• DENFIS

  • Referenced in 58 articles [sw24183]
  • through local element tuning. New fuzzy rules are created and updated during the operation ... system based on m-most activated fuzzy rules which are dynamically chosen from a fuzzy ... first-order Takagi-Sugeno-type fuzzy rule set for a DENFIS online model ... first-order Takagi-Sugeno-type fuzzy rule set, or an expanded high-order...
  • ANFIS

  • Referenced in 266 articles [sw08730]
  • knowledge (in the form of fuzzy if-then rules) and stipulated input-output data pairs ... artificial neural networks and earlier work on fuzzy modeling are listed and discussed. Other extensions...
  • Fuzzy Logic Toolbox

  • Referenced in 56 articles [sw07379]
  • provided for many common methods, including fuzzy clustering and adaptive neurofuzzy learning. The toolbox lets ... rules, and then implement these rules in a fuzzy inference system...
  • FURIA

  • Referenced in 12 articles [sw19135]
  • FURIA: an algorithm for unordered fuzzy rule induction. This paper introduces a novel fuzzy rule ... called FURIA, which is short for Fuzzy Unordered Rule Induction Algorithm. FURIA extends the well ... advantages, such as simple and comprehensible rule sets. In addition, it includes a number ... extensions. In particular, FURIA learns fuzzy rules instead of conventional rules and unordered rule sets...
  • FRI

  • Referenced in 9 articles [sw07389]
  • Fuzzy rule interpolation Matlab toolbox-FRI toolbox. Fuzzy systems use fuzzy rule base to make ... inference. A fuzzy rule base is fully covered (at level α), if all input universes ... rules at level α . Such fuzzy rule bases are also called dense or complete rule ... acceptable output for such cases. Fuzzy rule based interpolation (FRI) techniques were introduced to generate...
  • GenSoFNN

  • Referenced in 9 articles [sw08761]
  • essentially fuzzy systems with self-tuning capabilities and requires an initial rule base ... able to automatically formulate the fuzzy rules from the numerical training data. No initial rule ... training data and the fuzzy rules are subsequently derived through the proper connections of these ... discrete incremental clustering (DIC). The fuzzy rule base of the GenSoFNN network is consistent...
  • GP-COACH

  • Referenced in 10 articles [sw09137]
  • based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems ... learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems ... population and this obliges the rules to compete and cooperate among themselves and allows ... obtaining of a compact set of fuzzy rules. The results obtained have been validated...
  • RSPOP

  • Referenced in 6 articles [sw02562]
  • RSPOP: set-based pseudo outer-product fuzzy rule identification algorithm. System modeling with neuro-fuzzy ... increase in the number of identified fuzzy rules and computational complexity arising from high-dimensional ... using the proposed algorithm to identify fuzzy rules in the POPFNN using compositional rule ... fuzzy systems by identifying significantly fewer fuzzy rules, and improves the accuracy of the POPFNN...
  • HyFIS

  • Referenced in 12 articles [sw24184]
  • meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions ... hybrid learning scheme comprised of two phases: rule generation phase from data ... rule tuning phase using error backpropagation learning scheme for a neural fuzzy system. To illustrate...
  • PANFIS

  • Referenced in 6 articles [sw13735]
  • uneasy to be overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in nonstationary environment entails ... with an empty rule base. The fuzzy rules can be stitched up and expelled ... virtue of statistical contributions of the fuzzy rules and injected datum afterward. Identical fuzzy sets ... fuzzy set as a pursuit of a transparent rule base escalating human’s interpretability...
  • FisPro

  • Referenced in 9 articles [sw16651]
  • user documentation. They are based on fuzzy rules, which have a good capability for managing ... this success is the ability of fuzzy systems to incorporate human expert knowledge with ... concentrated our efforts on three points: The rule base interpretability. This is the main originality...
  • LFLC 2000

  • Referenced in 11 articles [sw08217]
  • given situation using fuzzy IF-THEN rules. The rules are interpreted either as fuzzy relations ... IRAFM. Sets of linguistically interpreted fuzzy IF-THEN rules are called linguistic descriptions. They ... following publications are recommended: detailed treatment of fuzzy logic can be found...
  • SparseFIS

  • Referenced in 10 articles [sw13736]
  • Takagi-Sugeno (T-S) fuzzy systems, extended by including rule weights. Our learning method consists ... fuzzy sets (centers and widths) in the antecedent parts of the rules. Hereby, the number ... second phase optimizes the rule weights in the fuzzy systems with respect to least-squares ... threshold, weights of many or a few rules can be forced toward 0, thereby, switching...
  • ANCFIS

  • Referenced in 7 articles [sw34242]
  • neurofuzzy system architecture to implement complex fuzzy rules (and, in particular, the signature property ... rule interference). We have applied this neurofuzzy system to the domain of time-series forecasting ... This work demonstrates the utility of complex fuzzy logic on real-world problems...
  • FuzzyCLIPS

  • Referenced in 6 articles [sw07001]
  • represent and manipulate fuzzy facts and rules. FuzzyCLIPS can deal with exact, fuzzy (or inexact ... reasoning, allowing fuzzy and normal terms to be freely mixed in the rules and facts...
  • FIRBS

  • Referenced in 6 articles [sw06572]
  • decision expert system. More precisely a fuzzy inference rule based system (FIRBS) is implemented...
  • FuzzyJ

  • Referenced in 3 articles [sw10659]
  • used standalone to create fuzzy rules and do reasoning, however, it can also be used...
  • NEFCLASS-X

  • Referenced in 4 articles [sw27865]
  • systems offer a means of obtaining fuzzy classification rules by a learning algorithm. Although ... usually no problem to find a suitable fuzzy classifier by learning from data ... shown how a readable fuzzy classifier can be obtained by a learning process ... interactive strategies for pruning rules and variables from a trained classifier can enhance its interpretability...
  • GENEFER

  • Referenced in 1 article [sw16838]
  • based approach which we model using fuzzy rule bases. For example if a single agent ... discourse. In order to learn a fuzzy rule base from examples we introduce genetic algorithms ... been developed for designing such a fuzzy rule base. The design process is modular ... neural learning algorithms for optimizing the fuzzy rule base...