Machine learning-based methods in structural reliability analysis: A review

(1977). Methods for Statistical Analysis of Reliability and Life Data. Journal of Quality Technology: Vol. 9, No. 1, pp. 44-45.

Methods for Statistical Analysis of Reliability and Life Data

Machine Learning-Based Methods in Structural Reliability Analysis: A Review

Support vector clustering algorithm and fuzzy decision are applied to optimizing reliability allocation model for modular software systems in this paper, The factor set of reliability level and the weight of factor are established and the membership degree of the software module-the factor is obtained using expert information and SVM optimum clustering by analyzing the influential factors of reliability allocation, appointed reliability index of software system is distributed rationally to the module and further synthesis decision-making based on attachment degree of every factor. Both reliability of whole system are ensured and production cost and development period are reduced. The model is simulated and calculated by the example for software reliability of electric-hydraulic proportional control system, decision shows reliability of position control and real-time management module is the biggest, secondly parameter control module, initialization preprocessing module, fault-diagnosis module respectively.

Optimal Reliability Allocation for Modular Software Systems Basis on Support Vector Clustering and Fuzzy Decision

Software reliability allocation method of the optimization decision making based on fuzzy synthesis evaluation is presented aiming at the disadvantage of the other software reliability allocation method. By analyzing the influential factors of reliability allocation, appointed reliability index of software system is distributed rationally to module by establishing factor collection of reliability level and the weight of factor and further synthesis decision-making based on attachment degree of every factor. Both reliability of whole system are ensured and production cost and exploitation period are reduced. The model is simulated and calculated by the example of numerical control system software reliability, decision-making shows reliability of position control and real-time management module is the biggest, secondly PLC module, initialization preprocessing module, coding show module respectively. It provides a feasible method for software system reliability optimum design.

Fuzzy Synthesis-Decision Model of Software Optimum Design

The discrimination of parameter probability distribution type is the key to structure reliability analysis. A support vector machine (SVM) intelligent recognition model of probability distribution law is presented aiming at traditional method disadvantage. The intelligent recognition model of probability distribution is constructed by SVM algorithm realization, network design and feature extraction, inward stress probability distribution type of a stem structural member is recognized by the model, recognition result is Weibull distribution, SVM has a good generalization ability and clustering ability by comparison between network recognition result and regression analysis, the experiment result shows total recognition rate achieved 98.25%, it provides a good new method for structure reliability analysis.

Study on Parameter Distribution in Structure Reliability Analysis: Machine Learning Algorithm and Application

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Study on Parameter Distribution in Structure Reliability Analysis: Machine Learning Algorithm and Application