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Research on the Development of Digital Business Forecasting in the 'Commerce, Culture, and Tourism Plus' Model Based on Big Data and Predictive Models

Published: 01 June 2024 Publication History

Abstract

In the face of the rapid development of digital business, accurate forecasting is of significant importance. This study constructs a business forecasting model based on deep learning to improve prediction accuracy. Data from tourism platform users and orders are collected, and a dataset is constructed through data processing. The study designs a deep neural network model that combines user information and time series to learn business time-related correlations. The model is trained on tourism business data, and the results show that the forecasting performance is better than traditional regression methods and can simulate business cycle patterns. The research demonstrates that deep learning methods can extract complex patterns and accurately predict digital business growth. However, factors such as business randomness need to be considered for adjustment. This study provides a framework for further improving business forecasting.

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  1. Research on the Development of Digital Business Forecasting in the 'Commerce, Culture, and Tourism Plus' Model Based on Big Data and Predictive Models

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    ICBAR '23: Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management
    November 2023
    1156 pages
    ISBN:9798400716478
    DOI:10.1145/3656766
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 01 June 2024

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