Parameter estimation of photovoltaic models based on improvement of moutain gazelle optimizer algorithm

Introduction The mountain gazelle (Gazella gazella) is a native species to the Middle East and has experienced a notable population decline due to human-induced habitat loss and fragmentation. In Saudi Arabia, the current status and distribution of this species remain poorly understood, necessitating data-driven conservation assessments. Methods, Results, and Discussion This study combined recent occurrence records with remote sensing and GIS-based environmental variables to model suitable habitats for the mountain gazelle using the MaxEnt algorithm. Key predictors included vegetation indices, land cover types, and elevation. The results identified core habitat areas in the western and southwestern regions, some of which fall outside current protected zones. These findings underscore the importance of expanding conservation areas and demonstrate how spatial modeling supports effective wildlife management in arid environments.

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Publication Details

Journal
Frontiers in Energy Research
Published
2025-08-29
DOI
https://doi.org/10.3389/fenrg.2025.1464011
Primary Topic
Oil Palm Production and Sustainability
Type
article
Field-Weighted Citation Impact
0.00

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article

Parameter estimation of photovoltaic models based on improvement of moutain gazelle optimizer algorithm

Diaa Salama AbdElminaam, Arar Al Tawil, Walaa H. Elashmawi, Ibrahim Shawky Farahat et al.
Frontiers in Energy Research
Oil Palm Production and Sustainability
article

Parameter estimation of photovoltaic models based on improvement of moutain gazelle optimizer algorithm

Diaa Salama AbdElminaam, Arar Al Tawil, Walaa H. Elashmawi, Ibrahim Shawky Farahat, Ala Saleh Alluhaidan, Sandy Adel Nabih, Sahar A. El-Rahman
article en

Abstract

Introduction The mountain gazelle (Gazella gazella) is a native species to the Middle East and has experienced a notable population decline due to human-induced habitat loss and fragmentation. In Saudi Arabia, the current status and distribution of this species remain poorly understood, necessitating data-driven conservation assessments. Methods, Results, and Discussion This study combined recent occurrence records with remote sensing and GIS-based environmental variables to model suitable habitats for the mountain gazelle using the MaxEnt algorithm. Key predictors included vegetation indices, land cover types, and elevation. The results identified core habitat areas in the western and southwestern regions, some of which fall outside current protected zones. These findings underscore the importance of expanding conservation areas and demonstrate how spatial modeling supports effective wildlife management in arid environments.

Frontiers in Energy ResearchVol. 13
Princess Nourah bint Abdulrahman University (SA), Suez Canal University (EG), Applied Science Private University (JO), Benha University (EG), Jadara University (JO), Misr International University (EG)
Princess Nourah Bint Abdulrahman University, Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University
Openalex Percentile: Top 78%
Oil Palm Production and Sustainability
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Parameter estimation of photovoltaic models based on improvement of moutain gazelle optimizer algorithm — Diaa Salama AbdElminaam, Arar Al Tawil, et al. · Frontiers in Energy Research (2025) | TGRS Research Map | TGRS