Design of environmental sensor networks using evolutionary algorithms
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Budi, Setia
de Souza, Paulo
Engelke, Ulrich
He, Jing
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Abstract
An evolutionary algorithm (EA)-assisted spatial sampling methodology is proposed to assist decision makers in sensor network (SN) deployments. We incorporated an interpolation technique with leave-one-out cross-validation (LOOCV) to assess the representativeness of a particular SN design. For the validation of our method, we utilized Tasmania's South Esk Hydrological Model developed by the Commonwealth Scientific and Industrial Research Organisation, which includes a range of environmental variables describing the landscape. We demonstrated that our proposed methodology is capable of assisting in the initial design of SN deployment. Ordinary Kriging is shown to be the best suited spatial interpolation algorithm for the EA's LOOCV under the current empirical study.
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IEEE Geoscience and Remote Sensing Letters
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13
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4
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© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Subject
Artificial intelligence
Electronics, sensors and digital hardware
Geomatic engineering
Science & Technology
Physical Sciences
Technology
Geochemistry & Geophysics
Engineering, Electrical & Electronic
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Susanto, F; Budi, S; de Souza, P; Engelke, U; He, J, Design of environmental sensor networks using evolutionary algorithms, IEEE Geoscience and Remote Sensing Letters, 2016, 13 (4), pp. 575-579