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A Review of Genetic Algorithm Approaches for Wildfire Spread Prediction Calibration

https://doi.org/10.3390/math10030300
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Time aware genetic algorithm for forest fire propagation prediction: exploiting multi‐core platforms
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S 2 F 2 M – Statistical System for Forest Fire Management
inferredcites →https://doi.org/10.1007/978-3-030-50433-5_2openalex-snapshot
Early Adaptive Evaluation Scheme for Data-Driven Calibration in Forest Fire Spread Prediction
inferredcites →https://doi.org/10.1007/978-3-540-69389-5_6openalex-snapshot
Applying a Dynamic Data Driven Genetic Algorithm to Improve Forest Fire Spread Prediction
inferredcites →https://doi.org/10.1007/978-3-642-01973-9_54openalex-snapshot
Computational Steering Strategy to Calibrate Input Variables in a Dynamic Data Driven Genetic Algorithm for Forest Fire Spread Prediction
inferredcites →https://doi.org/10.1007/978-3-642-01973-9_55openalex-snapshot
Injecting Dynamic Real-Time Data into a DDDAS for Forest Fire Behavior Prediction
inferredcites →https://doi.org/10.1007/s11069-014-1397-8openalex-snapshot
Adaptation of the Canadian Fire Weather Index to Mediterranean forests
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Genetic fuzzy system for data-driven soft sensors design
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Adaptive fuzzy identification and predictive control for industrial processes
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Automatic forest fire danger rating calibration: Exploring clustering techniques for regionally customizable fire danger classification
inferredcites →https://doi.org/10.1016/j.foreco.2012.09.041openalex-snapshot
Prescribed burning and browsing to control tree encroachment in southern European heathlands
inferredcites →https://doi.org/10.1016/j.future.2004.09.013openalex-snapshot
Enhancing wildland fire prediction on cluster systems applying evolutionary optimization techniques
inferredcites →https://doi.org/10.1016/j.jocs.2012.06.002openalex-snapshot
Dynamic Data-Driven Genetic Algorithm for forest fire spread prediction
inferredcites →https://doi.org/10.1016/j.procs.2012.04.033openalex-snapshot
Genetic Algorithm Characterization for the Quality Assessment of Forest Fire Spread Prediction
inferredcites →https://doi.org/10.1016/j.procs.2012.04.120openalex-snapshot
Coupling Wind Dynamics into a DDDAS Forest Fire Propagation Prediction System
inferredcites →https://doi.org/10.1016/j.procs.2012.04.183openalex-snapshot
On the Way of Applying Urgent Computing Solutions to Forest Fire Propagation Prediction
inferredcites →https://doi.org/10.1016/j.procs.2013.05.399openalex-snapshot
Relieving the Effects of Uncertainty in Forest Fire Spread Prediction by Hybrid MPI-OpenMP Parallel Strategies
inferredcites →https://doi.org/10.1016/j.procs.2015.05.294openalex-snapshot
Forest Fire Propagation Prediction Based on Overlapping DDDAS Forecasts
inferredcites →https://doi.org/10.1016/j.procs.2015.05.380openalex-snapshot
Relieving Uncertainty in Forest Fire Spread Prediction by Exploiting Multicore Architectures
inferredcites →https://doi.org/10.1016/j.procs.2016.05.330openalex-snapshot
Large Forest Fire Spread Prediction: Data and Computational Science
inferredcites →https://doi.org/10.1016/s0360-1285(03)00017-0openalex-snapshot
Mathematical models and calculation systems for the study of wildland fire behaviour
inferredcites →https://doi.org/10.1016/s0378-1127(00)00363-7openalex-snapshot
Fire spread prediction in shrub fuels in Portugal
inferredcites →https://doi.org/10.1016/s1364-8152(01)00072-xopenalex-snapshot
FireStation — an integrated software system for the numerical simulation of fire spread on complex topography
inferredcites →https://doi.org/10.1071/wf06142openalex-snapshot
Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models
inferredcites →https://doi.org/10.1071/wf13084openalex-snapshot
Equilibrium moisture content and timelag of dead Pinus pinaster needles
inferredcites →https://doi.org/10.1071/wf21016openalex-snapshot
On the non-monotonic behaviour of fire spread
inferredcites →https://doi.org/10.1109/aike48582.2020.00011openalex-snapshot
Automatic Calibration of Forest Fire Weather Index For Independent Customizable Regions Based on Historical Records
inferredcites →https://doi.org/10.1109/etfa.2011.6059063openalex-snapshot
Automatic extraction of the fuzzy control system for industrial processes
inferredcites →https://doi.org/10.1109/iecon.2014.7048490openalex-snapshot
Evolutionary learning of a fuzzy controller for industrial processes
inferredcites →https://doi.org/10.1139/er-2020-0019openalex-snapshot
A review of machine learning applications in wildfire science and management
inferredcites →https://doi.org/10.1139/x07-094openalex-snapshot
Reformulation of Rothermel’s wildland fire behaviour model for heterogeneous fuelbedsThis article is one of a selection of papers published in the Special Forum on the Fuel Characteristic Classification System.
inferredcites →https://doi.org/10.1139/x77-045openalex-snapshot
Behavior of experimental grass fires vs. predictions based on Rothermel's fire model
inferredcites →https://doi.org/10.13140/2.1.2045.7766openalex-snapshot
New approaches in fire simulations analysis with Wildfire Analyst
inferredcites →https://doi.org/10.14195/978-989-26-0583-8openalex-snapshot
Manual de computação evolutiva e metaheurística
inferredcites →https://doi.org/10.14195/978-989-26-0884-6_10openalex-snapshot
Calibrating Rothermel’s fuel models by genetic algorithms
inferredcites →https://doi.org/10.2307/2403338openalex-snapshot
Fire Behaviour in South African Fynbos (Macchia) Vegetation and Predictions from Rothermel's Fire Model
inferredcites →https://doi.org/10.2737/int-gtr-122openalex-snapshot
Aids to determining fuel models for estimating fire behavior
inferredcites →https://doi.org/10.2737/int-rp-115openalex-snapshot
A mathematical model for predicting fire spread in wildland fuels
inferredcites →https://doi.org/10.2737/rmrs-gtr-371openalex-snapshot
The Rothermel surface fire spread model and associated developments: A comprehensive explanation
inferredcites →https://doi.org/10.2737/rmrs-rp-4openalex-snapshot
FARSITE: Fire Area Simulator-model development and evaluation
inferredcites →https://doi.org/10.5424/fs/2018272-13175openalex-snapshot
A generic fuel moisture content attenuation factor for fire spread rate empirical models
inferredcites →https://doi.org/10.5849/forsci.12-064openalex-snapshot
Calibrating and Testing the Forest Vegetation Simulator to Simulate Tree Encroachment and Control Measures for Heathland Restoration in Southern Europe

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Cloud-based urgent computing for forest fire spread prediction
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Leveraging the power of internet of things and artificial intelligence in forest fire prevention, detection, and restoration: A comprehensive survey
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Wildfire spread prediction using geostationary satellite observation data and directional ROS adjustment factor
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Comment on essd-2023-182
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Comment on essd-2023-182
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.