Deep learning for economic transformation: a parametric review

Q2 Mathematics
Usman Tariq, Irfan Ahmed, Muhammad Attique Khan, Ali Kashif Bashir
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引用次数: 0

Abstract

Deep learning (DL) is increasingly recognized for its effectiveness in analyzing and forecasting complex economic systems, particularly in the context of Pakistan's evolving economy. This paper investigates DL's transformative role in managing and interpreting increasing volumes of intricate economic data, leading to more nuanced insights. DL models show a marked improvement in predictive accuracy and depth over traditional methods across various economic domains and policymaking scenarios. Applications include demand forecasting, risk evaluation, market trend analysis, and resource allocation optimization. These processes utilize extensive datasets and advanced algorithms to identify patterns that traditional methods cannot detect. Nonetheless, DL's broader application in economic research faces challenges like limited data availability, complexity of economic interactions, interpretability of model outputs, and significant computational power requirements. The paper outlines strategies to overcome these barriers, such as enhancing model interpretability, employing federated learning for better data privacy, and integrating behavioral and social economic theories. It concludes by stressing the importance of targeted research and ethical considerations in maximizing DL's impact on economic insights and innovation, particularly in Pakistan and globally.
深度学习促进经济转型:参数审查
深度学习(DL)在分析和预测复杂经济系统方面的有效性日益得到认可,尤其是在巴基斯坦经济不断发展的背景下。本文研究了深度学习在管理和解释日益增多的错综复杂的经济数据方面的变革性作用,从而得出更细致入微的见解。与传统方法相比,DL 模型在各种经济领域和决策场景中的预测准确性和深度都有显著提高。应用领域包括需求预测、风险评估、市场趋势分析和资源配置优化。这些过程利用广泛的数据集和先进的算法来识别传统方法无法发现的模式。然而,DL 在经济研究中的广泛应用面临着各种挑战,如数据可用性有限、经济互动的复杂性、模型输出的可解释性以及大量的计算能力要求。本文概述了克服这些障碍的策略,如提高模型的可解释性、采用联合学习以更好地保护数据隐私,以及整合行为和社会经济理论。最后,论文强调了有针对性的研究和伦理考虑对于最大限度地发挥 DL 对经济见解和创新的影响的重要性,特别是在巴基斯坦和全球。
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来源期刊
CiteScore
2.90
自引率
0.00%
发文量
782
期刊介绍: The aim of Indonesian Journal of Electrical Engineering and Computer Science (formerly TELKOMNIKA Indonesian Journal of Electrical Engineering) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the applications of Telecommunication and Information Technology, Applied Computing and Computer, Instrumentation and Control, Electrical (Power), Electronics Engineering and Informatics which covers, but not limited to, the following scope: Signal Processing[...] Electronics[...] Electrical[...] Telecommunication[...] Instrumentation & Control[...] Computing and Informatics[...]
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