Francisco Yepes BarreraI-CON Srl · Software Development
Francisco Yepes Barrera
Dr.
About
4
Publications
576
Reads
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5
Citations
Citations since 2017
Introduction
Owner of I-CON Srl, an Italian company that works in the IT sector.
My interests focus on some areas of artificial intelligence, mainly neural networks and genetic algorithms. In the past I worked on hybrid neuroevolutionary systems and their application to industrial problems.
I am currently working on a neural network optimization model called "Eigen Artificial Neural Networks" which, starting from an analogy with physical quantum-mechanical systems, uses wave mechanics techniques in their study.
Additional affiliations
July 2016 - March 2020
I-CON Srl
Position
- Developer
Education
September 1989 - June 1994
Publications
Publications (4)
The paper describes the use of Genetic Algorithms (GA) and Simulated Annealing (SA) for the configuration of neural networks, within the framework of a specific architecture, TSAGANN. The comparison has been carried out on established benchmarks, and described in detail. Statistical analysis of results indicates that SA seems not to be penalized wi...
Este artículo describe el uso de algoritmos genéticos (AG) y simulated annealing (SA) en la búsqueda de configuraciones óptimas de redes neurales artificiales, dentro de una arquitectura software, TSAGANN. El estudio comparativo ha sido realizado con benchmarks consolidados y es ilustrado en detalle. El análisis estadístico de los resultados indica...
Abstract This work has its origin in intuitive physical and statistical considerations. The problem of optimizing an artificial neural network is treated as a physical system, composed of a conservative vector force field. The derived scalar potential is a measure of the potential energy of the network, a function of the distance between prediction...
Questions
Question (1)
I'm looking for someone who can do an endorsement of my work on arXiv. Can anyone help me?
Thanks
Projects
Project (1)
Application of wave mechanics techniques to the problem of optimizing artificial neural networks
