Recently, many neural network models have been applied to Chinese word segmentation. However, such models focus more on collecting local information while long distance dependencies are not well learned. To integrate local features with long distance dependencies, we propose a dependency-based gated recursive neural network. Local features are first collected by bi-directional long short term m...

Traditional DEA models deal with measurements of relative eciency ofDMUs regarding multiple - inputs VS. multiple-outputs. One of the drawbacksof these model is the neglect of intermediate products or linkong activities. Af-ter pointing out needs for inclusion of them to DEA models. We propose hybridmodel that can deal with intermediate products formally using this model wecan evaluate division...

During the past 20 years, artificial neural networks was successfully applied for solving signal processing problems. Researchers proposed many different models of artificial neural networks. A challenge is to identify the most appropriate neural network model which can work reliably for solving realistic problem. This chapter provides some basic neural network model and efficiently applying th...

we propose a method for medical image denoising using calculus of variations and local variance estimation by shaped windows. this method reduces any additive noise and preserves small patterns and edges of images. a pyramid structure-texture decomposition of images is used to separate noise and texture components based on local variance measures. the experimental results show that the proposed...

in this research we have presented a local model for implementing systems engineering activities in optimized acquisition of electronic systems in electronic high-tech industrial. in this regard, after reviewing the literature and the use of documents, articles and latin books, we have collected system acquisition life cycle models from different resources. after considering the criteria of the...

By analyzing the dynamics behavior and parameter distribution of the transiently chaotic neural network, we propose an improved transiently neural network model with new embedded back-end chaotic dynamics for combinatorial optimization problem and test it on the maximum clique problem. With the new embedded back-end chaotic dynamics, the proposed model can get enough chaotic dynamics to do glob...

Neural network based Chinese Word Segmentation (CWS) approaches can bypass the burdensome feature engineering comparing with the conventional ones. All previous neural network based approaches rely on a local window in character sequence labelling process. It can hardly exploit the outer context and may preserve indifferent inner context. Moreover, the size of local window is a toilsome manual-...

This paper presents an e-Knowledge application able to support decision makers in strategic planning for the growth of a territory. The application integrates a decision support system and provides e-Knowledge services for the analysis of territorial dynamics by processing and modelling huge amounts of data through mining techniques, in order to discover rules and patterns in a distributed and ...

in this paper we present the problem of designing a three level hub center network. in our network, the top level consists of a complete network where a direct link is between all central hubs.  the second and third levels consist of star networks that connect the hubs to central hubs and the demand nodes to hubs and thus to central hubs, respectively. we model this problem in an incomplete net...