Browsing by Author "Castillo, Oscar"

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Enhanced Classification in IF-ARCA and IF-KNN with Fuzzy Metrics and Cosine Similarity Through Dual Stage Optimization Using Harris Hawks Algorithm
(Springer London Ltd, 2025) Kutlu, Fatih; Goleli, Kubra; Castillo, Oscar
This study proposes a dual-stage optimization framework for uncertainty-aware classification by integrating the Intuition-istic Fuzzy Any Relation Clustering Algorithm (IF-ARCA) with Intuitionistic Fuzzy K-Nearest Neighbors (IF-KNN). In the first stage, Harris Hawks Optimization (HHO) calibrates IF-ARCA parameters to construct reliable membership and non-membership matrices, while in the second stage HHO independently tunes IF-KNN parameters, ensuring decoupled and stable convergence. HHO was chosen for its effective exploration-exploitation balance in high-dimensional search spaces, and the dual-stage design uniquely enables clustering and classification to be optimized without mutual interfer-ence. Extensive experiments on eight benchmark datasets (seven from UCI, plus Yeast and Credit Fraud for scalability) confirm the superiority of the proposed approach: the fuzzy metric variant achieved F1 = 0.993 on Credit Fraud and 0.946 on MONK's Problems, while cosine similarity reached 0.989 on Digits. Compared with established FKNN variants, the framework yielded 20-35% relative improvements and demonstrated statistically significant gains on challenging datas-ets (Iris, MONK's, Yeast; Wilcoxon p < 0.05). These results highlight the framework's robustness under class overlap and imbalance, while maintaining competitive performance in high-dimensional domains, establishing a novel contribution to clustering-guided classification and nature-inspired optimization.
Intuitionistic Fuzzy Control of Twin Rotor Multiple Input Multiple Output Systems
(Ios Press, 2020) Castillo, Oscar; Kutlu, Fatih; Atan, Ozkan
This paper proposes an intuitionistic fuzzy control method for twin rotor multi-input and multi-output (twin rotor MIMO) systems. Twin rotor MIMO systems are often used to measure the performance of control systems as they are extremely sensitive to environmental factors. The use of the intuitionistic fuzzy control method for modeling these uncertainties offers an effective way to increase the robustness of the control system to uncertainties in the structure of twin rotor MIMO systems. In this study, two intuitionistic fuzzy controllers are designed, namely for the main and tail rotors separately and then combine the outputs of these rotors. Also, this method is compared with the classical optimal PID method in terms of stability and performance by various simulations and experiments.
Intuitionistic Fuzzy Sliding Controller for Uncertain Hyperchaotic Synchronization
(Springer Heidelberg, 2020) Atan, Ozkan; Kutlu, Fatih; Castillo, Oscar
In this study, the design of an intuitionistic fuzzy controller for synchronization of two non-identical hyperchaotic systems is proposed. Since hyperchaotic systems has high sensitivity to the initial condition, disturbance and parameter variability. Synchronization of hyperchaotic systems is used to test the controller performance. On the other hand, using of fuzzy logic-based controller has an increasing tendency. As known, fuzzy logic control (FLC), only membership functions are used to obtain a realistic model of the systems. But the intuitionistic fuzzy logic control (IFLC) allows us to obtain a more realistic model than FLC because it also takes into account the degree of non-membership and the degree of uncertainty beside of degree of membership to model examined system. Fuzzy logic-based controllers are hybridized with robust control methods such as sliding mode controller to improve the performance of controller. To take advantages of SMC with fuzzy logic-based IFLC, the IFSMC controller obtained by hybridizing these two methods was designed for hyperchaotic systems. To demonstrate the performance of IFSMC, the results obtained from the synchronization of hyperchaotic systems with FSMC (fuzzy sliding mode controller) and IFSMC were compared. The stability of IFSMC is proved by Lyapunov stability condition. The numerical results and analysis show the efficiency of the IFSMC with regards to synchronization control of uncertain chaotic systems having challenging external disturbances in terms of robustness, minimum tracking error.