Research on Risk Uncertainty Analysis and High-Quality Development Under Digital Transformation of Small and Medium-Sized Enterprises Based on Neural Network Algorithm

Abstract

 In the rapidly evolving landscape of digital transformation, small and medium-sized enterprises (SMEs) face unprecedented challenges and opportunities. This study delves into the intricate web of risk uncertainty that accompanies digital transformation, leveraging the power of neural network algorithms to dissect and mitigate these risks. Drawing from a rich tapestry of literature, we explore the historical and cultural contexts that have shaped the digital journey of SMEs, highlighting the unique vulnerabilities and potentials inherent in this transition. Through a detailed case study of an SME undergoing digital transformation, we apply neural network algorithms to identify and quantify key risk factors, revealing surprising insights into the dynamics of risk and uncertainty. Our findings not only underscore the critical role of advanced analytics in risk management but also pave the way for high-quality development strategies tailored to the specific needs of SMEs. As we navigate this digital frontier, the promise of neural network algorithms in fostering resilient and innovative SMEs is both tantalizing and profound.