Titlebook: Computational Intelligence Based on Lattice Theory; Vassilis G. Kaburlasos,Gerhard X. Ritter Book 2007 Springer-Verlag Berlin Heidelberg 2

痛恨

Density

Bumble

Convex Coordinates From Lattice Independent Sets for Visual Pattern Recognitioncs and data mining. The purpose of this chapter is to introduce a new feature extraction process based on the detection of extremal points on the cloud of points that represent the high dimensional data sample. These extremal points are assumed to de.ne an approximation to the convex hull covering t

NIP

A Lattice-Based Approach to Mathematical Morphology for Greyscale and Colour Imageslation. MM has many applications in image analysis such as edge detection, noise removal, object recognition, pattern recognition and image segmentation in a.o. geosciences, materials science, the biological and medical world [13, 15]. MM was originally developed for binary images only. The basic to

Angiogenesis

Morphological and Certain Fuzzy Morphological Associative Memories for Classification and Predictionight into the storage and recall phases of gray-scale autoassociative memories. This article extends these results to the heteroassociative and to the fuzzy case in view of the fact that a gray-scale MAM model can be converted into a fuzzy MAM model that coincides with the Lukasiewicz IFAM by applyi

Insulin

2否定

Machine Learning Techniques for Environmental Data Estimationthe historical data containing wind parameter values at two other di.erent locations. We evaluate the performance of two signi.cant machine learning methodologies, the Fuzzy Lattice Neurocomputing (FLN) and the Support Vector Regression (SVR). The results of the speci.c applications are compared wit

Cupping

Application of Fuzzy Lattice Neurocomputing (FLN) in Ocean Satellite Images for Pattern Recognitionizes the most important . in satellite AVHRR (Advanced Very High Resolution Radiometer) images. This chapter presents a hybrid model based on an expert system segmentation method, a method of correlation-based feature selection, and a few classi.ers including Bayesian nets (BN) and fuzzy lattice neu

guzzle

冷峻

Fuzzy Lattice Reasoning (FLR) Classification Using Similarity Measuresilarity and distance measures often used in cluster analysis. We show that for the cosine similarity measures, we can weigh the contribution of each attribute found in the data set. Furthermore, we show that evolutionary algorithms such as genetic algorithms, tabu search, particle swarm optimization