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.

Identification of descendants of an extinct bovine population from the Algarve region of Portugal using numerical taxonomy analysis of morphological traits

The morphology of a sample of four bulls and 43 cows, presumed to be descendants of the extinct cattle breed ‘Algarvia’ (AG), was used to assign their relationship with animals from other Portuguese autochthonous breeds – Arouquesa (AR), Barrosa˜ (BA), Cachena (CA), Marinhoa (MA), Maronesa (MO), Minhota (MN), Mirandesa (MI), (only bulls), Alentejana (AL), Garvonesa (GA), Mertolenga (ME) and Preta (PR). Standard numerical taxonomic methods were applied to a set of 183 (cows) and 170 (bulls) traits, to derive average pairwise taxonomic distances among the sample of 257 cows and 76 bulls. Distance coefficients (morphological index of distance) ranged from 0.22 to 2.62 (cows) and from 0.49 to 2.13 (bulls). Unweighted pair group method using arithmetic averages (UPGMA)-based phenograms and a principal coordinate analysis showed that bulls were highly clustered and cows showed a tendency to cluster according to their geographical and breed origin. The AG population grouped together with GA, AL, ME and MN breeds in the Red Convex group. The average taxonomic distance among breeds was 1.02, the highest being 1.39 (ME versus BA) and the lowest being 0.64 (MA versus AR). The approach allowed for the identification of a phenotypically differentiated set of animals, comprising 19 cows and four bulls representative of the AG breed, and which can be targeted in further studies aiming at the recovery of this extinct breed.