Fuzzy Trust Evaluation for Power IoT Generator Set Access
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current algorithms for controlling generator sets' connection to the Internet of Things fail to consider gain and loss values, leading to poor effectiveness in managing their access.
Innovation Solution
A method using fuzzy set theory to calculate information gain and loss values for photovoltaic and wind turbine generator sets, determining a trust degree to decide on access modes, including allowing or prohibiting access based on these values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current algorithms are used to control generator sets' connection to the Internet of Things, then the system structure remains simple, but the effectiveness of access control deteriorates due to not considering gain and loss values
Solution Approach 1:
The patent introduces new parameters (information gain value and information loss value) to transform the access control problem from a simple binary decision into a multi-parameter evaluation system. By calculating these parameters based on data quality, transmission stability, and market trading requirements, the system achieves more reliable access control decisions while maintaining manageable complexity through structured parameter computation.
2Measurement precision
If fuzzy set method is used to calculate information gain and loss values, then the access control effectiveness improves, but the calculation complexity increases
Solution Approach 1:
The patent introduces fuzzy set theory as an intermediary mechanism to bridge the gap between raw data parameters and access control decisions. The fuzzy membership functions serve as mediators that transform precise numerical inputs (data quality metrics, transmission stability) into graded trust degree outputs, enabling precise evaluation while managing complexity through standardized fuzzy logic operations.
Solution Approach 2:
The patent transforms precise numerical parameters into fuzzy membership values through parameter transformation functions. By converting exact measurements of data quality and transmission stability into graded membership degrees (0 to 1), the system achieves precise trust degree evaluation while the fuzzy framework manages the computational complexity of handling uncertainty and imprecision in the input parameters.
3Manufacturing precision
If multiple information gain and loss values are calculated for different generator sets, then the access control decision accuracy improves, but the data processing time increases
Solution Approach 1:
The patent segments the access control evaluation process into distinct computational stages: calculating information gain values for each generator set, calculating information loss values separately, combining them into trust degrees, and finally making access decisions. This segmentation allows parallel computation of gain and loss values for multiple generator sets, improving decision accuracy while managing processing time through structured modular computation.
Data Source
AI summary
A method for security access to power Internet of Things, an apparatus, a storage medium and a system are provided. According to the method, a first information gain value and a second information gain value are acquired by using a fuzzy set method; a first total information loss value, a second total information loss value and a third total information loss value are acquired; and a trust degree is determined according to the first information gain value, the second information gain value, the first total information loss value, the second total information loss value and the third total information loss value, and one of the following is executed according to a range where the trust degree is located: a first processing mode, a second processing mode and a third processing mode.