Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment

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...

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Main Author: Min Kuang
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2021/2860206
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author Min Kuang
author_facet Min Kuang
author_sort Min Kuang
collection DOAJ
description 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.
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institution Kabale University
issn 1687-5699
language English
publishDate 2021-01-01
publisher Wiley
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series Advances in Multimedia
spelling doaj-art-20b3e5a0b768481383eae0c0bd09866e2025-02-03T05:43:34ZengWileyAdvances in Multimedia1687-56992021-01-01202110.1155/2021/2860206Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things EnvironmentMin Kuang0Business SchoolIn 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.http://dx.doi.org/10.1155/2021/2860206
spellingShingle Min Kuang
Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment
Advances in Multimedia
title Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment
title_full Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment
title_fullStr Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment
title_full_unstemmed Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment
title_short Economic Development Trend Prediction Model Based on Unsupervised Learning in the Internet of Things Environment
title_sort economic development trend prediction model based on unsupervised learning in the internet of things environment
url http://dx.doi.org/10.1155/2021/2860206
work_keys_str_mv AT minkuang economicdevelopmenttrendpredictionmodelbasedonunsupervisedlearningintheinternetofthingsenvironment