Neural network and decision tree-based machine learning tools to analyse the anion-responsive behaviours of emissive Ru(<scp>ii</scp>)–terpyridine complexes-Reference-Cited by-同舟云学术

Neural network and decision tree-based machine learning tools to analyse the anion-responsive behaviours of emissive Ru(ii)–terpyridine complexes

Published:2023 Issue:1 Volume:52 Page:97-108
ISSN:1477-9226
Container-title:Dalton Transactions
language:en
Short-container-title:Dalton Trans.

Author:

Sahoo Anik¹,Bhattacharya Sohini¹,Jana Subhamoy²,Baitalik Sujoy¹^ORCID

Affiliation:

1. Department of Chemistry, Inorganic Chemistry Section, Jadavpur University, Kolkata 700032, India

2. School of Biological Sciences, Indian Association for the Cultivation of Science, Kolkata 700 032, India

Abstract

Artificial neural network, adaptive neuro-fuzzy inference and decision tree regression are implemented to analyse the anion-responsive behaviours of emissive Ru(ii)–terpyridine complexes.

Funder

Science and Engineering Research Board

Council of Scientific and Industrial Research

Publisher

Royal Society of Chemistry (RSC)

Subject

Inorganic Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/DT/D2DT03289A

Reference47 articles.

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