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Fintech Bitcoin Smart Investment Based on the Random Neural Network with a Genetic Algorithm

  • Will Serrano
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 840)

Abstract

This paper presents the Random Neural Network in a Deep Learning Cluster structure with a new learning algorithm based on the genome model, where information is transmitted in the combination of genes rather than the genes themselves. The proposed genetic model transmits information to future generations in the network weights rather than the neurons. The innovative genetic algorithm is implanted in a complex deep learning structure that emulates the human brain: Reinforcement Learning takes fast and local decisions, Deep Learning Clusters provide identity and memory, Deep Learning Management Clusters take final strategic decisions and finally Genetic Learning transmits the learned information to future generations. This structure has been applied and validated in Fintech, a Bitcoin Smart Investment application based in an Intelligent Banker that performs Buy and Sell decisions on several Cryptocurrencies with an associated exchange and risk. Our results are promising; we have connected the human brain and genetics with Machine Learning based on the Random Neural Network model where Artificial Intelligence, similar as biology, is learning gradually and continuously while adapting to the environment.

Keywords

Genetic learning Deep Learning Clusters Reinforcement Learning Random Neural Network Smart Investment Bitcoin Fintech 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Intelligent Systems and Networks GroupElectrical and Electronic Engineering Imperial College LondonLondonUK

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