In this thesis we present a Regularization Network approach to reconstruct a continuous
function ƒ:[0, 1] n→ R from its function values ƒ (xj) on discrete data points xj, j= 1,…, P. The …

With the emergence of customisation services, business-to-business price negotiation plays
an increasingly important role in economic and management science. Negotiation pricing …

In the last 20years, while most research on fuzzy approximation theory has focused on
nonadaptive fuzzy systems, little work has been done on adaptive fuzzy systems. This paper …

In this paper, we utilize generalized Bernstein polynomials to construct fuzzy system.
Different from traditional Bernstein polynomials, partition of interval on input variable can be …

Cascade process, such as wastewater treatment plant, includes many nonlinear sub-
systems and many variables. When the number of sub-systems is big, the input-output …

When applying gradient descent learning methods to hierarchical fuzzy systems, there is
great difficulty in handling the intermediate variables introduced by the hierarchical …

Fuzzy rule interpolation offers a useful means for reducing the complexity of fuzzy models,
more importantly, it makes inference possible in sparse rule-based systems. Backward fuzzy …

The core of fuzzy system is to bypass the establishment of a definite mathematical model to
carry out logical reasoning and intelligent calculation for fuzzy information; its main method …

Hierarchical fuzzy neural networks can use less rules to model nonlinear system with high
accuracy. But the normal training method for hierarchical fuzzy neural networks is very …

Real-world systems usually involve both continuous and discrete input variables. However,
in existing learning algorithms of both neural networks and fuzzy systems, these mixed …