Fuzzy model identification by evolutionary, gradient based and memtic algorithms

One of the crucial problems of fuzzy rule modeling is how to find an optimal or at least a quasi-optimal rule base fro a certain system. In most applications there is no human expert available, or, the result of a human expert's decision is too much subjective and is not reproducible, thus some automatic method to determine the fuzzy rule base must be deployed.

Automatic processing of bidimensional images of ''omic'' expression blobs

In this work, a comprehensive review on automatic analysis of Proteomics and Genomics images is presented. Special emphasis is given to a particularly complex image produced by a technique called Two-Dimensional Gel Electrophoresis (2-DE), with thousands of spots (or blobs). Automatic methods for the detection, segmentation and matching of blob like features are discussed and proposed. In particular, a very robust procedure was achieved for processing 2-DE images, consisting mainly of two steps: a) A very trustworthy new approach for the automatic detection and segmentation of spots, based on the Watershed Transform, without any foreknowledge of spot shape or size, and without user intervention; b) A new method for spot matching, based on image registration, that performs well for either global or local distortions. The results of the proposed methods are compared to state-of-the-art academic and commercial products.

Semi-pelagic longline selectivity for two demersal species from the Azores: the black spot sea bream (Pagellus bogaraveo) and the bluemouth rockfish (Helicolenus dactylopterus dactylopterus)

The selectivity of four hook sizes (STELL brand(1), Quality 2335, numbers 12, 9, 6 and 4) used in a semi-pelagic longline fishery was studied in the Azores. Two species were caught in sufficient numbers for modelling of selectivity: the black spot sea bream (Pagellus bogaraveo) and the bluemouth rockfish (Helicolenus dactylopterus dactylopterus). A maximum likelihood method was used to fit a versatile model which can be used to describe a wide range of selectivity curves; from bell-shaped to asymptotic. Significant differences in size selectivity between hooks were found for both species. In the case of Pagellus bogaraveo, the smallest hook (number 12) had the lowest catch rates and all hooks were characterised by logistic-type selectivity curves, with sizes at 50% selectivity of: 27.9, 30.4, and 32.8 cm for hooks numbers 12, 9 and 6, respectively. The number 9 hook was the most efficient for Helicolenus d. dactylopterus, with selectivity curves varying from strongly skewed to the right for the number 12 hook to logistic-type for the numbers 6 and 4 hooks. Sizes at 50% selectivity for this species were 16.8, 18.7, 20.7, and 22.0 cm. respectively. (C) 1999 Elsevier Science B.V. All rights reserved.