Wireless Sensor Network Localization using Artificial Intelligence and Simulated Annealing Optimization

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Abstract

In recent years localization of nodes in wireless sensor networks (WSNs) has become one the main features of applications. In fact, this issue has been widely explored by the scientific community that proposed many approaches in order to localize network nodes. However, artificial neural network (ANN) can be used as an operating method. Therefore, we aim in this paper to select the best suited structure of ANN to localize in WSN using a meta-heuristic technique. To optimize this procedure, we use the Simulated Annealing (SA) algorithm. We constituted a network of ESP8266 modules to create our WSN topology as well as the training and the testing data to evaluate the performances.

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Abkari*, S. E., Jilbab, A., & Mhamdi, J. E. (2020). Wireless Sensor Network Localization using Artificial Intelligence and Simulated Annealing Optimization. International Journal of Recent Technology and Engineering (IJRTE), 8(6), 3488–3491. https://doi.org/10.35940/ijrte.f8911.038620

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