Shield is a typical mechanical, electrical, hydraulic integration of equipment. Its faults species are complex and diverse. To prevent because machine failure causes economic losses and casualties by shield, this article will introduces rough set theory to the subway shield machine fault diagnosis, propose a method which is based on rough set theory combined with neural network of Metro shield ...

Automated fault forecasting proactivity offers a promising closed-loop approach for conventional network failure management activities. Automated intelligent failure forcasting requires the capability to prefilter the observation data so as to remove irrelevant features or factors from multi-dimensional observation data. In this paper, we propose a new hybrid methodology of combining the rough-...

The fault parameters of ball mill was unnoticed among large amount of data, According to the phenomenon, it put forward a fault diagnosis method of rough set to optimize neural network, and by using width algorithm, so that the fault sample set of ball mill had been processed with the discrete way. Firstly, it builded a diagnosis model of rough set-neural network, the diagnosis model had practi...

This paper presents a condition diagnosis method for a blower system using the rough sets, and a fuzzy neural network to detect faults and distinguish fault types. In order to solve the ambiguous problem between the symptoms and the fault types, the diagnosis knowledge for the training of the neural network is acquired by using the rough sets. The fuzzy neural network realized by partially-line...

This paper presents a methodology to biological image classification through a Rough-Fuzzy Artificial Neural Network (RFANN). This approach is used in order to improve the learning process by Rough Sets Theory (RS) focusing on the feature selection, considering that the RS feature selection allows the use of low dimension features from the image database. This result could be achieved, once the...

Because of high computational complexity of neural network to obtain the basic probability assignment of evidence theory, this paper proposed a method of rough set theory based on random set and BP neural network to obtain the basic probability assignment. In the framework of random set, this paper makes use of the ability of rough set’s attribute reduction to reduce the neural network input di...

Neural spike sorting refers to the classification of electric potentials (spikes) from multi-neuron recordings, a difficult but essential pre-processing step before neural data can be analyzed for information content. In this paper, we propose a novel method of multineuronal spike sorting based on rough set theory. In the experiments, the performance of the presented system was tested at variou...

Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is ...