Big-data-driven pre-stack seismic intelligent inversion

In order to further understand the current situation of the financial market and better supervise the resource management of the financial market, combined with big data and cloud computing technology, through the construction of big data cloud platform resource management system and the integration of various technical computing frameworks, we can realize the effective supervision of big data resources in the financial market. Using J2EE technology, this paper analyzes, designs, implements, and tests the investment data management system, analyzes the content of the software engineering subject, and obtains the demand function description of the business. According to the software development process and the actual situation of enterprise investment, this paper expounds the basic requirements of the investment data management business, system architecture requirements, user use case status, and the operation and configuration environment of the investment data management system. This paper analyzes the technical characteristics and operation indicators of the software, and establishes the data flow for the data related to investment data management, such as information statistics, data query, information classification and so on. Finally, the system is verified, operated and tested, and the business use cases and parameters of the system are tested according to the two indicators of software testing. The basic functions of the investment data management realized by the system are correct, the design is reasonable, the operation is stable, the operation response time is short, the operation accuracy is high, and the data access efficiency is good.

Section: Literature Reviewmentioning

confidence: 99%

Regulatory Mechanism of Financial Market Resource Management Driven by Big Data

Xie

Chen

2022

“…As a result, students are unable to selfregulate and self-manage. It is difficult to help more students master oral English and guarantee the enrollment rate only by teachers' own efforts in class [7]. Teachers only need to combine network resources to create a platform for effective communication with students and create a positive learning environment for students.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of an Online Oral English Teaching Model Using Big Data

Song

Yi²,

Shen

et al. 2022

In order to improve the online oral English teaching model, enhance its efficiency, and widen its utilization in university teaching, this study developed a rigorous oral English teaching model, constructed a comprehensive oral English evaluation model, and used PBL to guide the direction of oral English curriculum under the influence of big data-driven background. The use of online oral English teaching mode was realized to ensure that students can internalize knowledge in class. A complete teaching method was used to ensure that learners can master more knowledge in English class, promote the operation of online English learning in the network environment and create a safe learning environment for students, improve students’ oral English ability, improve oral teaching, and improve the integrity of oral teaching. The deepening of big data and online review teaching will be the requirements of the future teaching environment. Therefore, it was decided that only by making full use of all the advantages of information technology, combined with the background of education and teaching, can we explore the new education and training methods needed in the new semester.

“…The reverse transmission of the error starts from the output layer to calculate the output error value of each layer of neurons, and then relies on the error gradient descent method to correct the weights and thresholds of each layer, so that the final output of the adjusted network structure can be as close to the expected value as possible [15].…”

Section: Analysis Of Key Technologies Of Internet Of Things Cloud Pla...mentioning

confidence: 99%

Administrative Punishment Supervision System Based on Internet of Things Driven by Big Data

Wang

2022

In order to study the administrative punishment supervision system based on the Internet of things driven by big data, firstly, based on the full collection of materials, this paper makes a detailed induction and analysis from the perspective of demonstration, and discusses the problems existing in the practice of administrative punishment. In terms of theory, first determine the concept of administrative punishment from the overall direction, and then locate it to administrative punishment. Then, it analyzes the specific contents of the construction of the supervision system based on the Internet of things driven by big data and the key technologies of the cloud platform system of the Internet of things. Finally, focusing on the judgment cases published by the municipal and county courts in a province from 2014 to 2017, the analysis results are displayed, discussed, and summarized. The results show that the construction of intelligent supervision system is realized, the intelligent response to supervision needs is completed, and the scientific and effective supervision is promoted.