Abstract

In order to explore the economic development trend under the environment of the Internet of Things, this paper improves the chaotic algorithm of the Internet of Things and constructs an economic development trend analysis system based on big data technology. Moreover, this paper analyzes the actual situation of big data processing data and conducts research on economic data analysis process. In addition, this paper conducts effective research on the various modules of functional analysis, obtains the system functional architecture, constructs the system functional structure based on the actual situation, and analyzes the operating process of the system. Finally, this paper designs a simulation test based on actual data. The experimental research results show that the system model proposed in this paper has a good performance in the forecast of economic development trends, and the system can be used for forecasting in subsequent economic development forecasts.

Highlights

  • With the continuous development of the world economy, our country’s economy has entered a new era. e economic growth rate has gradually shifted from the original highspeed growth to the current medium-high growth. e new era corresponds to new development methods, and development gradually shifts its focus to optimize the industrial structure, transform the main body of the three major industries, accelerate the development of the tertiary industry, increase the scale of urbanization, improve people’s living standards, and reduce the gap between urban and rural areas

  • After experiencing the great economic crisis, developed countries have gradually realized that they need to return to the manufacturing industry to prevent the country from hollowing out the industry due to excessive outsourcing. e focus of the return is on industrial upgrading and the use of high-tech for high-end manufacturing

  • Φ(i, 2: N) Φ(i − 1, 1: N − 1), and among them, 2 ≤ i ≤ M and μ > 1. is paper adopts a hyper-IoT data chaos system that is highly sensitive to initial values and system parameter values. erefore, when the initial values and system parameter values change slightly, we can get completely different measurement matrices, which will produce completely different compression effects

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Summary

Introduction

With the continuous development of the world economy, our country’s economy has entered a new era. e economic growth rate has gradually shifted from the original highspeed growth to the current medium-high growth. e new era corresponds to new development methods, and development gradually shifts its focus to optimize the industrial structure, transform the main body of the three major industries, accelerate the development of the tertiary industry, increase the scale of urbanization, improve people’s living standards, and reduce the gap between urban and rural areas. The optimization of the financial structure is an effective way to promote macroeconomic growth, which is mainly reflected in two aspects: (1) By improving the capital allocation effect of the social production sector, it can achieve the promotion of technological progress and the optimization and upgrading of the industrial structure. (2) e optimization and upgrading of the industrial structure can promote social economic growth by increasing social productivity and increasing total social investment, thereby changing the financial structure and total financial volume. The question we want to study is the current status of my country’s provincial financial agglomeration and comprehensive economic development and what kind of relationship exists between the two systems of financial agglomeration and economic development, so as to provide a scientific basis for promoting regional economic development. Based on the above analysis, this paper analyzes the economic development trend in the Internet of ings environment, combines big data technology to carry out economic development data research, and predicts and analyzes economic development trends

Related Work
Chaos Data Processing Algorithm of the Internet of Things
Evaluation model management
Evaluation index management
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