As a matter of fact, the estimated loss of the human life caused by the earthquake is a crucial issue. This estimate helped to administrators in planning for the preventive measures or the crisis management after the earthquake. In this article, we represented a new model for measuring the loss of human life utilizing the self-organizing competitive neural networks. In the latest model, the neu...

Neural gas network is a single-layered soft competitive neural network, which can be applied to clustering analysis with fast convergent speed comparing to Self-organizing Map (SOM), K-means etc. Combining neural gas with principal component analysis, this paper proposes a new clustering method, namely principal components analysis neural gas (PCA-NG), and the online learning algorithm is also ...

Self-organising neural networks preserves the topology of an input space by using their competitive learning. In this work we use a kind of self-organising network, the Growing Neural Gas, to represent non rigid objects as a result of an adaptive process by a topology-preserving graph that constitutes an induced Delaunay triangulation of their shapes. The neural network is used to build a syste...

As a matter of fact, the estimated loss of the human life caused by the earthquake is a crucial issue. This estimate helped to administrators in planning for the preventive measures or the crisis management after the earthquake. In this article, we represented a new model for measuring the loss of human life utilizing the self-organizing competitive neural networks. In the latest model, the neu...

We propose a new surface reconstruction algorithm based on an incrementally expanding neural network known as Growing Cell Structure. The neural network learns a probability space, which represents the surface for reconstruction, through a competitive learning process. The topology is learned through statistics based operations which create boundaries and merge them to create handles. We study ...

It’s of great significance for wind power integration into grid to forecast wind power. Based on forecasting wind power by BP neural network, the article introduces global optimization algorithm, Imperialist Competitive Algorithm (ICA) to provide optimized initial weights of BP neural network. Thus, it can overcome the entrapment in local optical optimum of BP neural network. Compared with BP n...

Most Artificial Neural Networks (ANNs) have a fixed topology during learning, and typically suffer from a number of short-comings as a result. Variations of ANNs that use dynamic topologies have shown ability to overcome many of these problems. This paper introduces Location-Independent Transformations (LITs) as a general strategy for implementing feedforward networks that use dynamic topologie...

information on nitrate in groundwater resources requires periodic measurements are accurate. despite the measure in some areas due to sensitive social and health community are not reported. therefore, be informed of the status of each area of water quality, modeling is essential. the purpose of this study was the application of artificial neural network method for estimating nitrate and compare...

The competitive learning is an adaptive process in which the neurons in a neural network gradually become sensitive to different input pattern clusters. The basic idea behind the Kohonen’s Self-Organizing Feature Maps (SOFM) is competitive learning. SOFM can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main features of this kind of mappi...