A hybrid training method for B-spline neural networks

Current and past research has brought up new views related to the optimization of neural networks. For a fixed structure, second order methods are seen as the most promising. From previous works we have shown how second order methods are of easy applicability to a neural network. Namely, we have proved how the Levenberg-Marquard possesses not only better convergence but how it can assure the convergence to a local minima. However, as any gradient-based method, the results obtained depend on the startup point. In this work, a reformulated Evolutionary algorithm - the Bacterial Programming for Levenberg-Marquardt is proposed, as an heuristic which can be used to determine the most suitable starting points, therefore achieving, in most cases, the global optimum.

B-spline and neuro-fuzzy models design with function and derivative equalities

The design of neuro-fuzzy models is still a complex problem, as it involves not only the determination of the model parameters, but also its structure. Of special importance is the incorporation of a priori information in the design process. In this paper two known design algorithms for B-spline models will be updated to account for function and derivatives equality restrictions, which are important when the neural model is used for performing single or multi-objective optimization on-line.

B-splines neural network assisted PID autotuning

This papers describes an extantion of previous works on the subject of neural network proportional, integral and derivative (PID) autotuning. Basically, neural networks are employed to supply the three PID parameters, according to the integral of time multiplied by the absolute error (ITAE) criterion, to a standard PID controller.

Salamandra salamandra (Amphibia: Caudata: Salamandridae) in Portugal: not all black and yellow

The fire salamander complex is quite diverse in the Iberian Peninsula where nine subspecies of Salamandra salamandra are currently recognized. Here, we analysed the geographical distribution of the subspecies S. s. gallaica and S. s. crespoi using partial sequences of the mitochondrial cytochrome b gene of 168 individuals from 12 locations in Portugal. Our results support the existence of a deep lineage divergence between the two subspecies, with non-overlapping geographical distributions except in two contact zones: one in Sesimbra on the western coast, and another in Alcoutim on the southeastern border with Spain. Moreover, S. s. crespoi displays signs of gene flow among the sampled locations whereas S. s. gallaica shows evidence of some restriction to gene flow. Present-day genetic make-up of S. s. gallaica and S. s. crespoi is a result of past historical events, fine-tuned by contemporary Iberian geoclimate. Humid mountain areas were found to harbour increased genetic diversity possibly acting as past refugia during drier interglacial periods. To analyse wider geographical patterns and lineage splitting events within S. salamandra we performed a Bayesian dating analysis completing our data set with previously published sequences. The observed divergences were associated to successive biogeographic scenarios, and to other Iberian species showing similar trends.