In recent years, artificial neural networks (ANNs) have been applied to many geotechnical engineering problems and have demonstrated some degree of success. In the majority of these applications, data division is carried out on an arbitrary basis. However, the way the data are divided can have a significant effect on model performance. In this report, the relationship between the statistical pr...

Self-organizing feature maps with self-determined local neighborhood widths are applied to construct principal manifolds of data distributions. This task exempli es the problem of the learning of learning parameters in neural networks. The proposed algorithm is based upon analytical results on phase transitions in self-organizing feature maps available for idealized situations. By illustrative ...

We seek to implement intelligent character recognition of handwritten equations in a manner that allows for a computer program to translate a user’s hand-drawn equation into formatted LTEX. We use a Kohonen neural network fed by downsampled images to accomplish this task. While we were able to achieve single-character recognition with a very low error rate, multiple character recognition and wh...

From 69,130 households that were covered by a comprehensive community-based monitoring survey conducted in one of the cities that comprise Metro-Manila, in the Philippines, a neural network technique is used to identify the “absolute poor”. Households are considered to be among the “absolute poor” when the per capita income is less that 1USD per day, which is based on the UNESCO definition of a...

There are several guidelines for gene nomenclature, but they are not always applied to the names of newly identified genes. The lack of standardization in naming genes generates inconsistent databases with errors such as genes with the same function and different names, genes with different functions and the same name, and use of an abbreviated name. This paper presents a methodology for predic...

In recent modern era of neural networks technology, a model called Spiking Neural Network (SNN) was born. This SNN was classified by Maass [1] as the third generation of neural networks. It is a new kind of neural network which is inspired and motivated by the biological neurons ways of communication. The biological neurons communicate with each other through the media of action potentials, oft...