Neuro-fuzzy Classification of Submarine Lava Flow Morphology

2012 ◽  
Vol 78 (6) ◽  
pp. 605-616 ◽  
Author(s):  
J. Timothy McClinton ◽  
Scott M. White ◽  
John M. Sinton
Keyword(s):  
Lava Flow ◽  
Fuzzy Classification ◽  
Neuro Fuzzy ◽  
Submarine Lava ◽  
Flow Morphology

scholarly journals A Framework of A Ship Domain-Based Near-Miss Detection Method Using Mamdani Neuro-Fuzzy Classification

2018 ◽  
Vol 25 (s1) ◽  
pp. 14-21 ◽  
Author(s):  
Rafał Szłapczyński ◽  
Tacjana Niksa-Rynkiewicz
Keyword(s):  
Risk Measures ◽  
Risk Measure ◽  
Near Miss ◽  
Fuzzy Classification ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Neuro Fuzzy ◽  
Fuzzy Network

Abstract Safety analysis of navigation over a given area may cover application of various risk measures for ship collisions. One of them is percentage of the so called near-miss situations (potential collision situations). In this article a method of automatic detection of such situations based on the data from Automatic Identification System (AIS), is proposed. The method utilizes input parameters such as: collision risk measure based on ship’s domain concept, relative speed between ships as well as their course difference. For classification of ships encounters, there is used a neuro-fuzzy network which estimates a degree of collision hazard on the basis of a set of rules. The worked out method makes it possibile to apply an arbitrary ship’s domain as well as to learn the classifier on the basis of opinions of experts interpreting the data from the AIS.

scholarly journals REGION-BASED CLASSIFICATION OF ELECTRO-OPTICAL IMAGES WITH NEURAL NETWORKS AND FUZZY LOGIC

2014 ◽  
pp. 117-123
Author(s):  
Iryna Petrosyuk ◽  
Yuri Zaichenko
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Classification ◽  
Unification Algorithm ◽  
Sensing Systems ◽  
Optical Images ◽  
Novel Approach ◽  
The Neural Network ◽  
Neuro Fuzzy ◽  
Remote Sensing Systems

This paper reports on a novel approach to the optical information processing for the hyperspectral remote sensing systems by means of developed unification algorithm of the two mathematical tools: the fuzzy logic and the neural network. New neuro-fuzzy classification algorithm for hyperspectral remote sensed images has been proposed. It is able to replace complicated empirical formulae, which require the knowledge of dependences of many input parameters that rapidly change during of range time and difficult for crisp determination.

Segmentation of radiographic cervical images with neuro-fuzzy classification of multiresolution wavelets

1995 ◽  
Author(s):  
Suryalakshmi Pemmaraju ◽  
Sunanda Mitra ◽  
Yao-Yang Shieh ◽  
Glenn H. Roberson
Keyword(s):  
Fuzzy Classification ◽  
Neuro Fuzzy ◽  
Multiresolution Wavelets
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