C++ Neural Networks and Fuzzy Logic: Preface

objective function.

Deeming the objective function as giving the energy of a network in a given state, the simulated annealing

paradigm and the Hopfield network can be used to solve the problem. You then have a neural network in

which each neuron represents a stock, and the size of the layer is determined by the number of stocks in the

pool from which you want to build your stock portfolio. The paradigm suggested here strives to minimize the

energy of the machine. The objective function needs therefore to be stated for minimization to get the best

portfolio possible.

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C++ Neural Networks and Fuzzy Logic:Preface

Optimizing a Stock Portfolio

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