This is a short, two-line summary of the day’s lecture. Should provide a rough set of topics covered or questions discussed.

This paper proposes a hybrid intelligent system that predicts the failure of firms based on the past financial performance data, combining rough set approach and neural network. We can get reduced information table, which implies that the number of evaluation criteria such as financial ratios and qualitative variables is reduced with no information loss through rough set approach. And then, thi...

This paper presents a fault diagnosis method for a centrifugal pump system with frequency-domain symptom parameters by using the wavelet transform, rough sets and a fuzzy neural network to detect faults and distinguish fault types at an early stage. The wavelet transform is used for feature extraction across an optimum frequency region. The diagnosis knowledge for the training of neural network...

In order to solve speed and accuracy problems of maneuvering target tracking in wireless sensor networks, a Rough Set and neural network Adaptive Interacting Multiple Model (RSAIMM) tracking algorithm was proposed. Based on the establishment of target movement model and rough set neural integration adaptive model, a decision making method which combined rough set theory and neural network was u...

Face Recognition is oldest, natural method of visual interaction. Early face recognition algorithms used simple geometric models, but the recognition process has now matured into a science of sophisticated mathematical representations and matching process. Recent advances in rough set theory, parameterized approximation spaces, and rough neurocomputing coping with the uncertainty in making deci...

Shao-Han Liu Jzau-Sheng Lin, MEMBER SPIE National Chin-Yi Institute of Technology Department of Electronic Engineering No. 35, Lane 215, Sec. 1, Chung-Shan Rd Taiping, Taichung, Taiwan E-mail: [email protected] Abstract. A new fuzzy Hopfield-model net based on rough-set reasoning is proposed for the classification of multispectral images. The main purpose is to embed a rough-set learning...

This paper describes rough neural networks which consists of a combination of rough neurons and conventional neurons. Rough neurons use pairs of upper and lower bounds as values for input and output. In some practical situations, it is preferable to develop prediction models that use ranges as values for input and/or output variables. A need to provide tolerance ranges is an example of such a s...

Intrusion detection system (IDS) is now becoming an integral part of the network security infrastructure. Data mining tools are widely used for developing an IDS. However, this requires an ability to find the mapping from the input space to the output space with the help of available data. Rough sets and neural networks are the best known data mining tools to analyze data and help solve this pr...

Aimed at coping with the complexity of construction engineering cost evaluation, the advantages of rough set theory, particle swarm algorithm and BP neural network are integrated to put forward a new model of construction engineering cost evaluation, namely, the model of construction engineering cost evaluation of optimized particle swarm and BP neural network on the basis of rough set theory. ...

The paper presents application of neural network in a hybrid, high speed, pattern recognition system. The feature extraction part is built as a grating based holographic ring wedge detector and the classifier is a probabilistic neural network. Since the feature extractor can be produced with relatively low costs from computer generated high resolution masks, such masks should be designed specif...