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Method and system for optimizing extreme learning machine integrated learning based on lion group algorithm

An extreme learning machine and integrated learning technology, applied in the field of artificial intelligence, can solve problems such as poor integration effect

Inactive Publication Date: 2019-08-20
HUBEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] In view of this, the present invention provides a method and system for optimizing the integrated learning of extreme learning machines based on the Lion Pride algorithm, to solve or at least partially solve the technical problem of poor integration effect existing in the methods in the prior art

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  • Method and system for optimizing extreme learning machine integrated learning based on lion group algorithm
  • Method and system for optimizing extreme learning machine integrated learning based on lion group algorithm
  • Method and system for optimizing extreme learning machine integrated learning based on lion group algorithm

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Embodiment 1

[0072] This embodiment provides a method for optimizing the integrated learning of extreme learning machines based on the Lion Pride Algorithm, please refer to figure 1 , the method includes:

[0073] Step S1: Encode the input weights and hidden layer node thresholds randomly generated by the extreme learning machine into individuals of the Lion Pride algorithm to form an initial population.

[0074] Specifically, the extreme learning machine, as an improved algorithm of the feed-forward neural network, can predict the unified problem through the regular message passing between the 3-layer neuron system.

[0075] As a novel swarm intelligence optimization algorithm, the lion group optimization algorithm is gradually accepted for its good global convergence, fast convergence speed, high precision, and the ability to better obtain the global optimal solution. In the lion group algorithm, lions are divided into three parts according to a certain ratio: lion king, lioness and cub...

Embodiment 2

[0111] This embodiment provides a system for optimizing the integrated learning of extreme learning machines based on the Lion Pride algorithm, including:

[0112] The encoding module 201 is used to encode the input weights randomly generated by the extreme learning machine and the hidden layer node thresholds into lion-pride algorithm individuals to form an initial population;

[0113] The initial position calculation module 202 is used to use the formed initial population as a training set, and extract a preset proportion of training samples from the training set as a verification test set, and calculate the fitness of each individual and various types of lions based on the verification test set. The number of , set the position with the best fitness as the lion king position;

[0114] The position update module 203 is used to update the positions of the lion king, lioness and cub according to the position update function of each individual respectively, wherein the individu...

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Abstract

The invention discloses a method and a system for optimizing extreme learning machine integrated learning based on a lion group algorithm. The improved lion group algorithm is applied to integrated learning of an extreme learning machine; the characteristics of high precision, fast convergence and fast extreme learning training speed of the lion group algorithm are fully utilized; a global optimalsolution is searched by using a lion group algorithm to follow a currently searched optimal value so as to reduce the number of iterations and optimize an extreme learning machine individual; a corresponding selection mechanism is formulated according to relevant theories of the extreme learning machine, the extreme learning machine with a small output weight and a small training error is selected to be used for integrating the network, the network stability and the generalization capability are remarkably improved within acceptable training time, and the method is a new method with practicalapplication value.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a method and system for optimizing integrated learning of extreme learning machines based on the Lion Pride algorithm. Background technique [0002] Extreme Learning Machine (ELM) is a kind of machine learning algorithm based on feedforward neural network (feedforward neuron network). Its main feature is that the hidden layer node parameters can be randomly or artificially given and do not need to be adjusted. The learning process only needs to calculate the output weights. ELM has the advantages of high learning efficiency and strong generalization ability, and is widely used in classification, regression, clustering, feature learning and other problems. However, since some parameters are randomly generated, it is inevitable that some poorer parameters will be randomized, which will affect the stability and generalization ability of the entire extreme learning, ...

Claims

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Application Information

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IPC IPC(8): G06N20/00G06N3/00
CPCG06N3/006G06N20/00
Inventor 刘伟胡明威叶志伟王春枝黄千汤远志
Owner HUBEI UNIV OF TECH
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