Background Of Big Data Research Articles

Research on Optimization of Accounting Information System under the Background of Big Data

Big data technology affects all walks of life, posing new challenges to the accounting industry and accounting information systems. Cloud computing provides convenient and effective network terminal access ports through its strong service model, and can also establish a resource sharing platform to improve the efficiency of enterprise accounting information management. This article explores the optimization of accounting information systems from the perspective of big data. With the help of big data technology, accounting information systems can achieve data optimization, storage function optimization, report optimization, analysis function optimization, decision-making function optimization, and coordination optimization. In addition, this article conducts research on the construction of enterprise accounting information systems under cloud accounting systems, and proposes optimization strategies aimed at optimizing accounting information systems and improving the economic benefits of enterprises. While using big data technology to optimize accounting information systems, enterprises should always pay attention to the effective application of big data on the premise of good security precautions.

Research on Food Security System Based on Internet of Things Technology under the Background of Big Data

Food security is the main topic of social and economic construction in the new era, which directly affects the physical and mental health of urban residents. As the production, processing, sales and other links of food enterprises are the basic components of safety management, each link may cause food safety problems. Therefore, it is necessary to use modern technical means to collect and analyze the production data of each link, and pay attention to creating a safe and stable production environment, so as to ensure food safety and quality on the basis. On the basis of understanding the application advantages of Internet of Things technology in the era of big data, this paper takes the food tracking system as an example to deeply discuss the key technologies and main functions in order to provide technical support for solving food safety problems.

A mathematical model for the spread of Omicron virus based on grey prediction algorithm

After two years of the Newcastle epidemic, the emergence of a mutant strain of Omicron virus has once again raised a high level of alarm worldwide, and it has rapidly replaced the Delta strain as the major strain in the world epidemic with high infectivity. In order to study the spread of the epidemic in a qualitative and quantitative manner, this paper uses relevant mathematical modeling ideas and methods, combined with the background of big data, to conduct relevant research and analysis in order to provide guidance for the actual fight against the epidemic and facilitate scientific research and response measures. In this paper, a gray prediction algorithm is used to predict the future epidemic data. A metabolic algorithm is introduced to recursively correct the prediction residuals and build a multilevel gray model. In this paper, to investigate the role of vaccines on epidemics, the R values under each dose of vaccine were calculated by selecting data from several countries and regions using fitted curve idealization. The prediction of the data yields the conclusion that vaccination is indeed directly effective in controlling the spread of the epidemic.

Retraction Note: Optimal path for fault identification of marine communication network in the background of big data

Retraction Note: Optimal path for fault identification of marine communication network in the background of big data

Research on Monitoring technology of construction machinery based on Big data

In the rapid development of information era, the pace of economic construction in all fields of our country is becoming faster and faster, including the field of engineering machinery put forward modern remote monitoring system with big data technology as the core, not only has a broad development space, but also provides a variety of research directions for the development of new era technology equipment. On the basis of understanding the concept of big data technology, according to the development phenomenon and unique advantages of construction machinery monitoring technology under the background of big data, this paper deeply discusses the development trend of construction machinery monitoring technology with big data as the core, in order to provide effective basis for the technical development of construction machinery field in the new era.

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

Traditional parallel computing for power management systems has prime challenges such as execution time, computational complexity, and efficiency like process time and delays in power system condition monitoring, particularly consumer power consumption, weather data, and power generation for detecting and predicting data mining in the centralized parallel processing and diagnosis. Due to these constraints, data management has become a critical research consideration and bottleneck. To cope with these constraints, cloud computing-based methodologies have been introduced for managing data efficiently in power management systems. This paper reviews the concept of cloud computing architecture that can meet the multi-level real-time requirements to improve monitoring and performance which is designed for different application scenarios for power system monitoring. Then, cloud computing solutions are discussed under the background of big data, and emerging parallel programming models such as Hadoop, Spark, and Storm are briefly described to analyze the advancement, constraints, and innovations. The key performance metrics of cloud computing applications such as core data sampling, modeling, and analyzing the competitiveness of big data was modeled by applying related hypotheses. Finally, it introduces a new design concept with cloud computing and eventually some recommendations focusing on cloud computing infrastructure, and methods for managing real-time big data in the power management system that solve the data mining challenges.

Practice and Exploration of Virtual Simulation System to Cultivate Cross-Border E-Commerce Talents in the Context of Big Data

Under the background of big data, there are many types of virtual simulation software in the field of e-commerce. This article uses the survey method, combined with its own practical experience, to discuss how to use the virtual simulation system to cultivate cross-border e-commerce talents. The article analyzes the difficulties of cultivating cross-border e-commerce talents from the perspective of market demand. By comparing the mainstream cross-border e-commerce virtual simulation systems in China and the business models of software development enterprises, the advantages and disadvantages of virtual simulation systems in practice are discussed comprehensively. Suggestions such as promoting learning by competition and reducing software purchase dependence; cooperating with software companies for development based on their own conditions and regional characteristics are put forward. It is hoped that in the training of cross-border e-commerce talents, the virtual simulation system can be used to avoid the risk of real-life practice and keep up with the market demand at the same time.

Research on the Positive Impact of Information Technology on Student Education in Higher Vocational Colleges in the Era of Big Data

Under the background of big data, scientific application of big data technology can effectively improve the informatization construction level of education and teaching management in higher vocational colleges. This paper takes the informatization of higher vocational education and teaching management as the research object, analyzes the advantages of applying big data technology to higher vocational education and teaching management, and proposes specific ways to accelerate the improvement of the informatization level of higher vocational education and teaching management. Give full play to the guarantee role of education management and cultivate students' professional quality. Therefore, through the value analysis of educational management reform in higher vocational colleges, the article clarifies the new requirements of educational management reform in higher vocational colleges, and discusses the new strategies of educational management reform in higher vocational colleges.

Application of Swarm Intelligence Optimization Algorithm in Logistics Delivery Path Optimization under the Background of Big Data

Traditional logistics delivery route optimization algorithm has some problems such as long time to find the optimal route. Based on this, this paper discusses swarm intelligence optimization algorithm and logistics delivery route optimization. To solve the logistics vehicle routing problem, considering that the basic ACO (ant colony optimization) has the disadvantages of slow convergence speed and easy to fall into local optimum, this paper proposes a new hybrid population optimization algorithm and applies it to VRPTW (vehicle routing problem with time windows). In addition, the concept of crowding degree in AFSA (artificial fish swarm algorithm) is introduced into ACO. In the early stage of the optimization process, a strong crowding degree limit is set to ensure that most ants are not affected by pheromone concentration to conduct random optimization. The simulation results show that the AC (accuracy rate) of this algorithm is 95.08%, which is higher than the traditional PSO (particle swarm optimization) algorithm and general heuristic algorithm. The hybrid algorithm can effectively improve the optimization efficiency of VRPTW, lay a foundation for solving large-scale VRPTW, and provide new research ideas and methods. At the same time, the results fully show that the algorithm in this paper has certain advantages in performance, and it can be applied to logistics delivery route optimization.

Design and Development of Integrated Platform for Automobile Sales Model under the Background of Big Data

Based on the integration of the big data background and the exploration of related technologies in the enterprise service bus, this article focuses on the management strategy of auto parts, carries out theoretical analysis on parts classification, parts demand forecast, parts inventory control, and combines the characteristics of the auto parts industry. Research. At the same time, combined with the demand analysis of the actual business process of the car dealer, the car dealer business system based on the SOA integrated platform is designed. In the system design stage, the current more popular model-view-controller (MVC) three-tier design pattern is adopted to better focus on the hierarchical development of each level.

Challenges and Changes Faced by Enterprise Financial Management in the Background of Big Data

With the progress of society and the development of the times, the level of science and technology has been significantly improved and widely used in various fields. In the context of big data, the application of information technology has provided certain convenience for various industries, which can not only improve work efficiency, but also improve work quality. Therefore, internal managers and financial personnel of enterprises should give full play to the advantages of big data, enhance the awareness of big data while reforming and innovating, and cultivate more professional and versatile talents. Enterprises should actively integrate the big data system, establish a more complete financial management model, and achieve win-win economic benefits and management efficiency. This paper analyzes the challenges faced by enterprise financial management under the background of big data, and discusses the reform strategy of enterprise financial management.

Information Security Protection of Internet of Energy Using Ensemble Public Key Algorithm under Big Data

This work aims to solve the specific problem in the Power Internet of Things (PIoT). PIoT is vulnerable to monitoring, tampering, forgery, and other attacks during frequent data interaction under the background of big data, leading to a severe threat to the power grid’s Information Security (ISEC). Cryptosystems can solve ISEC problems, such as confidentiality, data integrity, authentication, identity recognition, data control, and nonrepudiation. Thereupon, this work expounds on cryptography from public-key encryption and digital signature and puts forward the model of network information attack. Then, the security of the two cryptograms is certified against the two cyberattack modes. On this basis, an Identity-based Combined Encryption and Signature (IBCES) ensemble scheme is proposed by combining public-key encryption with the digital signature. Finally, the security of the proposed IBCES’s encryption and the signature schemes is verified, and the results prove their feasibility. The results show that the proposed IBCEs are effective and feasible, fully meeting the information confidentiality requirements. Additionally, smart grid against Information Security (ISEC) algorithms must comprehensively consider network resources and computing power. This work creatively combines the two cryptosystems. The proposal breaks the traditional key segmentation principle by applying the same key to different cryptosystems and ensures the independent security of the two cryptosystems. The conclusion provides technical support for future research on cryptography.

Research on the comprehensive Literacy test and evaluation of English course students based on cloud education big data

In the innovation and development of modern education, the Internet, big data, cloud computing and so on have had a profound impact on the implementation of college English education curriculum. Especially after the development trend of economic globalization, college English courses pay more attention to optimizing the comprehensive quality of students in the face of the new talent training requirements put forward by the development of social and economic construction. Through the questionnaire survey, the main problems in the field of education are to study the current content of college students' comprehensive English quality test and evaluation, actively explore the test and evaluation path of students' comprehensive English quality under the background of big data, and clarify the implementation countermeasures of future college English courses according to the development trend of cloud education big data technology. On the basis of understanding the development status of cloud education big data technology, this paper constructs the testing and evaluation system of students' comprehensive quality from various aspects, such as motivation, attitude and quality, according to the requirements of English course students' comprehensive literacy training, and finally puts forward clear education management measures.

Research on the Influence of Securities Research Newspapers on the Company's Stock Trend and Investment Strategies

Because stocks have the advantages of good liquidity and high returns, many investors will choose to invest in stocks to obtain certain income. But stocks have the disadvantage of high risk. Therefore, certain analysis and research are required when investing in stocks. Under the background of big data, research papers of securities companies can play a certain reference role for investors. The paper extracts the characteristic indexes of 10 stocks, establishes TOPSIS model and multiple linear regression model to analyze the influence of characteristic indexes on the stock trend, and proposes clear investment strategies. In the further analysis, this paper uses the gray relational analysis method to study the impact of the flash of emergencies, public opinion and natural disasters on 10 stocks, so as to propose new investment strategies. The purpose of this study is to provide investors with valuable investment strategies and improve investment efficiency.

Research on the Psychological Motivation of Juvenile Criminal Law Crime in the Background of Big Data

Juvenile robbery is mainly in the form of joint crime and accomplished crime, and the elements of criminal motive and criminal instrument have special value. Its judicial countermeasures at the trial level are as follows: alternative conviction, unconverted conditions of robbery, negation of aggravated crime, elimination or mitigation of the wrong understanding of criminal illegality This paper adopts case analysis, experience summary and literature analysis in research methods. It is expected to reveal juvenile delinquency, enrich and improve the existing criminal psychology system, and correctly educate minors for families and schools, and cultivate a sound personality through the study of juvenile delinquency psychological characteristics, causes of criminal psychology and prevention of criminal psychology.

Problems and Countermeasures of Intelligent Transportation under the background of Big Data

The advent of the Internet and the era of big data, accompanied by the rapid development of information technology has had a huge impact on intelligent transportation, bringing important changes to its development. This paper mainly introduces the characteristics of big data and the concept of intelligence traffic, intelligent traffic system at home and abroad present situation and the influence of big data for intelligent traffic system faced the problem and the solution countermeasures. The research found that make more positive steps of big data technology to rapidly promote the development of intelligent transportation.

ChatGPT and Big Data: Enhancing Text-to-Speech Conversion

Text-to-speech (TTS) conversion is a crucial technology for various applications, including accessibility, education, and entertainment. With the rapid growth of big data, TTS conversion systems face new challenges in terms of data size and diversity. In this paper, we propose to use the state-of-the-art language model ChatGPT to enhance TTS conversion for big data. We first introduce the background of TTS conversion and big data, and then review the existing TTS conversion systems and their limitations. Next, we describe the architecture and training of ChatGPT, and how it can be applied to TTS conversion. Finally, we evaluate the performance of the ChatGPT-based TTS conversion system on a large-scale real-world big data dataset, and compare it with the existing TTS systems. Our experimental results demonstrate that ChatGPT can significantly improve the quality and efficiency of TTS conversion for big data.

Smart Agriculture and Rural Revitalization and Development Based on the Internet of Things under the Background of Big Data

Smart agriculture refers to the specific performance of the smart economy in the field of agriculture; it is a form of agricultural smart economy and an important part of the smart economy. It has played a certain role in promoting rural revitalization and development. The purpose of this paper was to study the role of smart agriculture based on the Internet of Things in rural revitalization and development under the background of big data. The purpose was to use Internet of Things technology to realize smart agriculture under the background of big data, so as to promote rapid rural revitalization and development. Therefore, in this paper, a fuzzy PID algorithm and genetic algorithm were proposed. Finally, through experimental analysis, the fuzzy PID algorithm was used to carry out experiments in the laboratory. The temperature and humidity of the laboratory were measured. The average difference between the collected and actual temperature values was 0.6 °C, and the maximum difference between the collected and actual humidity values was 1.32% RH. The laboratory simulation results satisfied the performance indicators and technical requirements of the system. The system operated normally and could be directly applied to field tests. The experimental results show that the role of Internet of Things technology in the smart agricultural economy is irreplaceable, which further illustrates the positive relationship between smart agriculture based on the Internet of Things and rural revitalization and development. As one of the most mature technologies in today’s society, the Internet of Things technology combined with smart agriculture not only offers new perspectives, but also promotes the revitalization and development of rural areas, indicating a new direction for its future research.

Research on the integrated and innovative teaching mode of probability and statistics courses under the background of big data

Big data has become a buzzword in many industries, forums and economic exchanges, and its development is interrelated and permeated with mathematics, computers and mathematical statistics courses. Probability theory and statistics, as tools for big data analysis, often belong to different teaching departments, and teaching and research are separated, this paper is based on the Department of Economics and Statistics doing innovative reforms in the discipline foundation, course class connotation and talent training direction to achieve two This paper is based on an innovative reform of the Department of Economics and Statistics in terms of the foundations of the subject, the content of the course and the direction of personnel training. Vertically, realize the theoretical content integration of "high school probability statistics university probability theory and mathematical statistics university statistics big data and statistics"; In the horizontal expansion of the teaching process, grasp the context of "theoretical system interesting cases mathematical modeling ideas project-based embedded teaching competition participation guidance theory and practice review and strengthening"; Form a student-centered and output-oriented integrated and innovative teaching model.

Research on the comprehensive Literacy test and evaluation of English course students based on cloud education big data

In the innovation and development of modern education, the Internet, big data, cloud computing and so on have had a profound impact on the implementation of college English education curriculum. Especially after the development trend of economic globalization, college English courses pay more attention to optimizing the comprehensive quality of students in the face of the new talent training requirements put forward by the development of social and economic construction. Through the questionnaire survey, the main problems in the field of education are to study the current content of college students' comprehensive English quality test and evaluation, actively explore the test and evaluation path of students' comprehensive English quality under the background of big data, and clarify the implementation countermeasures of future college English courses according to the development trend of cloud education big data technology. On the basis of understanding the development status of cloud education big data technology, this paper constructs the testing and evaluation system of students' comprehensive quality from various aspects, such as motivation, attitude and quality, according to the requirements of English course students' comprehensive literacy training, and finally puts forward clear education management measures.