Biomechanics-based early warning system for financial crises in advanced manufacturing enterprises using deep learning
Siwei Wang · Molecular & cellular biomechanics · 2025
In response to the increasing demand for lean marketing management, enterprises are leveraging intelligent data technologies for risk management. This paper aims to construct a marketing business risk management model inspired by biomechanics, combining Internet of Things (IoT) technology and BP neural network to provide a proactive early warning mechanism. In constructing the risk management model, this paper draws on the adaptive mechanism in biomechanics, emphasizing the flexibility and responsiveness of the system when facing a complex environment. By simulating how organisms adjust their behavior in a dynamic environment, this paper proposes a project group resource conflict risk assessment model based on BP neural network. The model uses nonlinear fitting and self-learning capabilities to dynamically adjust prediction parameters to adapt to market changes and resource allocation issues. This biomechanically inspired design enables the model to better capture potential risks and improve the accuracy of predictions when processing complex data. In addition, this paper also introduces a Linux-based multi-task embedded management system to achieve seamless integration of the Internet of Things and neural network risk models. The design of this system is inspired by the multi-tasking ability of organisms, which can efficiently switch between multiple tasks, thereby improving the response speed and processing power of the overall system. In this way, enterprises can monitor and manage various risks in marketing operations in real time. The experimental results show that the proposed biomechanically inspired risk management model performs well in practical applications, can effectively model marketing business risks, and provides superior performance. The research in this paper provides new ideas and tools for enterprises to achieve more efficient active risk management in a complex and changing market environment, and emphasizes the importance of biomechanics in the application of intelligent data technology. This not only provides a scientific basis for corporate decision-making, but also points out the direction for future research. By combining the inspiration of biomechanics, companies can better cope with challenges in risk management and enhance their competitiveness.