Package: fispro
Version: 3.5-1
Architecture: i386
Maintainer: bch <bch@supagro.inra.fr>
Installed-Size: 53656
Depends: libc6 (>= 2.4), libgcc1 (>= 1:3.4), libgsl23, libgslcblas0, libstdc++6 (>= 5.2), openjdk-8-jre | openjdk-7-jre, libgsl2 | libgsl0ldbl
Filename: ./i386/fispro_3.5-1_i386.deb
Size: 14393296
MD5sum: 1dc00262c75167f4d5bc2b7ed25802b0
SHA1: 6b5e44a111d87e255e7947b96cc82ab2c88e8358
SHA256: 89fab30bea1e03823b0fd3009f4959805b80a539b2d7f969178854a17fc1874a
Section: Math
Priority: optional
Description: fuzzy inference system design
 FisPro (Fuzzy Inference System Professional) allows to create fuzzy inference systems and to use them for reasoning purposes.
 They are based on fuzzy rules, which have a good capability for managing progressive phenomenons.
 Fuzzy logic, since the pioneer work by Zadeh, has proven to be a powerful interface between symbolic and numerical spaces.
 One of the reasons for this success is the ability of fuzzy systems to incorporate human expert knowledge with its nuances,
 as well as to express the behaviour of the system in an interpretable way for humans.
 Another reason is the possibility of designing data-driven FIS to make the most of available data.
   FisPro implementation allows to design fuzzy systems from expert knowledge or data.
 This package provides FisPro Java interface and C++ programs.

Package: fispro
Version: 3.5-1
Architecture: amd64
Maintainer: bch <bch@supagro.inra.fr>
Installed-Size: 53471
Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.4), libgsl23, libgslcblas0, libstdc++6 (>= 5.2), openjdk-8-jre | openjdk-7-jre, libgsl2 | libgsl0ldbl
Filename: ./amd64/fispro_3.5-1_amd64.deb
Size: 14381920
MD5sum: 8e8c41fe28be23e42cdfd54f07d5579a
SHA1: 0bf59d13c3d75a27eccd5e4a04e7b74d9fd04515
SHA256: efb50256de36158155b129e0c50887d74d9888d5fca5b04bb0057724d890dba8
Section: Math
Priority: optional
Description: fuzzy inference system design
 FisPro (Fuzzy Inference System Professional) allows to create fuzzy inference systems and to use them for reasoning purposes.
 They are based on fuzzy rules, which have a good capability for managing progressive phenomenons.
 Fuzzy logic, since the pioneer work by Zadeh, has proven to be a powerful interface between symbolic and numerical spaces.
 One of the reasons for this success is the ability of fuzzy systems to incorporate human expert knowledge with its nuances,
 as well as to express the behaviour of the system in an interpretable way for humans.
 Another reason is the possibility of designing data-driven FIS to make the most of available data.
   FisPro implementation allows to design fuzzy systems from expert knowledge or data.
 This package provides FisPro Java interface and C++ programs.