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26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY WOS: 000511448500023 In this article, we have proposed a new hybrid clustering algorithm based on Fuzzy C Means (FCM) and Whale Optimization Algorithm (WOA) using chaotic map. The random selection of the initial cluster centers in the FCM algorithm is a disadvantage for the algorithm. To reduce this disadvantage, the BOA algorithm, which is improved performance with chaotic maps, is used to optimize the initial cluster centers. The proposed hybrid algorithm is tested for four different sets of data and better results are obtained from the FCM algorithm. IEEE, Huawei, Aselsan, NETAS, IEEE Turkey Sect, IEEE Signal Proc Soc, IEEE Commun Soc, ViSRATEK, Adresgezgini, Rohde & Schwarz, Integrated Syst & Syst Design, Atilim Univ, Havelsan, Izmir Katip Celebi Univ

26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY WOS: 000511448500024 In this work, we propose a hybrid clustering algorithm that integrates Fuzzy C-Means (FCM) and Whale Optimization Algorithm (WOA) using the Chebshev distance function. The FCM algorithm uses Euclidean distance to measure the similarity between the data. To avoid the existing disadvantages of the Euclidean distance, all distances in the FCM algorithm is calculated with the Chebsyhev distance function. The BOA algorithm is used to optimize the initial cluster centers. The proposed hybrid algorithm is tested with three different sets of data selected from UCI Machine Learning Repository database. As a result, it is seen that the clustering performance of the proposed algorithm is much better than the FCM algorithm. IEEE, Huawei, Aselsan, NETAS, IEEE Turkey Sect, IEEE Signal Proc Soc, IEEE Commun Soc, ViSRATEK, Adresgezgini, Rohde & Schwarz, Integrated Syst & Syst Design, Atilim Univ, Havelsan, Izmir Katip Celebi Univ