Neural networks applications in concrete structures

How NBDS learns to learn
(d) Table shows neural network

After a long period of absence, I’m back to announce the 0.2.5 version of the neuron-based data structure called NBDS. This project was introduced in december 2010 as a concept. After that, the development of NBDS still continued, so I wrote about my first implementation of NBDS concept in PHP. This post is about the improvements of  NBDS for PHP. I will write about new features, ideas and some things that can be easily solved with NBDS.

New features

After the last release of version 0.1.3 on github, version 0.2.5 will be the next official release. You can consult a few documents (in the docs folder or on the project page) to understand how NBDS works. Below you can find a list of new features and functionalities that were added to the NBDS:

Lookup handling

The lookup/reverse lookup table was implemented in version 0.1.1 and works pretty well, when its set to ‘on’. After I’ve noticed that, I set this feature obligatory to ‘on’ and removed all on/off switches in the code. This will allow an easier handling and furthermore it improves the speed of NBDS.

Weight of axons

Since version 0.2.2 NBDS implements a new attribute for the Axon object. Inspired by nature where a synapse between neurons has an equivalent weight that points out the importance of a synapse. To make NBDS learnable,  you need an element that learns. With this idea in mind, the following versions of NBDS will be learnable and you can train it with common training algorithms for neural networks.

Source: cip-labs - PHP, MySQL and CMS Systems

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