Analyzing a sustainability indicator by means of qualitative kernels:

N. Agell; Cecilio Angulo Bahón; Andreu Català; Luis González; Francisco Javier Ruiz Vegas; Francisco Velasco

Analyzing a sustainability indicator by means of qualitative kernels

N. Agell, Cecilio Angulo Bahón, Andreu Català, Luis González, Francisco Javier Ruiz Vegas, Francisco Velasco

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Research output: Book chapter › Chapter

Abstract

This chapter presents two totally new inference techniques for the field of interval and qualitative analysis, based on the kernel methods and statistical learning methodology, which have been shown to be very effective as machine learning. Moreover, on using them it is possible to work on any original space, and it is not necessary to work with numerical values (bioinformatics, string-type kernels). This study analyzes two approaches oriented at sustainability data: kernels on a discrete structure (the orders of magnitude) and interval kernels. Their good characteristics are studied with several examples, and an initial application to the sustainability data of the Town Council of Vilanova is performed. Finally, the feasibility is analyzed of a soft-computing tool which allows the degree of citizen satisfaction to be qualitatively assessed.

Original language	English
Title of host publication	Advanced methods for decision making and risk management in sustainability science
Pages	129-142
Publication status	Published - 1 Oct 2007

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title = "Analyzing a sustainability indicator by means of qualitative kernels",

abstract = "This chapter presents two totally new inference techniques for the field of interval and qualitative analysis, based on the kernel methods and statistical learning methodology, which have been shown to be very effective as machine learning. Moreover, on using them it is possible to work on any original space, and it is not necessary to work with numerical values (bioinformatics, string-type kernels). This study analyzes two approaches oriented at sustainability data: kernels on a discrete structure (the orders of magnitude) and interval kernels. Their good characteristics are studied with several examples, and an initial application to the sustainability data of the Town Council of Vilanova is performed. Finally, the feasibility is analyzed of a soft-computing tool which allows the degree of citizen satisfaction to be qualitatively assessed.",

author = "N. Agell and {Angulo Bah{\'o}n}, Cecilio and Andreu Catal{\`a} and Luis Gonz{\'a}lez and {Ruiz Vegas}, {Francisco Javier} and Francisco Velasco",

year = "2007",

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T1 - Analyzing a sustainability indicator by means of qualitative kernels

AU - Agell, N.

AU - Angulo Bahón, Cecilio

AU - Català, Andreu

AU - González, Luis

AU - Ruiz Vegas, Francisco Javier

AU - Velasco, Francisco

PY - 2007/10/1

Y1 - 2007/10/1

N2 - This chapter presents two totally new inference techniques for the field of interval and qualitative analysis, based on the kernel methods and statistical learning methodology, which have been shown to be very effective as machine learning. Moreover, on using them it is possible to work on any original space, and it is not necessary to work with numerical values (bioinformatics, string-type kernels). This study analyzes two approaches oriented at sustainability data: kernels on a discrete structure (the orders of magnitude) and interval kernels. Their good characteristics are studied with several examples, and an initial application to the sustainability data of the Town Council of Vilanova is performed. Finally, the feasibility is analyzed of a soft-computing tool which allows the degree of citizen satisfaction to be qualitatively assessed.

AB - This chapter presents two totally new inference techniques for the field of interval and qualitative analysis, based on the kernel methods and statistical learning methodology, which have been shown to be very effective as machine learning. Moreover, on using them it is possible to work on any original space, and it is not necessary to work with numerical values (bioinformatics, string-type kernels). This study analyzes two approaches oriented at sustainability data: kernels on a discrete structure (the orders of magnitude) and interval kernels. Their good characteristics are studied with several examples, and an initial application to the sustainability data of the Town Council of Vilanova is performed. Finally, the feasibility is analyzed of a soft-computing tool which allows the degree of citizen satisfaction to be qualitatively assessed.

M3 - Chapter

SN - 1-60021-427-4

SP - 129

EP - 142

BT - Advanced methods for decision making and risk management in sustainability science

ER -

Analyzing a sustainability indicator by means of qualitative kernels

Abstract

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