A neuro-fuzzy approach for prediction of human work efficiency in noisy environment
Applied Soft Computing
Engineering Applications of Artificial Intelligence
Process control using genetic algorithm and ant colony optimization algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The paper proposes new membership functions (mfs) for fuzzy modeling. Existing mfs do not simultaneously satisfy ease in optimization and low-end hardware implementation. The proposed mfs satisfy the two contradicting requirements. The algorithm for hardware implementation is detailed. The performance and applicability of the proposed mfs are illustrated using two well-known benchmarks. Optimized fuzzy models are coded and implemented using the Intel 8XC196KC microcontroller. Results show that the proposed mfs simplify offline design and facilitate online implementation