Separation of Fire Images with Biogeography-Based Optimization

Toptaş, Buket; Hanbay, Davut; Yeroğlu, Celaleddin

doi:10.1109/idap.2018.8620753

Cited by 1 publication

(1 citation statement)

References 8 publications

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“…Since forest fires are complex and nonlinear dynamic systems, it is necessary to resort to the use of algorithms for their modeling. Among the most widely used tools for the development of susceptibility maps, coverage models, analysis of large volumes of data, and localization of forest fires, several metaheuristics have been identified, including hybrid evolutionary algorithms for evaluating and mapping wildfire susceptibility [8]; biogeography-based optimization (BBO) for fire detection using a system based on the distribution of fire/flame color pixels [11]; a multi-objective programming model for wildfire suppression that considers rescue priority, utilizing the gravitational search algorithm (GSA) [12]; and ant colony optimization (ACO) for predicting temperature distribution in tunnel fires [13] concerning fire duration [14]. ACO is also employed for evacuation route planning [15], and genetic algorithm (GA) is used for data-driven wildfire spread prediction [4,16].…”

Section: Introductionmentioning

confidence: 99%

Water Reservoir Placement Methodology for Forest Firefighting: A Case Study of Valparaíso, Chile

Alfaro,

Santander,

Fuertes

et al. 2024

Forests

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Climate change has a significant impact on generating forest fires. These fires damage property, interrupt productive processes, reduce employment sources, and generate direct economic losses. Also, fires contribute to climate change, resulting in a negative cycle. Therefore, the effective management of forest fires is of vital importance. This research focuses on the combat and mitigation phase of forest fires, with special emphasis on using helicopters to transport water from nearby reservoirs to the fire site. The location of these reservoirs is key since a greater distance traveled by helicopter means a longer delay in water transport, which favors the spread of the fire. For this reason, this research proposes an optimization model to determine the optimal location of these reservoirs in a territory. The proposed model is illustrated with a case study of the region of Valparaiso, demonstrating its usefulness for management and decision making when locating reservoirs for firefighting.

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