CRODNM: Chemical Reaction Optimization of Dendritic Neuron Models for Forecasting Net Asset Values of Mutual Funds

Sarat Chandra Nayak, Satchidananda Dehuri, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Learning algorithm and aggregation function used in the neurons have imperative influence on the approximation of an artificial neural network. Dendritic neuron model (DNM) using additive and multiplicative-based aggregation functions has been emerging as a machine learning approach and found successful in many engineering applications. This study attempts to advance the predictive accuracy of DNM through maintaining a decent steadiness between exploration and exploitation of its search space with chemical reaction optimization (CRO) algorithm, termed as CRODNM. The CRO, being a parameter free and powerful global search optimization method synergies with better approximation capability of DNM thus, able to overcome the limitations of conventional back propagation learning based DNM. In addition to this, to start the search operation with a better-quality initial population, we propose a new initial population generation method for CRODNM by incorporating several methods. The proposed CRODNM is evaluated on forecasting net asset values of four mutual funds in terms of convergence and prediction accuracy. The learning paradigm formed due to reasonable combination of CRO and DNM (i.e., CRODNM) found competitive and outperforms over DNM, multilayer perceptron (MLP), and genetic algorithm trained DNM prediction models.

Original languageEnglish
Title of host publicationInnovations in Intelligent Computing and Communication - 1st International Conference, ICIICC 2022, Proceedings
EditorsMrutyunjaya Panda, Satchidananda Dehuri, Manas Ranjan Patra, Prafulla Kumar Behera, George A. Tsihrintzis, Sung-Bae Cho, Carlos A. Coello Coello
PublisherSpringer Science and Business Media Deutschland GmbH
Pages299-312
Number of pages14
ISBN (Print)9783031232329
DOIs
Publication statusPublished - 2022
Event1st International Conference on Innovations in Intelligent Computing and Communication, ICIICC 2021 - Bhubaneswar, India
Duration: 2022 Dec 162022 Dec 17

Publication series

NameCommunications in Computer and Information Science
Volume1737 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference1st International Conference on Innovations in Intelligent Computing and Communication, ICIICC 2021
Country/TerritoryIndia
City Bhubaneswar
Period22/12/1622/12/17

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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