The local paradigm for modeling and control: From neuro-fuzzy to lazy learning

DOI10.1016/S0165-0114(99)00172-4zbMath0978.93528WikidataQ62672056 ScholiaQ62672056MaRDI QIDQ5947594

Mauro Birattari, Hugues Bersini, Gianluca Bontempi

Publication date: 4 February 2002

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Fuzzy control/observation systems (93C42)

Related Items (7)

Mathematical modeling of observed natural behavior: a fuzzy logic approach ⋮ Using local learning with fuzzy transform: application to short term forecasting problems ⋮ Online affine model identification of nonlinear processes using a new adaptive neuro-fuzzy approach ⋮ Credit scoring with drift adaptation using local regions of competence ⋮ A process transfer model-based optimal compensation control strategy for batch process using just-in-time learning and trust region method ⋮ Data-driven techniques for direct adaptive control: The lazy and the fuzzy approaches ⋮ The local paradigm for modeling and control: From neuro-fuzzy to lazy learning

Cites Work

• Theory and applications of adaptive control - a survey
• Structure identification of fuzzy model
• Current developments in time series modelling
• Stability analysis and design of fuzzy control systems
• A practical guide to splines
• Input-output parametric models for non-linear systems Part I: deterministic non-linear systems
• Fuzzy identification of systems and its applications to modeling and control
• Robust Locally Weighted Regression and Smoothing Scatterplots
• Constructing NARMAX models using ARMAX models
• Lazy learning for local modelling and control design
• Learning representations by back-propagating errors
• Nearest neighbor pattern classification
• The local paradigm for modeling and control: From neuro-fuzzy to lazy learning
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