Adaptive learning rate BP neural network algorithm

Abstract

The invention discloses an adaptive learning rate BP neural network algorithm. The back propagation process of the BP neural network algorithm is optimized, and different learning rates are dynamically adapted to the connection weight of different neurons so that optimization of each direction is ensured to search the optimal solution of the direction, the adjustment efficiency of the weight can be enhanced to the greatest extent to accelerate the convergence speed of the whole training. The algorithm comprises the step one: network initialization; step two: sample inputting; step three: forward propagation; step four: result judgment; and step five: back propagation. The algorithm is simple in program and easy to implement and great in improvement effect so that the training time of the BP neural network can be greatly shortened, the problem of being prone to the local minimum of the present algorithm can be effectively overcome, the universality is high and thus the algorithm has great practical application value.

Description

technical field [0001] The invention belongs to the technical field of artificial intelligence, in particular to a BP neural network algorithm with an adaptive learning rate. Background technique [0002] Artificial neural network is one of the research hotspots in the direction of artificial intelligence in modern science. It analyzes the network structure of the human brain nervous system and the system mechanism of human brain nerve work to establish a mathematical network model that imitates the work of the human brain, has real-time processing and storage functions. BP neural network is the most commonly used algorithm in artificial intelligence network, and it is one of the most mature network structures currently researched. Because of its super self-learning, self-organization, self-adaptation, associative memory and fault tolerance, its application is very extensive. It covers almost every aspect of life, including information processing, automatic control, economy...

AI Technical Summary

Problems solved by technology

[0004] The technical problem solved by the present invention is to provide a BP neural network algorithm of adaptive learning rate, to solve the problem that the existing BP algorithm training time is long and easy to fall into local minimum; meanwhile, the BP neural network algorithm of adaptive learning rate of the present invention The neural network algorithm can ensure that the complexity of the algorithm is low, and the realization conditions are easy

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