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A hybrid heuristic-driven technique to study the dynamics of savanna ecosystem

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Abstract

Savanna fire has many types: Savanna woody, Savanna vegetation, and grassland. In this paper, Savanna vegetation is studied, characterized by low trees and high grass. It grows in hot and seasonally dry conditions. The Savanna vegetation is described by relating to the environment and climate. Savanna vegetation is considered a metastable mixture of trees and grass and is advanced to explain stability. The Savanna vegetation is modeled with first-order linear differential equations having grass, trees, and sapling (young trees) as components. Furthermore, the model is evaluated numerically by integrating the global search technique Sine-Cosine algorithm and local search technique Interior point algorithm. Comprehensive numerical experiments are conducted to analyze numerical results. To validate solution of proposed technique, Runge-Kutta order four method isolution is taken as a reference solution. The solutions are compared graphically with the results of the reference technique. Performance indicators Mean Absolute Deviation, Root Mean Squared Error, and Error in Nash-Sutcliffe Efficiency are implemented to verify consistency, and multiple independent runs are drawn. Furthermore, the scheme is evaluated through convergence graphs as well.

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Abbreviations

SCA:

Sine cosine algorithm

IPA:

Interior point algorithm

RK4:

Runge-Kutta methods order four

ANN:

Artificial neural network

SES:

Savanna ecosystem

MAD:

Mean absolute deviation

RMSE:

Root mean squared error

ENSE:

Error in nash-sutcliffe efficiency

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Authors and Affiliations

  1. Department of Mathematics, Abdul Wali Khan University, Mardan, 23200, Pakistan

    Muhammad Fawad Khan & Muhammad Sulaiman

  2. Department of Mathematics, College of Science and Humanities in Alkharj, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia

    Fahad Sameer Alshammari

Authors
  1. Muhammad Fawad Khan
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  2. Muhammad Sulaiman
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  3. Fahad Sameer Alshammari
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Correspondence to Muhammad Sulaiman or Fahad Sameer Alshammari.

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Khan, M.F., Sulaiman, M. & Alshammari, F.S. A hybrid heuristic-driven technique to study the dynamics of savanna ecosystem. Stoch Environ Res Risk Assess 37, 1–25 (2023). https://doi.org/10.1007/s00477-022-02270-7

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