The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the in...

Scope: Topics of interest include, but are not limited to: Neural Networks and Connectionist Models Evolutionary Algorithms Fuzzy Logic Knowledge Management Multi-valued Logic Semantic Networks Rough Sets Intelligent Agents Ontologies Reinforcement Learning Complex Network Computational Intelligence Data integration across multiple social networks Honorary Chairs Yongyi, Guo, Taiyuan University...

This paper introduces the class of min max classifiers. These are binary-valued functions that can be used as pattern classifiers of both real-valued and binary-valued feature vectors. They are also lattice-theoretic generalization of Boolean functions and are also related to feed-forward neural networks and morphological signal operators. We studied supervised learning of these classifiers und...

In this paper, we develop a theory of the integration of fibring neural networks (a generalization of conventional neural networks) into model-theoretic semantics for logic programming. We present some ideas and results about the approximate computation by fibring neural networks of semantic immediate consequence operators TP and TP , where TP denotes a generalization of TP relative to a many-v...

there are three major strategies to form neural network ensembles. the simplest one is the cross validation strategy in which all members are trained with the same training data. bagging and boosting strategies pro-duce perturbed sample from training data. this paper provides an ideal model based on two important factors: activation function and number of neurons in the hidden layer and based u...

premature ventricular contraction (pvc) is one of the common cardiac arrhythmias. the occurrence of pvc is dangerous in people who have recently undergone heart. a pvc beat can easily be diagnosed by a doctor based on the shape of the electrocardiogram signal. but in automatic detection, extracting several important features from each beat is required. in this paper, a method for automatic dete...

There are a number of mathematical approaches to the study of learning and generalization in artiicial neural networks. Here we survey thèprobably approximately correct' (PAC) model of learning and some of its variants. These models provide a probabilistic framework for the discussion of generalization and learning. This survey concentrates on the sample complexity questions in these models; th...

Althoughartificial neural networks have been applied in a variety of real-world scenarios with remarkable success, they have often been criticized for exhibiting a low degree of human comprehensibility. Techniques that compile compact sets of symbolic rules out of artificial neural networks offer a promising perspective to overcome this obvious deficiency of neural network representations. This...

Although artificial neural networks have been applied in a variety of real-world scenarios with remarkable success, they have often been criticized for exhibiting a low degree of human comprehensibility. Techniques that compile compact sets of symbolic rules out of artificial neural networks offer a promising perspective to overcome this obvious deficiency of neural network representations. Thi...

There are a number of mathematical approaches to the study of learning and generalization in arti cial neural networks. Here we survey the `probably approximately correct' (PAC) model of learning and some of its variants. These models provide a probabilistic framework for the discussion of generalization and learning. This survey concentrates on the sample complexity questions in these models; ...