According to the design procedure of fault self-diagnosis system and features of automatic transmission system, the list of relation and mapping between fault symptoms and fault causes are made in this paper. Applying the approach of fault self-diagnosis based on fuzzy neural network, fault diagnosis of the automatic transmission electronic control system is realized. The structure of fuzzy neu...

To address deficiencies in the process of fault diagnosis of belt conveyor, this study uses a BP neural network algorithm combined with fuzzy theory to provide an intelligent fault diagnosis method for belt conveyor and to establish a BP neural network fault diagnosis model with a predictive function. Matlab is used to simulate the fuzzy BP neural network fault diagnosis of the belt conveyor. R...

the main problem associated with the traditional approach to image classification for the mapping of hydrothermal alteration is that materials not associated with hydrothermal alteration may be erroneously classified as hydrothermally altered due to the similar spectral properties of altered and unaltered minerals. the major objective of this paper is to investigate the potential of a neuro-fuz...

The paper presents the neuro-fuzzy controller algorithm for air conditioning system. Neuro-fuzzy control combines the learning capabilities of neural networks and control capabilities of fuzzy logic control. The neurofuzzy controller for air conditioning system takes two inputs from temperature and humidity sensors and controls the compressor speed. The experimental results of the developed sys...

Neuro-fuzzy computing, which provides efficient information processing capability by devising methodologies and algorithms for modeling uncertainty and imprecise information, forms at this juncture, a key component of soft computing. An integrated neuro-fuzzy system is simply a fuzzy inference system trained by a neural networklearning algorithm. The learning mechanism fine-tunes the underlying...

This paper surveys Neuro fuzzy systems (NFS) development in biomedical field. Paper gives brief literature review of articles for last decade (2005-2015) which explores various Neuro Fuzzy System methodologies that have been developed during this period of time, their work done and deficiencies. Use of Neuro fuzzy integrated systems in various biomedical engineering applications is summarised. ...

Submitted: Jun 23, 2013; Accepted: Jul 20, 2013; Published: Jul 25, 2013 Abstract: Peculiar features of development of hybrid adaptive systems using neuro-fuzzy network structures are discussed. Quality and amount of information about an object is insufficient. Classical, adaptive, robust, fuzzy, neural methods of regulator designing have been compared. Problem of parameter adjustment of neuro-...

The system MiND (Multipurpose integrated Neural Device) is a tool for the development of artiicial neural network applications which integrates hardware and software components. It includes a PCI neuro{board with up to four SAND (Simple Applicable Neural Device) neuro{chips. The neuro{board accelerates feedforward networks, Radial{ Basis-Function networks, and Kohonen feature maps. There are se...

By using differential neural networks, we present a novel robust adaptive controller for a class of unknown nonlinear systems. First, dead-zone and projection techniques are applied to neural model, such that the identification error is bounded and the weights are different from zero. Then, a linearization controller is designed based on the neuro identifier. Since the approximation capability ...

Forecasting energy price and consumption is essential in making effective managerial decisions and plans. While there are many sophisticated mathematical methods developed so far to forecast, some nature-based intelligent algorithms with desired characteristics have been developed recently. The main objective of this research is short term forecasting of energy price and consumption in Iranian ...