Network Performance Analysis Using Update Volatility and Significance Tests
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Solution Overview
Problem
Traditional methods for evaluating network performance before and after major operations in communication networks require significant manual labor, leading to low efficiency and high labor costs.
Innovation Solution
A data analysis method that automatically calculates deviation rates and significance test probabilities of network performance indexes before and after updates, outputting target indexes for further analysis, thereby reducing manual effort and improving evaluation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data sources are collected and integrated to improve analysis comprehensiveness, then data completeness is improved, but data processing complexity increases
Solution Approach 1:
The patent segments data processing by creating separate processing pipelines for different data sources (sensor data, image data, audio data, etc.). Each data type is processed independently through dedicated modules before being integrated into the unified knowledge graph, reducing the complexity of handling heterogeneous data simultaneously.
Solution Approach 2:
The patent introduces an intermediary layer (data processing module and knowledge graph construction module) that mediates between raw multi-source data and the final analysis results. This intermediary layer standardizes and structures data from various sources into a unified knowledge graph format, simplifying subsequent analysis operations.
2Measurement precision
If detailed data processing and analysis are performed to improve diagnostic accuracy, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing data during collection and immediately constructing a knowledge graph structure as data arrives. This preliminary organization of data into structured relationships enables faster retrieval and analysis during diagnostic operations, reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent replaces traditional sequential mechanical data processing with a parallel processing architecture using GPU acceleration for knowledge graph construction and analysis. This substitution enables simultaneous processing of multiple data streams and complex analytical operations, significantly reducing processing time while maintaining high diagnostic accuracy.
3Measurement precision
If comprehensive data from multiple sources is integrated to improve analysis accuracy, then measurement precision is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal knowledge graph structure that can accommodate multiple data types (sensor data, image data, audio data, text data) through a unified schema. This multi-functional knowledge graph serves as a common framework for integrating heterogeneous data sources, reducing system complexity by providing a single integration architecture rather than separate processing systems for each data type.
Data Source
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AI summary
Embodiments of the present application relate to the technical field of communications, and provide a data analysis method, including: obtaining network performance index data before a network is updated as a first data, and obtaining network performance index data after the network is updated as a second data; and outputting a network performance analysis result after the network is updated according to a data volatility of the second data relative to the first data. Embodiments of the present application further provide an electronic device and a storage medium.