基于深度学习的创新创业市场趋势预测模型:案例研究与性能评估。

IF 2.6 4区 综合性期刊 Q2 MULTIDISCIPLINARY SCIENCES Science Progress Pub Date : 2024-07-01 DOI:10.1177/00368504241272722
Kongyao Huang, Yongjun Zhou, Xiehua Yu, Xiaohong Su
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引用次数: 0

摘要

在当前的经济形势下,创新和创业的重要性日益凸显,因此迫切需要准确的市场趋势预测。针对这一挑战,我们的研究引入了基于深度学习原理的创新创业市场趋势预测模型。通过详细的案例研究和性能评估,本文展示了该模型的有效性及其在竞争激烈的商业环境中提高决策能力的潜力。准确的市场趋势预测在创新和创业领域至关重要,我们的方法满足了这一需求。我们的模型利用了深度学习技术的力量,将历史市场数据与各种市场指标(包括从社交媒体中获得的情感分析)相结合,创建了一个超越传统方法的先进预测模型。通过分析来自多个渠道的数据,我们的模型在预测未来市场趋势方面表现出了非凡的准确性。该案例研究有力地证明了我们模型的性能和精确度,展示了它对创新者和企业家驾驭复杂市场趋势的重要支持。此外,这项研究还凸显了深度学习技术在经济领域的巨大潜力。我们强调了开发创新型创业市场趋势预测模型的重要性,并预计通过采用深度学习提高决策质量,创新者和创业者的项目成功率将会提高。
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Innovative entrepreneurial market trend prediction model based on deep learning: Case study and performance evaluation.

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.

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来源期刊
Science Progress
Science Progress Multidisciplinary-Multidisciplinary
CiteScore
3.80
自引率
0.00%
发文量
119
期刊介绍: Science Progress has for over 100 years been a highly regarded review publication in science, technology and medicine. Its objective is to excite the readers'' interest in areas with which they may not be fully familiar but which could facilitate their interest, or even activity, in a cognate field.
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