Innovative entrepreneurial market trend prediction model based on deep learning: Case study and performance evaluation.

Journal: Science progress
PMID:

Abstract

In the current economic landscape, the growing importance of innovation and entrepreneurship underscores an urgent need for accurate market trend prediction. Addressing this challenge, our study introduces an innovative entrepreneurial market trend prediction model based on deep learning principles. Through detailed case studies and performance evaluations, this paper demonstrates the model's effectiveness and its potential to enhance decision-making capabilities in a competitive business environment. Accurate market trend prediction is crucial in the fields of innovation and entrepreneurship, and our approach meets this demand. Our model leverages the power of deep learning technology, combining historical market data with diverse market indicators, including sentiment analysis derived from social media, to create an advanced predictive model that surpasses traditional methods. By analyzing data from multiple channels, our model exhibits exceptional accuracy in forecasting future market trends. The case study provides strong evidence of our model's performance and precision, showcasing its significant support for innovators and entrepreneurs navigating complex market trends. Furthermore, this study highlights the vast potential of deep learning technology in the economic sector. We emphasize the importance of developing innovative entrepreneurial market trend prediction models and foresee an increase in project success rates for innovators and entrepreneurs by enhancing decision quality through the adoption of deep learning.

Authors

  • Kongyao Huang
    School of Innovation and Entrepreneurship, Minnan Science and Technology University, Nanan, China.
  • Yongjun Zhou
    Institute of Bioengineering and Biotechnology, Minnan Science and Technology University, Nanan, China.
  • Xiehua Yu
    School of Computer and Information, Minnan Science and Technology University, Nanan, China.
  • Xiaohong Su
    Business School, Minnan Science and Technology University, Nanan, China.