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Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident
The disposable income of residents can reflect the living standard of people in the area. For government departments, it is necessary to master the trend of rural resident income to formulate corresponding policies benefiting farmers. Thus, this paper proposes a grey model with an improved jellyfish...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208948/ https://www.ncbi.nlm.nih.gov/pubmed/35733558 http://dx.doi.org/10.1155/2022/3343505 |
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author | Lei, Yang Fan, Lingyun Yang, Juntao Si, Wenhu |
author_facet | Lei, Yang Fan, Lingyun Yang, Juntao Si, Wenhu |
author_sort | Lei, Yang |
collection | PubMed |
description | The disposable income of residents can reflect the living standard of people in the area. For government departments, it is necessary to master the trend of rural resident income to formulate corresponding policies benefiting farmers. Thus, this paper proposes a grey model with an improved jellyfish search optimizer to predict the rural resident income in Shaanxi Province. Firstly, by applying fractional-order modified strategy and Gaussian mutation mechanism to the original algorithm, the proposed algorithm shows better performance in solving accuracy, stability, and convergence acceleration when compared with different classical methods on cec2017 and cec2019 test functions. Then, based on the fractional time-delayed grey model, a discrete fractional time-delayed grey model with triangular residual correction (TDFTDGM) is proposed by replacing the derivative with a first-order difference and introducing the triangular residual correction functions. Finally, the improved jellyfish search optimizer is used to explore the optimal order of the TDFTDGM model. The all-around performance of the forecast model is incomparable to additional grey models compared on four measure criteria, which means it is a practical approach for long-term prediction with small samples. Moreover, the forecast data of rural resident income in Shaanxi Province from 2021 to 2025 are given for reference. |
format | Online Article Text |
id | pubmed-9208948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-92089482022-06-21 Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident Lei, Yang Fan, Lingyun Yang, Juntao Si, Wenhu Comput Intell Neurosci Research Article The disposable income of residents can reflect the living standard of people in the area. For government departments, it is necessary to master the trend of rural resident income to formulate corresponding policies benefiting farmers. Thus, this paper proposes a grey model with an improved jellyfish search optimizer to predict the rural resident income in Shaanxi Province. Firstly, by applying fractional-order modified strategy and Gaussian mutation mechanism to the original algorithm, the proposed algorithm shows better performance in solving accuracy, stability, and convergence acceleration when compared with different classical methods on cec2017 and cec2019 test functions. Then, based on the fractional time-delayed grey model, a discrete fractional time-delayed grey model with triangular residual correction (TDFTDGM) is proposed by replacing the derivative with a first-order difference and introducing the triangular residual correction functions. Finally, the improved jellyfish search optimizer is used to explore the optimal order of the TDFTDGM model. The all-around performance of the forecast model is incomparable to additional grey models compared on four measure criteria, which means it is a practical approach for long-term prediction with small samples. Moreover, the forecast data of rural resident income in Shaanxi Province from 2021 to 2025 are given for reference. Hindawi 2022-06-13 /pmc/articles/PMC9208948/ /pubmed/35733558 http://dx.doi.org/10.1155/2022/3343505 Text en Copyright © 2022 Yang Lei et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lei, Yang Fan, Lingyun Yang, Juntao Si, Wenhu Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident |
title | Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident |
title_full | Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident |
title_fullStr | Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident |
title_full_unstemmed | Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident |
title_short | Fractional-Order Boosted Jellyfish Search Optimizer with Gaussian Mutation for Income Forecast of Rural Resident |
title_sort | fractional-order boosted jellyfish search optimizer with gaussian mutation for income forecast of rural resident |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9208948/ https://www.ncbi.nlm.nih.gov/pubmed/35733558 http://dx.doi.org/10.1155/2022/3343505 |
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