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A New Cascade-Correlation Growing Deep Learning Neural Network Algorithm

Research Authors
Soha Abd El-Moamen Mohamed, Marghany Hassan Mohamed, Mohammed F Farghally
Research Date
Research Department
Research Journal
Research Publisher
Multidisciplinary Digital Publishing Institute
Research Year
Research Abstract

In this paper, a proposed algorithm that dynamically changes the neural network structure is presented. The structure is changed based on some features in the cascade correlation algorithm. Cascade correlation is an important algorithm that is used to solve the actual problem by artificial neural networks as a new architecture and supervised learning algorithm. This process optimizes the architectures of the network which intends to accelerate the learning process and produce better performance in generalization. Many researchers have to date proposed several growing algorithms to optimize the feedforward neural network architectures. The proposed algorithm has been tested on various medical data sets. The results prove that the proposed algorithm is a better method to evaluate the accuracy and flexibility resulting from it. View Full-Text