7,317 research outputs found
Fuzzy integral for rule aggregation in fuzzy inference systems
The fuzzy inference system (FIS) has been tuned and re-vamped many times over and applied to numerous domains. New and improved techniques have been presented for fuzzification, implication, rule composition and defuzzification, leaving one key component relatively underrepresented, rule aggregation. Current FIS aggregation operators are relatively simple and have remained more-or-less unchanged over the years. For many problems, these simple aggregation operators produce intuitive, useful and meaningful results. However, there exists a wide class of problems for which quality aggregation requires non- additivity and exploitation of interactions between rules. Herein, we show how the fuzzy integral, a parametric non-linear aggregation operator, can be used to fill this gap. Specifically, recent advancements in extensions of the fuzzy integral to \unrestricted" fuzzy sets, i.e., subnormal and non- convex, makes this now possible. We explore the role of two extensions, the gFI and the NDFI, discuss when and where to apply these aggregations, and present efficient algorithms to approximate their solutions
Validation and Verification of Aircraft Control Software for Control Improvement
Validation and Verification are important processes used to ensure software safety and reliability. The Cooper-Harper Aircraft Handling Qualities Rating is one of the techniques developed and used by NASA researchers to verify and validate control systems for aircrafts. Using the Validation and Verification result of controller software to improve controller\u27s performance will be one of the main objectives of this process. Real user feedback will be used to tune PI controller in order for it to perform better. The Cooper-Harper Aircraft Handling Qualities Rating can be used to justify the performance of the improved system
Multi-objective genetic optimisation for self-organising fuzzy logic control
This is the post-print version of the article. The official published version can be accessed from the link below.A multi-objective genetic algorithm is developed for the purpose of optimizing the rule-base of a Self-Organising Fuzzy Logic Control algorithm (SOFLC). The tuning of the SOFLC optimization is based on selection of the best shaped performance index for modifying the rule-base on-line. A comparative study is conducted between various methods of multi-objective genetic optimisation using the SOFLC algorithm on the muscle relaxant anaesthesia system, which includes a severe non-linearity, varying dynamics and time-delay
Hybridisation for versatile decision-making in game opponent AI
Hybridisation for versatile decision-making in game opponent A
Hardware/software codesign methodology for fuzzy controller implementation
This paper describes a HW/SW codesign methodology
for the implementation of fuzzy controllers on a platform
composed by a general-purpose microcontroller and specific
processing elements implemented on FPGAs or ASICs. The
different phases of the methodology, as well as the CAD tools
used in each design stage, are presented, with emphasis on the
fuzzy system development environment Xfuzzy. Also included is
a practical application of the described methodology for the
development of a fuzzy controller for a dosage system
Synergy Modelling and Financial Valuation : the contribution of Fuzzy Integrals.
Les mĂ©thodes dâĂ©valuation financiĂšre utilisent des opĂ©rateurs dâagrĂ©gation reposant sur les propriĂ©tĂ©s dâadditivitĂ© (sommations, intĂ©grales de Lebesgue). De ce fait, elles occultent les phĂ©nomĂšnes de renforcement et de synergie (ou de redondance) qui peuvent exister entre les Ă©lĂ©ments dâun ensemble organisĂ©. Câest particuliĂšrement le cas en ce qui concerne le problĂšme dâĂ©valuation financiĂšre du patrimoine dâune entreprise : en effet, en pratique, il est souvent mis en Ă©vidence une importante diffĂ©rence de valorisation entre lâapproche « valeur de la somme des Ă©lĂ©ments » (privilĂ©giant le point de vue financier) et lâapproche « somme de la valeur des diffĂ©rents Ă©lĂ©ments » (privilĂ©giant le point de vue comptable). Les possibilitĂ©s offertes par des opĂ©rateurs dâagrĂ©gation comme les intĂ©grales floues (Sugeno, Grabisch, Choquet) permettent, au plan thĂ©orique, de modĂ©liser lâeffet de synergie. La prĂ©sente Ă©tude se propose de valider empiriquement les modalitĂ©s dâimplĂ©mentation opĂ©rationnelle de ce modĂšle Ă partir dâun Ă©chantillon dâentreprises cotĂ©es ayant fait lâobjet dâune Ă©valuation lors dâune OPA.Financial valuation methods use additive aggregation operators. But a patrimony should be regarded as an organized set, and additivity makes it impossible for these aggregation operators to formalize such phenomena as synergy or mutual inhibition between the patrimonyâs components. This paper considers the application of fuzzy measure and fuzzy integrals (Sugeno, Grabisch, Choquet) to financial valuation. More specifically, we show how integration with respect to a non additive measure can be used to handle positive or negative synergy in value construction.Fuzzy measure; Fuzzy integral; Aggregation operator; Synergy; Financial valuation;
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