Design of Environmental Sensor Networks Using Evolutionary Algorithms

作者：Susanto Ferry^*; Budi Setia^*; de Souza Paulo Jr^*; Engelke Ulrich^*; He Jing^*

来源：IEEE Geoscience and Remote Sensing Letters, 2016, 13(4): 575-579.

DOI：10.1109/LGRS.2016.2525980

• Evolutionary algorithm (EA)
• inverse distance weighting (IDW)
• leave-one-out cross-validation (LOOCV)
• multiobjective
• optimization
• ordinary Kriging (OK)
• sensor network (SN) deployment
• spatial data interpolation
• spatial sampling
• thin plate spline (TPS)

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.

• 出版日期2016-4