Extending the functional equivalence of radial basis functionnetworks and fuzzy inference systems

We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditions of the previous result

Real exchange rate dynamics in transition economies : a nonlinear analysis

We examine the behavior of the real exchange rates of nine transition economies during the 1990s. We propose an empirical model rationalized on the basis of standard economic models in the tradition of Mundell-Fleming-Dornbusch and Harrod-Balassa-Samuelson, allowing explicitly for real interest rate differentials and (implicitly) for productivity differentials to have an impact on real exchange rate equilibrium and employing nonlinear modeling techniques that are consistent with recently developed economic theories and observed regularities. Using a nonlinear multivariate generalization of the Beveridge-Nelson decomposition applied to our models, we also identify the permanent and temporary components of these real exchange rates implied by our estimates. The results have a natural interpretation and clear policy implications

Modelling dynamic decision making with the ACT-R cognitive architecture

This paper describes a model of dynamic decision making in the Dynamic Stocks and Flows (DSF) task, developed using the ACT-R cognitive architecture. This task is a simple simulation of a water tank in which the water level must be kept constant whilst the inflow and outflow changes at varying rates. The basic functions of the model are based around three steps. Firstly, the model predicts the water level in the next cycle by adding the current water level to the predicted net inflow of water. Secondly, based on this projection, the net outflow of the water is adjusted to bring the water level back to the target. Thirdly, the predicted net inflow of water is adjusted to improve its accuracy in the future. If the prediction has overestimated net inflow then it is reduced, if it has underestimated net inflow it is increased. The model was entered into a model comparison competition-the Dynamic Stocks and Flows Challenge-to model human performance on four conditions of the DSF task and then subject the model to testing on five unseen transfer conditions. The model reproduced the main features of the development data reasonably well but did not reproduce human performance well under the transfer conditions. This suggests that the principles underlying human performance across the different conditions differ considerably despite their apparent similarity. Further lessons for the future development of our model and model comparison challenges are considered

Similarity Rule for Dynamic Model Tests of Geotechnical Structures

Soils and rocks are characterized by their highly nonlinear behaviors. This makes it very difficult to ensure similarity between model and prototype for dynamic model tests of geotechnical structures. In reality, a great number of such tests were carried out qualitatively, and valuable information was missed. Based on fairly long time practice and experience of performing dynamic model tests, we get some new ideas to establish similarity relationships between model and real earth structures. It is noticed that during strongly inelastic shaking, peak crest acceleration of earth and rock-fill dams decreases with increasing base excitation, finally at near failure stage the dynamic amplification tends to the uniformly distributed along the dam height and approaches 1.0, despite the variation of inhomogeneity of the dam materials. Results of centrifuge modeling and field earthquake measurements also support such findings. Keeping these in mind, a rather simple dynamic similarity rule may be derived

Optimization under fuzzy rule constraints

Suppose we are given a mathematical programming problem in which the functional relationship between the decision variables and the objective function is not completely known. Our knowledge-base consists of a block of fuzzy if-then rules, where the antecedent part of the rules contains some linguistic values of the decision variables, and the consequence part is a linear combination of the crisp values of the decision variables. We suggest the use of Takagi and Sugeno fuzzy reasoning method to determine the crisp functional relationship between the objective function and the decision variables, and solve the resulting (usually nonlinear) programming problem to find a fair optimal solution to the original fuzzy problem

Estimating Connecticut Stream Temperatures Using Predictive Models

The Connecticut Department of Energy and Environmental Protection (CT DEEP) seeks to better classify their streams into thermal regimes (cold, cold transitional, warm transitional, and warm water). A prediction model was created based upon physical characteristics such that CT DEEP could classify streams into thermal regimes based upon the parameters described in Lyons et al. 2009 and compare them to their own classification system. Accurately classifying these thermal regimes determines the environmental protection provided to a stream as well as the potential for establishing fisheries

Mean reversion in stock index futures markets: a nonlinear analysis

Several stylized theoretical models of futures basis behavior under nonzero transactions costs predict nonlinear mean reversion of the futures basis towards its equilibrium value. Nonlinearly mean-reverting models are employed to characterize the basis of the SandP 500 and the FTSE 100 indices over the post-1987 crash period, capturing empirically these theoretical predictions and examining the view that the degree of mean reversion in the basis is a function of the size of the deviation from equilibrium. The estimated half lives of basis shocks, obtained using Monte Carlo integration methods, suggest that for smaller shocks to the basis level the basis displays substantial persistence, while for larger shocks the basis exhibits highly nonlinear mean reversion towards its equilibrium value. © 2002 Wiley Periodicals, Inc