Transfer learning in optimization: Interpretable self-organizing maps driven similarity indices to identify candidate source functions-Reference-Cited by-同舟云学术

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Transfer learning in optimization: Interpretable self-organizing maps driven similarity indices to identify candidate source functions

Published:2023-11 Issue: Volume:229 Page:120529
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Ravichandran Suja Shree^ORCID,Sekar Kannan,Ramanath Vinay,Ramu Palaniappan^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference83 articles.

1. Modeling, analysis, and optimization under uncertainties: a review;Acar;Structural and Multidisciplinary Optimization,2021

2. Artificial neural network for forecasting car mileage per gallon in the city;Afana;International Journal of Advanced Science and Technology,2018

3. Measuring the performance of image contrast enhancement technique;Asamoah;International Journal of Computer Applications,2018

4. Cars CSV file: CORGIS dataset project;Austin,2015

5. Climate change: Earth surface temperature data;Berkeley,2017

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. IntraSOM: A comprehensive Python library for Self-Organizing Maps with hexagonal toroidal maps training and missing data handling;Software Impacts;2023-09

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