A Review of Modeling and Data Mining Techniques Applied for Analyzing Steel Bridges

Abstract

The vibration response data measured from the structure contains uncertainties and requires different techniques for its analysis. The present study involves the comprehensive review of the model based and data mining techniques which are frequently applied by various researchers in past to solve various multi criteria decision making and analysis problems. The selection of suitable technique for specific problem is required to obtain accurate outcomes. The literature survey is done to provide summary of articles with used data type, involved uncertainty type, and technique used. The uncertainty in the input data can be due to ambiguity, randomness, and partial information. The paper includes brief about Stochastic, Statistical and Computer based modeling techniques and Artificial Neural Networks (ANN), Fuzzy logic, Support vector machine (SVM), Bayesian classifiers (BC), and Cluster algorithms based data mining techniques. The advantages and disadvantages of each technique are also mentioned.