Multi-Objective Evolutionary Algorithm for Oil Spill Detection from COSMO-SkeyMed Satellite

Marghany, Maged

doi:10.1007/978-3-319-09153-2_27

Cited by 6 publications

(11 citation statements)

References 26 publications

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“…E-MMGA is run until there is no further improvement in the entropy value (i.e., entropy 10 is maximum), and then it is stopped. The solution of the overall problem is obtained by taking the nondominated frontier of the points in the grand pool of the last E-MMGA (Marghany, 2014b) iteration (Zhang et al, 2013).…”

Section: Interactive Discussionmentioning

confidence: 99%

“…In general, MOP consists of n decision variable parameters, k objective functions and m constraints (Gunawan et al, 2004). Multi-objective Optimization (Marghany, 2014b;20 Gunawan et al, 2004) aims at conducting optimization for a range of functions as follows…”

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

“…And β 0 is called the Pareto optimal solution in the minimization problem for identification of oil spill pixels. if the following conditions are satisfied (Marghany, 2014b).…”

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

“…Following Marghany (2014b), the optimization of oil spill detection from SAR data using 20 entropy based MOEA E-MOEA, the entropy of oil spill footprint boundaries must be coded into a Genetic Algorithm syntax form i.e. the chromosome form.…”

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

“…Therefore the weights have to be changed again and again. The weights consist of random numbers and they are generated as the following way (Marghany, 2014b):…”

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

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Multi-objective entropy evolutionary algorithm for marine oil spill detection using cosmo-skymed satellite data

Marghany¹

2015

Preprint

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Abstract. Oil spill pollution has a substantial role in damaging the marine ecosystem. Oil spill that floats on top of water, as well as decreasing the fauna populations, affects the food chain in the ecosystem. In fact, oil spill is reducing the sunlight penetrates the water, limiting the photosynthesis of marine plants and phytoplankton. Moreover, marine mammals for instance, disclosed to oil spills their insulating capacities are reduced, and so making them more vulnerable to temperature variations and much less buoyant in the seawater. This study has demonstrated a design tool for oil spill detection in SAR satellite data using optimization of Entropy based Multi-Objective Evolutionary Algorithm (E-MMGA) which based on Pareto optimal solutions. The study also shows that optimization entropy based Multi-Objective Evolutionary Algorithm provides an accurate pattern of oil slick in SAR data. This shown by 85 % for oil spill, 10 % look-alike and 5 % for sea roughness using the receiver-operational characteristics (ROC) curve. The E-MMGA also shows excellent performance in SAR data. In conclusion, E-MMGA can be used as optimization for entropy to perform an automatic detection of oil spill in SAR satellite data.

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Section: Interactive Discussionmentioning

confidence: 99%

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

“…And β 0 is called the Pareto optimal solution in the minimization problem for identification of oil spill pixels. if the following conditions are satisfied (Marghany, 2014b).…”

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

“…Therefore the weights have to be changed again and again. The weights consist of random numbers and they are generated as the following way (Marghany, 2014b):…”

Section: Entropy-based Multi-objective Evolutionary Algorithm (E-mmga)mentioning

confidence: 99%

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Multi-objective entropy evolutionary algorithm for marine oil spill detection using cosmo-skymed satellite data

Marghany¹

2015

Preprint

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Automatic Detection of Coral Reef Induced Turbulent Boundary Flow in the Red Sea from Flock-1 Satellite Data

Marghany¹,

Hakami²

2018

Springer Oceanography

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Application of genetic algorithm-based support vector machines for prediction of soil liquefaction

Xue

Xiao

2016

Environ Earth Sci

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Multi-Objective Evolutionary Algorithm for Oil Spill Detection from COSMO-SkeyMed Satellite

Cited by 6 publications

References 26 publications

Multi-objective entropy evolutionary algorithm for marine oil spill detection using cosmo-skymed satellite data

Multi-objective entropy evolutionary algorithm for marine oil spill detection using cosmo-skymed satellite data

Automatic Detection of Coral Reef Induced Turbulent Boundary Flow in the Red Sea from Flock-1 Satellite Data

Application of genetic algorithm-based support vector machines for prediction of soil liquefaction

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