scholarly journals Induced Rule-Based Fuzzy Inference System from Support Vector Machine Classifier for Anomalous Propagation Echo Detection

2016 ◽  
Vol 6 (2) ◽  
pp. 92-96
Author(s):  
Hansoo Lee ◽  
◽  
Yeongsang Jeong ◽  
Sungshin Kim
Keyword(s):  
Support Vector Machine ◽  
Fuzzy Inference System ◽  
Support Vector Machine Classifier ◽  
Fuzzy Inference ◽  
Support Vector ◽  
Inference System ◽  
Rule Based ◽  
Echo Detection ◽  
Anomalous Propagation

Daily Forecasting of Dam Water Levels: Comparing a Support Vector Machine (SVM) Model With Adaptive Neuro Fuzzy Inference System (ANFIS)

2013 ◽  
Vol 27 (10) ◽  
pp. 3803-3823 ◽  
Author(s):  
Afiq Hipni ◽  
Ahmed El-shafie ◽  
Ali Najah ◽  
Othman Abdul Karim ◽  
Aini Hussain ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Water Levels ◽  
Support Vector ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Svm Model

scholarly journals Intelligent Stereo Vision in Autonomous Robot Traversability Estimation

Robotics ◽  
2013 ◽  
pp. 350-365
Author(s):  
Lazaros Nalpantidis ◽  
Ioannis Kostavelis ◽  
Antonios Gasteratos
Keyword(s):  
Support Vector Machine ◽  
Stereo Vision ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Autonomous Robots ◽  
Specific Area ◽  
Support Vector ◽  
Inference System ◽  
Reliable Solution ◽  
Scene Depth

Traversability estimation is the process of assessing whether a robot is able to move across a specific area. Autonomous robots need to have such an ability to automatically detect and avoid non-traversable areas and, thus, stereo vision is commonly used towards this end constituting a reliable solution under a variety of circumstances. This chapter discusses two different intelligent approaches to assess the traversability of the terrain in front of a stereo vision-equipped robot. First, an approach based on a fuzzy inference system is examined and then another approach is considered, which extracts geometrical descriptions of the scene depth distribution and uses a trained support vector machine (SVM) to assess the traversability. The two methods are presented and discussed in detail.

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