Phasmatodea population evolution algorithm and its application in length-changeable incremental extreme learning machine

Pei Cheng Song, Shu Chuan Chu, Jeng Shyang Pan, Hongmei Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Extreme learning machine (ELM) is an effective classification and prediction learning algorithm based on feedforward neural network (FNN). This paper presents the Phasmatodea (stick insect) population evolution algorithm (PPE), which is different from other algorithms, in which each solution represents a population and has two attributes: quantity and growth rate. Combining the concept of similar evolution and the model of population competition, it is a new local search method. The algorithm is compared with the other algorithms on benchmark functions and engineering problems. Then use it to enhance a variant of the ELM model. The results show that the proposed algorithm has a certain competitiveness.

Original languageEnglish
Title of host publication2nd International Conference on Industrial Artificial Intelligence, IAI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781728182162
DOIs
Publication statusPublished - 23 Oct 2020
Externally publishedYes
Event2nd International Conference on Industrial Artificial Intelligence, IAI 2020 - Shenyang, China
Duration: 23 Oct 202025 Oct 2020

Publication series

Name2nd International Conference on Industrial Artificial Intelligence, IAI 2020

Conference

Conference2nd International Conference on Industrial Artificial Intelligence, IAI 2020
Country/TerritoryChina
CityShenyang
Period23/10/2025/10/20

Keywords

  • Statistics
  • Sociology
  • prediction algorithims
  • insects
  • Benchmark testing
  • Classification algorithms

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