This paper addresses the problem of rate control for Available Bit Rate (ABR) service class in Asynchronous Transfer Mode (ATM) networks. An adaptive neurofuzzy mechanism based on Adaptive Network Fuzzy Inference System (ANFIS) for allocating rates in ABR service has been proposed and compared with the fuzzy technique called as Fuzzy Explicit Rate Marking (FERM). To achieve this, a neurofuzzy A...

Conventional control algorithms used in pH control systems give inefficient performance, leading to use of large mixers. To improve the neutralization control process, an ANFIS based advanced controller has been proposed. In this paper, method of design of adaptive controller based on neurofuzzy technique is presented. The method uses ANFIS methodology to automatically generate fuzzy rule base ...

In this work the application of a neurofuzzy control system in a multimachine power system is presented. The neurofuzzy control is obtained by the off-line training of a fuzzy neural network based on

Owing to the evolution of the smart grid, the emergence of hybrid power systems (HPSs), and the proliferation of plug-in-hybrid electric vehicles, the development of efficient and robust maximum power point tracking (MPPT) algorithms for renewable energy sources due to their inherent intermittent nature has overwhelmed the power industry. In this paper, an incremental conductance (IC) based Her...

En el bombeo mecánico de petróleo, para minimizar los costos operativos y maximizar la producción, es esencial identificar problemas forma rápida precisa. El dinagrama fondo pozo decisivo analizar las condiciones trabajo del sistema bombeo, normalmente diagnóstico fallas se ha basado en interpretación visual su forma, por un experto humano. Se presenta una arquitectura (NeFSuckerRod) automático...

Motivated by the research works in adaptive observers, this paper presents a structure for black-box identification based on state-space recurrent neural networks for a class of dynamic nonlinear systems in discrete-time. The proposed network catches the dynamics of the unknown plant by generating state estimates of a network and jointly identifying its parameters using only output measurements...

Our original motivation for the development of the Feature Space Mapping (FSM) system came from cognitive modelling. Mind arises from complex dynamics of the brain. Approximations to this dynamics lead to a set of concepts [1] helpful in description of the mind, such as the “inner space” concept, called also the “conceptual space” or the “mind space”. Among many other aspects mind models should...

This article presents the Neo-Fuzzy-Neuron Modified by Kohonen Network (NFN-MK), an hybrid computational model that combines fuzzy system techniques and artificial neural networks. Its main task consists in the automatic generation of membership functions, in particular, triangle forms, aiming a dynamic modeling of a system. The model is tested by simulating real systems, here represented by a ...

This paper evaluates the performance of ten significance measures applied to the problem of determining an appropriate network structure, for data modelling with neurofuzzy systems. The advantages of Neurofuzzy systems are demonstrated with application to both real and synthetic data interpretation problems.

Fuzzy systems, neural networks and its combination in neuro-fuzzy systems are already well established in data analysis and system control. Especially, neurofuzzy systems are well suited for the development of interactive data analysis tools, which enable the creation of rule-based knowledge from data and the introduction of a-priori knowledge into the process of data analysis. However, its rec...