A fast method for fuzzy neural modeling and refinement

In the identification of complex dynamic systems using fuzzy neural networks, one of the main issues is the curse of dimensionality, which makes it difficult to retain a large number of system inputs or to consider a large number of fuzzy sets. Moreover, due to the correlations, not all possible network inputs or regression vectors in the network are necessary and adding them simply increases the model complexity and deteriorates the network generalisation performance. In this paper, the problem is solved by first proposing a fast algorithm for selection of network terms, and then introducing a refinement procedure to tackle the correlation issue. Simulation results show the efficacy of the method.

Cumulative or sequential assessment during hermit crab shell fights: effects of oxygen on decision rules

Agonistic interactions between animals are often settled by the use of repeated signals which advertise the resource-holding potential of the sender. According to the sequential assessment game this repetition increases the accuracy with which receivers may assess the signal, but under the cumulative assessment model the repeated performances accumulate to give a signal of stamina. These models may be distinguished by the temporal pattern of signalling they predict and by the decision rules used by the contestants. Hermit crabs engage in shell fights over possession of the gastropod shells that they inhabit. During these interactions the two roles of signaller and receiver may be examined separately because they are fixed for the duration of the encounter. Attackers rap their shell against that of the defender in a series of bouts whereas defenders remain tightly withdrawn into their shells for the duration of the contest. At the end of a fight the attacker may evict the defender from its shell or decide to give up without first effecting an eviction; the decision for defenders is either to maintain a grip on its shell or to release the shell and allow itself to be evicted. We manipulated fatigue levels separately for attackers and defenders, by varying the oxygen concentration of the water that they are held in prior to fighting, and examined the effects that this has on the likelihood of each decision and on the temporal pattern of rapping. We show that the vigour of rapping and the likelihood of eviction are reduced when the attacker is subjected to low oxygen but that this treatment has no effect on rates of eviction when applied to defenders. We conclude that defenders compare the vigour of rapping with an absolute threshold rather than with a relative threshold when making their decision. The data are compatible with the cumulative assessment model and with the idea that shell rapping signals the stamina of attackers, but do not fit the predictions of the sequential assessment game.

Purchasing power parity versus fixed exchange rate rules: A stability and welfare analysis

This paper evaluates the desirability of PPP rules vis-á-vis fixed exchange rates both in terms of welfare and stability properties. The analysis is conducted within a small open-economy New Keynesian framework extended to include a cost channel. In terms of stability, we find that while the equilibrium is always unique under fixed exchange rates its uniqueness critically depends upon the presence/absence of the cost channel under a PPP rule. Overall, then, in terms of welfare a fixed exchange rate always outperforms a PPP rule.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.