期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2013
卷号：4
期号：2
页码：224-226
出版社：TechScience Publications
摘要：In wireless sensor networks, sensor node localization is important because sensor nodes are randomly scattered in the region of interest and they get connected into network on their own. Localization information is needed in routing of data, reducing energy consumption and in location dependent data acquisition. No prior knowledge of the noise distribution is the intelligence of a neural network. Noisy distance measurements can be used directly to train the network with the actual coordinate locations. The neural network is capable of characterizing the noise and compensating for it to obtain the accurate position. In this paper, we show that MLP can potentially achieve the highest localization accuracy and requires the least amount of computational and memory resources. Neural Network with its class MLP provides an optimistic solution of localization.
关键词：In wireless sensor networks; sensor node localization;is important because sensor nodes are randomly scattered in the;region of interest and they get connected into network on their;own. Localization information is needed in routing of data;reducing energy consumption and in location dependent data;acquisition. No prior knowledge of the noise distribution is the;intelligence of a neural network. Noisy distance measurements;can be used directly to train the network with the actual;coordinate locations. The neural network is capable of;characterizing the noise and compensating for it to obtain the;accurate position. In this paper; we show that MLP can;potentially achieve the highest localization accuracy and;requires the least amount of computational and memory;resources. Neural Network with its class MLP provides an;optimistic solution of localization.
