published: April 2021

In order to provide better travel experience for users under smart tourism, a data model that can be used for tourism analysis which is constructed by combining big data, Hadoop and crawler technology. Then, we combine with Item-based recommendation algorithm and the technology collected by crawler technology based on this model. It can provide an example of the specific integration application of big data analysis model and tourism. The results showed that the analysis model can highly recommend scenic spots favored by tourists. So it can provide reference for the integration of ARTIFICIAL intelligence and tourism, as well as a concrete example for the integration of artificial intelligence and tourism in the future.
Construction of College English Teaching Model in the Era of Artificial Intelligence
Authors: Zheng Huixi , Miao Jing
Published: April 2021

The development of artificial intelligence (AI) technology provides new thoughts and ideas for the reform of English teaching(ET) mode. This article understands the related knowledge of AI technology and ecological pedagogy, and studies and analyses the current situation of college ET in my country, and discusses how to use AI technology to reform my country’s ET model. Relying on data mining technology and deep learning algorithms in AI, the ET model gradually develops in a better direction, making it a virtuous circle.
Research on Artificial Intelligence-based English Writing Blended Teaching Mode
Authors: Chong Daojing
Published: April 2021

In this artificial intelligence-based English writing blended teaching model is in the stage of research and innovation, this article uses a university English major as the experimental object, and launched a 19-week teaching experiment. The combination of advantages improves the traditional English writing teaching mode and establishes an artificial intelligence English writing mixed teaching mode. The results of the study show that this model can improve students’ English writing level while improving students’ English writing level, and can also increase students’ interest in English writing.
Study about Impact of Big Data Technology on the Diversity of Ideological and Political Teaching Methods
Authors: Zhou Yi , Cao Yanxia
Published: April 2021

Big data(BD) technology is a kind of information technology that has emerged in my country in recent years. It also plays a important role in the ideological and political(IAP) teaching of college education. Making use of BD technology to implement reforms in IAP education and breaking the traditional IAP teaching mode is an inevitable requirement for reforms. At the same time, IAP education can be carried out with high efficiency and high quality. This article analyzes the impact of BD technology on the diversification of IAP teaching, and gives some examples of the application of BD in IAP teaching. And the study finally gives suggestions on IAP teaching under BD.
RETRACTED: Virtual Restoration of Mural Color Based on Artificial Intelligence
Authors: Gao Lei
Published: April 2021

In recent years, the development of artificial intelligence can be described as rapid change, which provides a safer method for the virtual restoration of mural colors. This article mainly studies the virtual restoration of mural color based on artificial intelligence. This paper constructs the minimum spanning tree of the segmentation line and transforms it into a graph, finds out the closed sub-ring as the segmentation line from the graph, and uses the depth-first search algorithm to extract the surface in the segmentation line area. This paper performs threshold segmentation on the mural image to obtain the drop-off area. The threshold T is selected based on experience; the pixel points of the same attribute are merged by 8 adjacent methods, that is, the pixel value is 1, and then the closed operation is used to achieve the purpose of continuous drop-off information. In order to control the tendency of global optimization and neighborhood correlation, a proportional parameter needs to be added, and the parameters are adjusted to obtain a balance between neighborhood correlation and global optimization, and the best matching point can be obtained. The data shows that the average objective evaluation score of Criminisi algorithm is 0.794603, and the average objective evaluation score of the improved algorithm in this paper is 0.848665. The results show that artificial intelligence technology plays an extremely important role in the virtual restoration of mural colors.
Innovation Strategy of Network Ideological and Political Education Based on Big Data
Authors: He Linjian
Published: April 2021

In the context of the Internet era, the diversity and authenticity of data collections provide visual data support for work decisions and process optimization. NIAPE(Internet ideological and political education) is an important educational reform that adapts to the development of the Internet era. In view of the single teaching method, insufficient grasp of the characteristics and laws of network education, and low awareness of network utilization, in order to achieve educational results, it is necessary to know how to skillfully use the advantages of the current network age for innovative applications, combining education with precision objects and key groups of “small and beautiful”, and innovating education and teaching from the aspects of curriculum optimization management, precision push, and perfect evaluation mechanisms.
Construction of Civil Engineering Teaching System Based on Data Mining Algorithm and Big Data Technology
Authors: Wang Xiaowei
Published: April 2021

Under the big data(BD) technology, colleges and universities pay more and more attention to educational technology, so as to follow up with modern information, digitization, and visualization. The courses of civil engineering teaching with traditional teaching methods and single knowledge of students are profit-only, applying data mining(DM) technology and BD technology to realize positive thinking mode. This article first gives a brief overview of DM technology and BD technology, and then discusses the strategy of applying BD technology in teaching of civil engineering professional courses, and finally applies BD DM technology to the construction of civil engineering teaching system, to realize the intelligent teaching mode. Based on DM technology and BD technology, this paper comprehensively studies the construction of two technologies in the civil engineering teaching system of colleges and universities. This article combines the new concept of constructing attention to teaching, expounds the advantages of DM algorithm in the construction of civil engineering teaching system, and briefly analyzes the composition and development of the networked civil engineering teaching system platform. At the same time, this article also in-depth research In the classification algorithm of the DM algorithm, the k-nearest algorithm is discussed, and for the efficiency of their construction in the civil engineering teaching system, the visualization research is carried out from the operation efficiency of the algorithm steps and other aspects and the organization of the data set. Based on the above research, the optimization schemes of particle swarm algorithm and ant colony algorithm are designed, and a parallelized early warning system model is realized using GPU based on CUDA platform. In the above research, the two algorithms were compared and tested, and the efficiency of the algorithm in the construction of civil engineering teaching system was verified. Experimental research results show that the cosine correlation analysis based on DM algorithms and the hybrid particle swarm algorithm can effectively integrate BD technology to construct a civil engineering teaching system and improve the operating efficiency of the system.
Design of a Hybrid Classroom Teaching Quality Evaluation System Based on Information Technology
Authors: Chen Xiao
Published: April 2021

With the rapid development of today’s information technology, it is an inevitable trend for the reform and development of education and teaching in colleges and universities to promote education modernization through education informatization. Information management has penetrated into the teaching and management of colleges and universities. Based on information technology, this paper studies the design of a data mining algorithm-based hybrid classroom teaching quality improvement evaluation system model, which fully reflects the quality of hybrid classroom teaching based on information technology in universities. In order to accurately grasp the current status of the current mixed classroom teaching quality, this experiment has been collected, sorted, and studied in recent years for analysis. A neural network algorithm is used to construct a model for it. This algorithm is combined with a questionnaire survey method to screen the mixed classroom teaching quality evaluation indicators of college information technology. Finally, a BP model is constructed through the classroom teaching quality and the model calculation samples are selected., The teaching quality can be obtained after calculation. Experimental research results show that with the advent of the information age, the development of blended teaching is divided into three stages. The first is based on technology, and the second is based on the interactive method of online and offline technology teaching. The third is to focus on the learning experience of learners. Blended teaching is a sublimation of traditional teaching mode and a return to traditional concepts. This brand-new teaching model will surely become the new normal of the education model in the future.
RETRACTED: Reform and Innovation of Higher Fine Arts Distance Education under the Background of Big Data
Authors: Li Wei
Published: April 2021

The development direction of online teaching is personalized and customized teaching based on user needs. The application of big data(BD) technology to the art remote network teaching platform can effectively solve the problems of the huge and chaotic amount of teaching resources, the difficulty of user selection, the weak management of the network learning process, the inefficient use of teaching resources, and the lack of user role sense. The purpose of this article is to study the reform and innovation of higher art distance online education under the background of BD. Methods such as literature analysis and BD technology closely link BD with education reform and innovation. This article uses BD technology methods to discover and grasp the laws of higher art distance online education in colleges and universities(CAU), build a higher art distance online education innovation system in CAU, and then promote the innovation of college art distance online education. This paper proposes a distance education innovation system for CAU from the perspective of BD, and further adopts the method of structured system analysis to carry out an in-depth study of the innovation system of CAU distance education of fine arts from the perspective of BD. This article points out that the college network ideological and political education innovation system under the BD perspective is composed of internal and external elements such as ideas, mechanisms, paths and carriers. Based on the analysis of the realistic basis of higher art education innovation in CAU from the perspective of BD, this paper puts forward the realistic possibility of the innovation of higher art distance network education under the vision of BD. Experimental research shows that there are more than 700 million netizens in my country, among which netizens are mainly 20-29 years old, accounting for 30.30% of the total number of netizens. In addition, students are an important part of netizens, reaching 25.4%.
Innovation Mode of Art Education in Colleges and Universities Based on Big Data
Authors: Liu Rong
Published: April 2021

In this paper, firstly, the author expounds the current situation and development of modern art education in China in the digital information age,and points out the shortcomings of the current art education. Then a new interactive data teaching method is proposed, which is analyzed from three parts: the reason of the new interactive data teaching design, the curriculum design and the innovation of the curriculum design. Finally, from the perspective of practical teaching cooperation with enterprises, this paper puts forward scientific innovation education strategies.
RETRACTED: The Innovation of Music Teaching Mode Under the Background of Big Data
Authors: Liu Jie
Published: April 2021

Technological progress, that is, large data scale, fast data extraction and analysis speed, and data structure diversity are the essential characteristics of big data. Big data is the key historical factor to promote the current development of the times. Facing the future education reform and development, information technology has become an innovation. With the support of big data technology, MOOC centered teaching mode and computing research paradigm are gradually becoming mature and become an important development trend of teaching research. Develop learning modules and suggest specific core courses in which their coverage may find the right context. In this paper, we study the participatory teaching method and record our classroom experience in these interventions. Specifically, we discussed learning outcomes, module content, their design and implementation, student assessment results and lessons learned.
Future Development Trend of “New Retail” and E-Commerce Based on Big Data
Authors: Wang Yanyan , Chang Jiancong
Published: April 2021

In recent years, my country’s “new retail” and E-Commerce (EC) have developed vigorously and have become the world’s largest offline shopping market on the Internet. At the same time, with the development of information technologies such as cloud computing and the Internet of Things, rapidly expanding data has brought mankind into the era of big data(BD). It has become possible to use BD technology to analyze the development of regional “new retail” and future EC and provide corresponding guidance. The purpose of this article is to study the future development trend of “new retail” and EC based on BD technology. Based on the development status of “new retail” and EC in Anhui Province, this paper selects Hefei and Huangshan as the research objects. After referring to numerous theoretical studies, this article has determined the factors affecting the development of regional EC, such as informatization infrastructure, logistics services, etc. At the same time, it uses the range of standardization method and selects representative indicators to construct a regional “new retail” and EC development level evaluation index system. Finally, combining the evaluation results and the development status of various regions, taking Hefei and Huangshan as examples, proposed the concept of building a regional third-party “new retail” and EC trading platform and creating regional product integration services. This article combines BD to deeply analyze the influencing factors that traditional trade and circulation companies face in the process of strategic transformation in the development of “new retail”. This article explores the strategic transformation paths and measures for traditional trade and circulation enterprises to develop the “new retail” business model Draw on. Investigation and research show that, through the evaluation model, this article concludes that Hefei’s online retail sales are higher than Huangshan’s, with an annual growth rate of more than 3%, which is also high relative to the province’s growth rate.
Information Management Strategy of Bridge Construction Technology Based on Big Data
Authors: Meng Fancheng
Published: April 2021

With the rapid integration of big data, cloud computing, BIM and other new technologies into construction enterprises, the degree of information of bridge construction is gradually deepened. This process is usually very complex, there are many influencing factors, and the construction progress is difficult to control. This paper summarizes the fiber composite materials which have potential application in Bridge Engineering in recent years. This paper first discusses the development prospect of carbon fiber, and then briefly introduces the mechanical properties of carbon fiber composite laminates. Referring to relevant literature, this paper introduces BIM Technology in detail.Based on the current situation and application advantages of BIM technology,it fully understands the practical application of BIM Technology in bridge engineering design, construction stage and later operation and maintenance. Their tensile strength, elastic modulus, longitudinal and transverse thermal expansion are introduced in detail.The results show that BIM Technology has been widely used in bridge engineering projects. In 2015, the Growth rate of BIM technology usage in construction industry country a was 1.536.
Optimization Design of Green Building Landscape Space Environment Based on VR Virtual Technology
Authors: Wang Xiaochen
Published: April 2021

At present, China does not pay enough attention to the cognition of a person’s specific psychological behavior feelings for green buildings in China, and it fails to introduce the psychological behavior feelings of specific people into the overall design and construction process of green buildings in China. In view of these problems, this paper puts forward the research of green building landscape space environment optimization design based on VR virtual technology. According to the current situation of green building landscape space environment design in China, this paper proposes the construction of objective function, and calculates the optimization satisfaction value of square and pedestrian street, and obtains the average satisfaction of two kinds of landscape space are 0.6 and 0.46 respectively. The results show that the facilities and green area are well planned, with high satisfaction. Through the comparative analysis of the effect, interactive experience and viewing effect between traditional architectural design and VR architectural landscape design, it is concluded that VR architectural landscape design is obviously superior to traditional design. VR virtual technology provides technical support for the optimization design of green building landscape space environment.
Image Pattern Recognition Algorithm Based on Improved Genetic Algorithm
Authors: Kuang Qing
Published: April 2021

Image recognition is an important part of artificial intelligence. In recent years, the technology has been developed rapidly and has been widely used in various fields. However, the existing image recognition technology is still not perfect, especially in the complex environment; the recognition accuracy still needs to be improved. To solve this problem, this paper proposes an image pattern recognition algorithm based on improved genetic algorithm. There are many algorithms for image recognition, but the mainstream algorithm is genetic algorithm. Genetic algorithm also shows its unique advantages in the field of image recognition. Aiming at the problem that the accuracy of existing image pattern recognition is not enough, this paper optimizes and improves the traditional genetic algorithm of image recognition. By improving the calculation method and genetic steps, the adaptability of genetic algorithm in the field of image recognition is improved. In order to further verify the actual effect of this algorithm, the corresponding comparative experiments are carried out. The experimental results show that the accuracy of the traditional genetic algorithm is 73.7%, and the improved genetic algorithm is 98.3%. The analysis shows that the improved genetic algorithm can better meet the actual needs of image pattern recognition. According to the characteristics of image recognition, the genetic algorithm can improve the accuracy and robustness of image recognition while ensuring the image quality.
Single Image Super Resolution Reconstruction Algorithm Based on Deep Learning
Authors: Kuang Qing
Published: April 2021

Super resolution image reconstruction technology is the core technology in image processing, which provides technical support for most of the intelligent devices for target tracking and target detection. However, the existing image acquisition stage will cause extra high cost to improve the image resolution. Optimization algorithm is one of the best ways to solve this kind of problem. At present, there is no substantial breakthrough in this field in China. Therefore, this paper studies single image super-resolution reconstruction algorithm based on deep learning. In this paper, the application of super-resolution reconstruction algorithm in single image is discussed. The analysis shows that the application of deep learning in this field is shallow and has a large optimization space. Especially for the existing main problems, the traditional algorithm is optimized and improved. According to the demand of resolution reconstruction, combined with the latest deep learning method, the accuracy and robustness of the algorithm are further improved. At the same time, it effectively improves the comprehensive performance of the model. In order to further verify the actual performance of the proposed algorithm, the corresponding comparative experiments are established. The experimental results show that the proposed algorithm has obvious advantages over the traditional fsrcnn algorithm, especially when the PSNR of dataset 4 is 2, 3, and 4 times, it can increase 0.41 dB, 0.58 dB and 0.52 DB respectively. Analysis shows that this algorithm has obvious advantages and achieves ideal results.
Continuous Fast Terminal Sliding Mode Control of Permanent Magnet Linear Synchronous Motor
Authors: Shen Liang , Sheng Hu
Published: April 2021

The permanent magnet linear synchronous motor(PMLSM) with direct driving method, which can obtain faster speed and acceleration, has been widely used in the industrial field in recent years. However, due to the lack of transmission links and the influence of nonlinear factors, the control of PMLSM is more difficult. In order to solve the problem that the control system is easy to be affected by nonlinear friction, external disturbance and other uncertain factors, the mathematical model of PMLSM with uncertain factors is established, and a continuous fast terminal sliding mode control(TSMC) method is proposed in this paper. The exponential reaching law(ERL) is used in this method to make the motion track reach the sliding surface quickly and effectively weaken the chattering of the system. The singular problem in the fast TSMC is solved by selecting the parameters to ensure the robustness of the system and improve the response speed of the system. The simulation results show that the continuous fast TSMC method has the ability of accurate position tracking and fast response of the system, so it has great practical value.
Thoughts on building an intelligent integrated management system of agricultural environment
Authors: Wang Feng
Published: April 2021

In modern agricultural production, environmental factors are very important. It determines not only the production cost and benefits, but also the success and difficulty of agricultural production. Agricultural environmental monitoring is the foundation of agricultural environmental management. It is vigorously developing agricultural environmental monitoring to meet the environmental needs of different varieties and planting models. Organically combining agricultural production equipment and agricultural operations is the research focus of agricultural informationization at this stage. In order to better serve the entire industry chain of agricultural forecasting, production and sales, this paper proposes to create an integrated intelligent management system that integrates pre-production, mid-production and post-production.
Research on Forecast Model of Elderly Pension Expenses Based on Data Mining Algorithm
Authors: Zhu Bin , Zhang Li , Zhang Yonggang
Published: April 2021

With the intensification of the aging of our country’s population, research on how to better protect the living standards of the elderly, reduce the burden of the working population to support the elderly, and ensure the orderly and healthy development of the society, is currently the focus of attention. In order to prevent aging from bringing further negative impacts on our society or economy, this paper uses data mining algorithms as the research basis and uses time series models to make effective predictions. Therefore, this article first decomposes these data by analyzing the characteristics of elderly consumption data. The decomposed sequence has short correlation characteristics, and the prediction accuracy is significantly higher than that of the traditional time series model. However, this kind of time series model can only predict some offline data. In order to make it can be used for dynamic data prediction, this paper uses RBFNN online prediction algorithm. The RBF neural network is partially improved, and the parameters are calculated by improving the later SGD algorithm. The experimental conclusion shows that the prediction accuracy and efficiency of this algorithm are obviously more accurate than the neighbor clustering online training algorithm, and it achieves more effective online prediction. It can be concluded that the role of the elderly social security budget in economic management can fully reflect the income and expenditure of the elderly social security funds, improve the efficiency of fund use, and establish a unified national social security budget, thereby reducing the impact of aging on society Negative impact.
The Early Warning Method of Drug Adverse Reaction Monitoring Based on Data Mining Algorithm Was Studied
Authors: Zhu Bin , Zhang Li , Zhang Yonggang
Published: April 2021

With the continuous progress of modern society, human rights are becoming more and more perfect, especially the medical system, because of the inevitability of development, at this stage has achieved a lot of proud results, but this can not meet the modern people’s pursuit of health. Because the use of resources in the industrial society has led to the emergence of many viruses that have not been seen many, so now more and more kinds of drugs, we are considering more and more things, one of which is about adverse reactions to drugs. Therefore, this paper is based on this data mining algorithm to monitor adverse drug reactions early warning method. Based on the security of the user’s personal privacy data, this paper proceeds to monitor the drug reaction in real time as the way, adopts the data mining algorithm as the main intelligent means used, compares it by consulting the domestic and foreign literature, and experiments with sandbox simulation as a modeling method, and finally results in the experimental results. The results show that if we can monitor drug reactions in real time, we can monitor adverse reactions early.
Optimization Design of Civil Engineering Construction Schedule Based on Genetic Algorithm
Authors: Shen Li , Zhang Guihong
Published: April 2021

With the acceleration of the modernization process in our country, the construction and construction of civil engineering projects are becoming more and more frequent. As an important and complex system work, the progress control and optimization in the civil engineering construction process is very important. It is not only directly affect the overall planning and layout of the entire project, as well as the overall construction quality of the project. For this reason, this article applies genetic algorithm to civil engineering construction, and hopes to use genetic algorithm to optimize the construction progress of civil engineering. Taking the construction of a hydropower station in our province as an example, the genetic algorithm was specifically applied to the schedule optimization design of the project, and three optimization schemes were analyzed. After the investment amount and initial investment amount of each project and sub-project. By comparison, it is found that under the third optimization plan, the investment in the construction of the main dam, the construction of the auxiliary dam, the reinforcement and reconstruction of the sluice gate, the construction of the upstream and downstream rivers and the construction of the surrounding buildings of the project has increased from the initial 535.69 million yuan, 369.42 million yuan, 136.57 million yuan, 125.98 million yuan and112.34 million yuan fell to 512.59 million yuan, 340.12 million yuan, 113.58 million yuan, 105.92 million yuan and 98.74 million yuan, which greatly reduced investment costs. Research shows that genetic algorithm is beneficial to optimize the progress of civil engineering construction, and has a positive effect on reducing construction costs and improving project quality.
Research on the Guidance Technology of Air-To-Ship Missile Attacking Nearshore Ship
Authors: Wei Jiayu , Li Haijun , Wang Tianran , Wang Yiming
Published: April 2021

In the complex nearshore context, attacking warship has been one of the important combat tasks to air-to-ship missile. Due to the island environment and anti-air facilities, hitting effect significantly decreases which calls for higher requirements for guidance technology. This paper hackles the development of air-to-ship missile used to attack nearshore warship, expounds vital guidance technology like the TV guidance technique, the man-in-loop infrared imaging guidance technology, multi-mode compound guidance, etc., and analyzes the trend of the guidance technology of anti-aircraft missile for nearshore combat, which can provide valuable technical reference for study of new type of air-to-ship missile and the nearshore combat.
Research on the Influence of Rumors on Consumers’ Irrational Purchasing Behavior under Public Crisis in the Era of Big Data
Authors: He Jiahui , Mou Yan , Zhang Zhengjie
Published: April 2021

Based on COVID-19 and Persuasion Communication Theory, this study constructs a research model to analyze the influence of rumors on consumers’ irrational purchasing behavior in the context of public crisis. Using an online questionnaire survey, the empirical results show that information quantity, content features, platform credibility, and source credibility all have a significant positive impact on rumor credibility; rumor credibility has a significant positive impact on negative emotion; Negative emotions have a significant positive impact on irrational purchasing behavior. The platform, source, quantity, and content features of rumors will affect people’s trust in rumors. Rumors cause social panic and lead to a surge of negative emotion, making people lose rational judgment and make irrational purchasing behavior. These irrational behaviors are largely due to the panic about some rumors, the urgency, and suddenness of public crisis events, making people more willing to believe in the uncertain information and engage in some irrational consumption behaviors.
Life Prediction Method of Missile Based On Environmental Load Spectrum of Shipborne Tilt Launching
Authors: Shan Xin , Zhang Weijian , Cao Yang , Li Xue
Published: April 2021

The fault time data of missile is an important information source to reflect the reliability and life index of missile. However, most of the failure time data are used for the life evaluation of missile, and there is no method to predict the life of missile by using the data of fault time. According to engineering experience and statistical analysis of fault data, the life characteristics of missiles are closely related to the storage environment. In this chapter, the relationship between the failure time data of missile and environmental load is established, the influence of environmental load on missile life is explored, and the life index of missile is predicted according to its service history and storage environment.
Application Research of Digital Media Technology in Ceramic Product Design
Authors: Yu Lu
Published: April 2021

Digital media technology is different from general digital technology, its own comprehensive is extremely strong, can organic combination and artistic, cultured is calculated, general digital technology and digital media technology exquisite combination of art and digital content, through digital content and effective performance art, also can be converted to a digital, art content to facilitate the design work, design work gradually into the public class, people can through the way of combination number, independent to make art and design. It also means that the era of national design is coming in the future. Although the content is not artistic enough, it represents the public’s pursuit of art, and also strengthens the individuality of ceramic products, so as to better meet the private customized needs of customers. Therefore, this paper will start with the advantages of digital media technology in ceramic product design, and fully launch the application research of digital media technology in ceramic product design.
Privacy Protection of Frequent Sequences based on Uniform Adaptive Local Margin
Authors: Wang Zhihan , Qiu Yiwei
Published: April 2021

In order to enhance the privacy protection of frequent sequences, and improve its mining utility and reduce the impact of data dimension, this paper proposes a consistent adaptive margin for marginal release under local difference privacy, which has the characteristics of improving the effectiveness and efficiency. The algorithm mainly uses the consistent adaptive local margin strategy to index, finds frequent sequences, perturbs transaction data through random response mechanism, and finds all the sensitivities that satisfy local differential privacy. For the purpose of determining the running time of mining frequent sequences, a reasonable local sensitivity traversal data set before and after the interference is selected. According to the combination property of differential privacy, it is proved theoretically that the algorithm satisfies local differential privacy, and the effectiveness of the algorithm is verified by experiments. The experimental results show that the proposed algorithm can protect the local differential privacy of frequent sequences safely and efficiently, and ensure the accuracy of frequent sequences.
Application Research of Big Data Technology in Engineering Cost
Authors: Yan Songyang
Published: April 2021

In view of the frequent use of information technology in practical engineering cost projects in recent years, the engineering cost industry slowly accumulated a lot of information data. The development of engineering cost industry has entered a new era of data era. The disadvantages are that there is no unified standard for project cost information data, information interconnection is difficult, the frequency of updating project cost data is slow, and the value of information has not been fully reflected. Therefore, in order to solve these problems, the most advanced information technology is applied to the construction of the project cost platform by relying on large number technology, and the project cost information data is collected, sorted out and analyzed, so that these data are full of its deserved value. The process of building a platform of the need to establish a unified standard, engineering cost data shall be carried out in accordance with the standard information collection, sorting and processing, for project cost related units to query, data model, is applied to analyze the information data at the same time, to invest in the project cost, engineering material price analysis, all staff to provide decision support for engineering cost industry. This paper USES questionnaire survey to obtain data, and analyzes the data to find that 50% of the cost information obtained comes from professional journals, and only 19% of engineering cost workers can use the Internet.
Change-In-Mean Problem for Long Memory Time Series Model
Authors: Liang Danya , Jin Hao
Published: April 2021

In this paper, we propose the ratio test to detect the mean change point in the long-range memory. We proved that the limit distribution of the cumulative sum (CUSUM) statistic under the null hypothesis is a functional of fractional Brownian motion. At the same time, the consistency under the alternative hypothesis is also obtained. Simulations demonstrate that our asymptotic results provide good size and power.