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Optimization Mold and Algorithm of Risk Control for Power Grid Corporations Based on Collaborative Filtering

Longxing Chen1, Ping Han1

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Financial meltdown is a gradual process, not sudden. This study introduces a data mining algorithm for early warning systems, improving risk control in power grid corporations by 30% over traditional methods.

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Area of Science:

  • Business and Financial Management
  • Data Science and Analytics
  • Risk Management

Background:

  • Enterprises face increasing uncertainties and risks due to dynamic environments, elevating the likelihood of financial meltdown.
  • Financial meltdown is a gradual, predictable process, not an abrupt event, necessitating proactive early warning systems.
  • Identifying predictive signals within vast financial data is crucial for listed corporations, especially in China.

Purpose of the Study:

  • To develop an effective data mining approach for early warning systems to predict and mitigate financial meltdown in enterprises.
  • To analyze and optimize the risk control model and algorithm for power grid corporations using advanced data mining techniques.

Main Methods:

  • Utilizing data mining techniques to analyze large volumes of enterprise financial data.
  • Applying collaborative filtering techniques to develop a novel risk control optimization algorithm.
  • Comparing the performance of the proposed algorithm against traditional methods.

Main Results:

  • The developed algorithm demonstrates a 30% improvement in performance compared to traditional algorithms.
  • The collaborative filtering-based approach effectively mines early warning signals from financial data.
  • The algorithm is suitable for widespread adoption in risk management.

Conclusions:

  • Data mining, particularly collaborative filtering, offers a powerful solution for financial meltdown early warning systems.
  • The proposed algorithm significantly enhances risk control optimization for power grid corporations.
  • The findings provide a valuable tool for ensuring the healthy development and preventing financial distress in enterprises.