Neuro-Fuzzy Computing System with the Capacity of Implementation on Memristor-Crossbar and Optimization-Free Hardware Training [PDF]
, 2012 In this paper, first we present a new explanation for the relation between logical circuits and artificial neural networks, logical circuits and fuzzy logic, and artificial neural networks and fuzzy inference systems.
Merrikh-Bayat, Farnood +2 more
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Electricity consumption forecasting using Adaptive Neuro-Fuzzy Inference System (ANFIS) [PDF]
, 2019 Universiti Tun Hussein Onn Malaysia (UTHM) is a developing Malaysian Technical University. There is a great development of UTHM since its formation in 1993.
K.G., Tay +3 more
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Modeling of Fuzzy Systems Based on the Competitive Neural Network
Applied Sciences, 2023 This paper presents a method to dynamically model Type-1 fuzzy inference systems using a Competitive Neural Network. The aim is to exploit the potential of Competitive Neural Networks and fuzzy logic systems to generate an intelligent hybrid model with ...
Juan Barraza +3 more
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Monotone Interval Fuzzy Inference Systems [PDF]
IEEE Transactions on Fuzzy Systems, 2019 In this paper, we introduce the notion of a monotone fuzzy partition , which is useful for constructing a monotone zero-order Takagi–Sugeno–Kang Fuzzy Inference System (ZOTSK-FIS). It is known that a monotone ZOTSK-FIS model can always be produced when a consistent, complete, and monotone fuzzy rule base is used.
Yi Wen Kerk, Kai Meng Tay, Chee Peng Lim
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Z Number Based Fuzzy Inference System for Dynamic Plant Control
Advances in Fuzzy Systems, 2016 Frequently the reliabilities of the linguistic values of the variables in the rule base are becoming important in the modeling of fuzzy systems. Taking into consideration the reliability degree of the fuzzy values of variables of the rules the design of ...
Rahib H. Abiyev
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Advances in Mechanical Engineering, 2016 Magnetorheological dampers have become prominent semi-active control devices for vibration mitigation of structures which are subjected to severe loads.
Xiufang Lin, Shumei Chen
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Identifikasi Gangguan Neurologis Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS)
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2015 Abstrak Penggunaan metode Adaptive Neuro Fuzzy Inference System (ANFIS) dalam proses identifikasi salah satu gangguan neurologis pada bagian kepala yang dikenal dalam istilah kedokteran stroke ischemic dari hasil ct scan kepala dengan tujuan untuk ...
Jani Kusanti, Sri Hartati
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Extending the functional equivalence of radial basis functionnetworks and fuzzy inference systems [PDF]
, 1996 We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference.
Haas, R., Hunt, K.J., Murray-Smith, R.
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Genetic fuzzy system for prediction of respiratory rate of chicks subject to thermal challenges
Revista Brasileira de Engenharia Agrícola e AmbientalThe aim of this study was to estimate and compare the respiratory rate (breath min-1) of broiler chicks subjected to different heat intensities and exposure durations for the first week of life using a Fuzzy Inference System and a Genetic Fuzzy Rule ...
Patrícia F. P. Ferraz +5 more
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Modelling of a Flexible Manoeuvring System Using ANFIS Techniques [PDF]
, 2010 The increased utilization of flexible structure systems, such as flexible manipulators and flexible aircraft in various applications, has been motivated by the requirements of industrial automation in recent years.
Bin Zaidan, Martha Arbayani +2 more
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