Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Probabilities, possibilities, and fuzzy sets
Fuzzy Sets and Systems
On types of fuzzy numbers and extension principles
Fuzzy Sets and Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Zadeh's extension principle in design reliability
Fuzzy Sets and Systems - Special issue on fuzzy methodology in system failure engineering
On a class of fuzzy c-numbers clustering procedures for fuzzy data
Fuzzy Sets and Systems
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
A defuzzification method respecting the fuzzification
Fuzzy Sets and Systems
Management of uncertainty and vagueness in databases: the firms point of view
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Fuzzy Control and Fuzzy Systems
Fuzzy Control and Fuzzy Systems
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
A formal approach to fuzzy modeling
IEEE Transactions on Fuzzy Systems
Artificial Intelligence technique for modelling and forecasting of solar radiation data: a review
International Journal of Artificial Intelligence and Soft Computing
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Solar irradiance is an extreme case of an uncertain variable when measured on an hourly, or shorter time interval. In this paper solar irradiance has been considered as a case study for physical fuzzy modelling of a climate variable. The uncertainty of the solar irradiance is treated as a fuzzy uncertainty whilst other variables are considered crisp. The approach is robust as it does not rely on statistical assumptions, and it is a possible alternative to modelling complex systems. To our knowledge, this is the first time that a physical model of a meteorological variable based on fuzzy numbers has been proposed. Previous rule-based fuzzy meteorological models are only descriptive, and cannot be extrapolated to non-measured cases. When compared with previous non-fuzzy models of solar irradiance, the fuzzy model shows an improved performance, and when compared with experimental data, the performance can be evaluated by fuzzy indices that take into account the uncertainty of the data and the model output.