Name
Title | ||
|---|---|---|
A Self-Adaptive Fuzzy Inference Model Based On Least Squares Svm For Estimating Compressive Strength Of Rubberized Concrete |
Abstract | ||
|---|---|---|
This paper presents an AI approach named as self-Adaptive fuzzy least squares support vector machines inference model (SFLSIM) for predicting compressive strength of rubberized concrete. The SFLSIM consists of a fuzzification process for converting crisp input data into membership grades and an inference engine which is constructed based on least squares support vector machines (LS-SVM). Moreover, the proposed inference model integrates differential evolution (DE) to adaptively search for the most appropriate profiles of fuzzy membership functions (MFs) as well as the LS-SVM's tuning parameters. In this study, 70 concrete mix samples are utilized to train and test the SFLSIM. According to experimental results, the SFLSIM can achieve a comparatively low MAPE which is less than 2%. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1142/S0219622016500140 | INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING |
Keywords | Field | DocType |
Rubberized concrete, strength estimate, fuzzy logic, least squares support vector machines, differential evolution | Least squares,Least squares support vector machine,Inference,Support vector machine,Fuzzy logic,Fuzzy set,Inference engine,Artificial intelligence,Adaptive neuro fuzzy inference system,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
15 | 3 | 0219-6220 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Min-Yuan Cheng | 1 | 174 | 19.84 |
| Nhat-Duc Hoang | 2 | 64 | 12.96 |