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The traditional neural networks with continuous weights easy to implement in software might often be very burdensome in the embedded hardware systems and therefore more costly. Hardware-friendly neural networks are essential to ensure the functionality and effectiveness of the embedded implementation. To achieve this aim, A GA-based algorithm for training neural networks with discrete weights and...
Aiming at the insufficiencies of BP neural network, this paper established a hybrid neural network based on the combination of GA and BP algorithms. The hybrid algorithm made fully use of GA's global searching to improve the learning ability of neural network with the combination of BP. The model was used in personal credit scoring in commercial banks. Compared with single BP neural network, the training...
By integrating the global searching advantage of Genetic Algorithm (GA) and the local searching ability of BP Artificial Neural Network (BP ANN), this paper proposes a new model of BP ANN based on GA (called GA-BP ANN). Firstly, it applies GA to optimize the initial interconnecting weights and thresholds of BP ANN. Then, it utilizes the BP algorithm to train the neural network more accurately. This...
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