In this paper, a novel neuro-fuzzy based method combined with a feature selection technique is proposed for online dynamic voltage stability status prediction of power system. This technique uses synchronized phasors measured by phasor measurement units (PMUs) in a wide-area measurement system. In order to minimize the number of neuro-fuzzy inputs, training time and complication of neuro-fuzzy ...

Problem statement: Computer networks are expanding at very fast rate and the number of network users is increasing day by day, for full utilization of networks it need to be secured against many threats including malware, which is harmful software with the capability to damage data and systems. Fuzzy rule based classification systems considered as an active research area in recent years, due to...

In this paper performance of Puma 560 manipulator is being compared for hybrid gradient descent and least square method learning based ANFIS controller with hybrid Genetic Algorithm and Generalized Pattern Search tuned radial basis function based Neuro-Fuzzy controller. ANFIS which is based on Takagi Sugeno type Fuzzy controller needs prior knowledge of rule base while in radial basis function ...

The goal of this work is to propose a learning procedure for fuzzy systems. Fuzzy systems are able to treat uncertain and imprecise informations. They have a capability to express knowledge in the form of linguistic rules. Their drawbacks are caused mainly by the diiculty of deening accurate membership functions and lack of a systematic procedure for the transformation of the expert knowledge i...

In this paper, a novel self-generating neuro-fuzzy system through reinforcements is proposed. Not only the weights of the network but also the architecture of the whole network are all learned through reinforcement learning. The proposed neuro-fuzzy system is applied to the inverted pendulum system to demonstrate its performance. Key-words: reinforcement learning, neural network, neuro-fuzzy sy...

Today hybrid computing is a popular framework for solving complex problems. If we have knowledge expressed in rules, we can build an Expert System, and if we have data, or can learn from stimulation (training) then we can use Artificial Neural Networks. In this paper we present the FUzzy NEUrule System (FUNEUS) which is a Neuro Fuzzy approach based on fuzzy Adaline neurons and uses Differential...