PREDICTION OF SURFACE AREA OF MATERIAL (MnO2) BY     ARTIFICIAL NEURAL NETWORK

Dinesh Kumar, Poonam Kumari

PREDICTION OF SURFACE AREA OF MATERIAL (MnO2) BY ARTIFICIAL NEURAL NETWORK

Authors

Dinesh Kumar, Poonam Kumari

Keywords:

Artificial neural network , MATLAB, Prediction of Surface Area, MnO2

Abstract

This paper employs Artificial neural network algorithm (ANN) through MATLAB software to predictMnO2 surface area by applying best possible parameter correlations. The researchers gathered theirdata from various recent studies. The first step of data processing together with factor analysis filteredunneeded information from the data set. Surface area prediction was achieved by using Temperature

References

Ulusoy U. A Review of Particle Shape Effects on Material Properties for Various Engineering Applications: From Macro to Nanoscale. Minerals [Internet]. 2023 ;13(1):91. Available from: https://www.mdpi.com/2075-163X/13/1/91

Rai PK. Novel adsorbents in remediation of hazardous environmental pollutants: Progress, selectivity, and sustainability prospects. Cleaner Materials [Internet]. 2022 Mar 1;3:100054. Available from: https://www.sciencedirect.com/science/article/pii/S2772397622000144

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Published

2024-12-20

How to Cite

Dinesh Kumar, Poonam Kumari. (2024). PREDICTION OF SURFACE AREA OF MATERIAL (MnO2) BY ARTIFICIAL NEURAL NETWORK . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 3890–3902. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2646