Fintech Model: The Random Neural Network with Genetic Algorithm
By Will Serrano. 2018
15 citations recorded by the source corpus.
Abstract This paper proposes the Random Neural Network with a new learning algorithm based on the genome model. Following genetics, 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 local current decisions, Deep Learning Clusters provide identity and memory, Deep Learning Management Clusters take final strategic decisions and finally Genetic Learning transmits the information learned to future generations. The presented algorithm and Deep Learning structure has been applied and validated in a Fintech Model; a Smart Investment application where an Intelligent Bankers are specialised in Buy and Sell decisions on several Assets, Markets and Risks. The obtained results are promising; the proposed model combines human brain and genetics with Deep Learning structure based on the Random Neural Network model where biology; similar as Artificial Intelligence is learning gradually and continuously while adapting to the environment.
Subfields: Economics and Econometrics, Electrical and Electronic Engineering, Management Science and Operations Research
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Citations in the corpus
- Deep Learning for Financial Applications : A Survey (2020, methodology): “[63] 8 experimental assets from bond/derivative market Asset prices data RL, DNN, Genetic Algorithm Learning and genetic algorithm error -”