TY - JOUR TT - ANFIS Analysis of Wireless Sensor Data with FPGA AU - Ercan, Tuncay AU - Ahmed, Khazal PY - 2018 DA - June DO - 10.30801/acin.357635 JF - Acta Infologica JO - ACIN PB - Istanbul University WT - DergiPark SN - 2602-3563 SP - 22 EP - 32 VL - 2 IS - 1 LA - en KW - ANFIS KW - Neuro-Fuzzy System KW - FPGA KW - Sensor Nodes KW - Smart Node N2 - Applicationsrelated with WSNs may include thousands of separate sensor nodes, productionand control data for different industrial sectors. It is important to managethese applications, monitor the network and reprogram the nodes to avoidoperational problems. In this study, we propose a smart wireless sensor networkusing a reconfigurable embedded system of Field-Programmable Gate Arrays(FPGAs) with a soft-core processor. This processor can be programmeddynamically and synthesized to implement the preprocessing of sensed data byensemble Hybrid Neuro-Fuzzy algorithms such as Adaptive Neuro-Fuzzy InferenceSystem (ANFIS). The first part of the proposed work is based on Matlab softwareto develop and train the ANFIS algorithm. Two different types of data sets(temperature and humidity) downloaded from Internet have been used in order tomake a comparison between the Matlab Toolbox and modified ANFIS algorithm withmomentum factor. The results obtained in this study have shown that themodified ANFIS algorithm is the convenient choice in terms of speed, accuracy. CR - [1] Ahmed, E.,Mohamed, S., Khaled, M., Ahmed, A., (2016), A hybrid neuro-fuzzy power prediction system for wind energy generation, International Journal of Electrical Power & Energy Systems,74, 384-395. CR - [2] Akyıldız, L., Sankarasubramaniam, Y., Su, W., Cayırcı, E. ,(2002), “Wireless sensor networks: A survey”, Journal of Computer Networks, 38, 393-422. 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