NDLI: Multiobjective evolutionary optimization of quadratic Takagi-Sugeno fuzzy rules for remote bathymetry estimation

Content Provider	IEEE Xplore Digital Library
Author	Cococcioni, M. Lazzerini, B.
Copyright Year	2015
Description	Author affiliation: Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy (Cococcioni, M.; Lazzerini, B.)
Abstract	In this work we tackle the problem of bathymetry estimation using: i) a multispectral optical image of the region of interest, and ii) a set of in situ measurements. The idea is to learn the relation that between the reflectances and the depth using a supervised learning approach. In particular, quadratic Takagi-Sugeno fuzzy rules are used to model this relation. The rule base is optimized by means of a multiobjective evolutionary algorithm. To the best of our knowledge this work represents the first use of a quadratic Takagi-Sugeno fuzzy system optimized by a multiobjective evolutionary algorithm with bounded complexity, i.e., able to control the complexity of the consequent part of second-order fuzzy rules. This model has an outstanding modeling power, without inheriting the drawback of complexity due to the use of quadratic functions (which have complexity that scales quadratically with the number of inputs). This opens the way to the use of the proposed approach even for medium/high dimensional problems, like in the case of hyper-spectral images.
Starting Page	1
Ending Page	6
File Size	301041
Page Count	6
File Format	PDF
e-ISBN	9781479987368
DOI	10.1109/OCEANS-Genova.2015.7271447
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-18
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Complexity theory Fuzzy systems Estimation Accuracy Optical sensors Optimization Optical imaging multiobjective evolutionary algorithms Bathymetry estimation quadratic Takagi-Sugeno fuzzy rules remotely sensed optical images
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Fast Multiobjective Genetic Rule Learning Using an Efficient Method for Takagi-Sugeno Fuzzy Systems Identification

A hybrid continuity preserving inference strategy to speed up Takagi-Sugeno multiobjective genetic fuzzy systems

Identification of Takagi-Sugeno (TS) fuzzy model with Evolutionary Parallel Gradient Search

Evolutionary multiobjective optimization and multiobjective fuzzy system design

Parameter optimization for Takagi-Sugeno fuzzy models-lessons learnt

Generation of Takagi-Sugeno fuzzy systems with minimum rules in modeling and identification

Rule base normalization in Takagi-Sugeno ensemble

Evaluation and analysis of fusion algorithms for active and passive remote sensing image

Robust Takagi-Sugeno fuzzy control for systems with static nonlinearity and time-varying delay

Multiobjective evolutionary optimization of quadratic Takagi-Sugeno fuzzy rules for remote bathymetry estimation

Similar Documents

Fast Multiobjective Genetic Rule Learning Using an Efficient Method for Takagi-Sugeno Fuzzy Systems Identification

A hybrid continuity preserving inference strategy to speed up Takagi-Sugeno multiobjective genetic fuzzy systems

Identification of Takagi-Sugeno (TS) fuzzy model with Evolutionary Parallel Gradient Search

Evolutionary multiobjective optimization and multiobjective fuzzy system design

Parameter optimization for Takagi-Sugeno fuzzy models-lessons learnt

Generation of Takagi-Sugeno fuzzy systems with minimum rules in modeling and identification

Rule base normalization in Takagi-Sugeno ensemble

Evaluation and analysis of fusion algorithms for active and passive remote sensing image

Robust Takagi-Sugeno fuzzy control for systems with static nonlinearity and time-varying delay

Multiobjective evolutionary optimization of quadratic Takagi-Sugeno fuzzy rules for remote bathymetry estimation