PRESS RELEASE: In the continually evolving telecommunications industry, efficient network resource management and accurate traffic forecasting are paramount. Addressing these challenges, ZTE has developed an innovative solution – the AI Assistant of Network Autonomous solution in the cloud – that employs a variety of AI models and a unique precision self-iterative method.

As the core technology of network and wireless energy-saving solutions, the ZTE AI Assistant Cloud Solution has been deployed and applied globally. This marks the first time that this type of technology has been implemented in the public cloud, fully demonstrating its powerful and efficient capabilities. This innovative technological application by ZTE not only enhances the operational efficiency of businesses but also makes significant strides in reducing environmental burdens.

The ZTE AI Assistant Cloud Solution adapts to various types of data and computational resources by applying appropriate AI models. For smaller linear datasets, the solution employs the ARIMA model, known for its interpretability. For larger, complex data sets, it leverages the power of Long Short Term Memory (LSTM) models. Regression tree models are used in cases involving categorical variables such as subscriber location or subscription type (like premium, basic, etc.). By using different models based on the nature of the data, ZTE has created a flexible and robust tool that can handle various scenarios and data types.

To ensure accurate and reliable results, ZTE has introduced exponential smoothing as a baseline model in the solution. This model provides a performance benchmark, enabling us to cross-check and validate the results produced by more complex models like ARIMA or LSTM. This multi-model approach by ZTE mitigates the risk of bias or inaccurate results, ensuring reliable data analysis and accurate traffic load forecasting.

The ZTE AI Assistant Cloud Solution also introduces a technique we call precision self-iteration. By analyzing the fluctuations of various KPIs, we fine-tune energy threshold parameters, continuously iterate, and analyze the impact relationship between KPIs and the energy-saving threshold to find the optimal energy-saving threshold. This balance between energy efficiency and network performance not only helps to maximize the reduction of energy costs but also contributes to more sustainable network operations.

By improving forecast accuracy, optimizing energy usage, ensuring reliable results, and reducing operational burdens, ZTE’s cloud-based solution provides a more efficient and cost-reducing pathway for mobile networks. The innovative use of multiple AI models and precision self-iterative methods by ZTE significantly improves the economic efficiency of the mobile network offerings.

Furthermore, by maintaining optimal network performance and ensuring efficient resource allocation, ZTE also guarantees the end user’s experience. Fast, reliable network connections can lead to higher customer satisfaction and loyalty, a crucial factor in today’s competitive market.

In a world where data is growing exponentially, the ZTE AI Assistant Cloud Solution offers a revolutionary approach to mobile network management. By harnessing the power of artificial intelligence and precision iteration, ZTE is setting new standards for network efficiency, reliability, and user satisfaction. Looking forward, the cloud-based solution will have the advantage of keeping pace with the latest technologies around the world, solidifying its role as a leading innovation in the telecom industry.