Introduction to Artificial Neural Networks 901 2 Neural Network Architectures 902 3 Neural Network Learning 903 4 Backpropagation Learning 903 5 Training and Testing Neural Networks 904 6 Higher Order Learning Algorithms 905 7 Designing Artificial Neural Networks 905 8 Self-organizing Feature Map

of the sparselypopulated 1970's in favor of influential papers from the crowded 1980's. The editors of Artificial Intelligence deserve everyone's applause for their inspiration and effort in soliciting retrospectives from authors of highly-cited AIJ papers from the first 50 volumes, recently published

The diffusing capacity of the lung, DL, is a critical physiological parameter, yet the currently accepted clinical model (Jones–Meade) assumes a well-mixed alveolar region, and a constant DL independent of alveolar volume, VA, despite experimental evidence to the contrary. We have formulated a new

With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equal basis is a challenging task. Here we propose a general method for integrating heterogeneous data sets based

Abstract: RUBRYX is a document classifier developed in 2000s for processing large volumes of Web information. RUBRYX uses weighted sum of n-grams (n=1,2,3) extracted from a very limited number of samples (about 5-10) and takes into account their mutual position in a given text. This sophisticated

as the links and relations between them. The system creates a set of blocks (modules) for which the concurrent work is pre-established. The volume of knowledge can be also increased without increasing the number of blocks. For Artificial Intelligence systems the ratio between the user’s and the system’s work

Informatics and Computer Science. It is aimed to support growing collaboration between scientists from all over

V) of the solutions measured after the addition of different volumes of the titrant. The optimized network predicted the concentrations of agents in synthetic mixtures. The results showed that the employed ANN can precede the titration data with an average relative error of prediction of less than 2.30 %.

important role in the stock market environment. Therefore, this research proposes illl intelligent stock market forecasting system which considers the quantitative factors as well as the qualitative factors. Basically, the proposed system consists of (1) factors collection, (2) quantitative model ( i s

measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets- artificial (W TTest), hand