Double Inverted Pendulum Control Based on Support Vector Machines and Fuzzy Inference

2006 ◽  
pp. 1124-1130 ◽  
Author(s):  
Han Liu ◽  
Haiyan Wu ◽  
Fucai Qian
Keyword(s):  
Support Vector Machines ◽  
Inverted Pendulum ◽  
Fuzzy Inference ◽  
Support Vector ◽  
Vector Machines

A Self-Adaptive Fuzzy Inference Model Based on Least Squares SVM for Estimating Compressive Strength of Rubberized Concrete

2016 ◽  
Vol 15 (03) ◽  
pp. 603-619 ◽  
Author(s):  
Min-Yuan Cheng ◽  
Nhat-Duc Hoang
Keyword(s):  
Compressive Strength ◽  
Support Vector Machines ◽  
Least Squares ◽  
Fuzzy Inference ◽  
Support Vector ◽  
Rubberized Concrete ◽  
Inference Model ◽  
Adaptive Fuzzy ◽  
Vector Machines ◽  
Self Adaptive

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%.

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