Modelling and Trading the DJIA Financial Index Using Neural Networks Optimized with Adaptive Evolutionary Algorithms

2012 ◽  
pp. 453-462 ◽  
Author(s):  
Konstantinos Theofilatos ◽  
Andreas Karathanasopoulos ◽  
Georgios Sermpinis ◽  
Thomas Amorgianiotis ◽  
Efstratios Georgopoulos ◽  
...  
Keyword(s):  
Neural Networks ◽  
Evolutionary Algorithms ◽  
Financial Index ◽  
Adaptive Evolutionary Algorithms

Using Particle Swarm Optimization Algorithm as an Optimization Tool Within Developed Neural Networks

2018 ◽  
pp. 215-244
Author(s):  
Goran Klepac
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Particle Swarm Optimization ◽  
Evolutionary Algorithms ◽  
Optimization Algorithm ◽  
Recommendation System ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Optimal Combination ◽  
Swarm Optimization

Developed neural networks as an output could have numerous potential outputs caused by numerous combinations of input values. When we are in position to find optimal combination of input values for achieving specific output value within neural network model it is not a trivial task. This request comes from profiling purposes if, for example, neural network gives information of specific profile regarding input or recommendation system realized by neural networks, etc. Utilizing evolutionary algorithms like particle swarm optimization algorithm, which will be illustrated in this chapter, can solve these problems.

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