over the last decade or so, artificial neural networks (anns) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. however, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. for this reason, this study aims at de...

Neural maps are a very popular class of unsupervised neural networks that project high-dimensional data of the input space onto a neuron position in a low-dimensional output space grid. It is desirable that the projection effectively preserves the structure of the data. In this paper we present a hybrid model called K-Dynamical Self Organizing Maps (KDSOM ) consisting of K Self Organizing Maps ...

The advance in the global environment, rapidly changing markets, and information technology has created a new stage for design. In such an environment, one strategy for success is the Collaborative Product Development (CPD). Organizing people effectively is the goal of Collaborative Product Development, and it solves the problem with certain foreseeability. The development group activities are ...

This article describes a sensor network suitable for human tracking and a sensor localization methodology using self-organizing map in indoor environments. We employed sensor nodes with passive binary infrared motion sensors, and characteristically implemented with functionalities for network configuration, time synchronization, and collision avoidance for transmitting data with accuracy. Using...

– A new technique of color face recognition is proposed. First processing stage consists of an optimum color conversion from the 3D RGB space into a 2D selected feature space using the old Karhunen-Loève transform (KLT). The resulted 2D color space is defined by the two color components (called C1 and C2), corresponding to the two largest eigenvalues of the RGB pixel covariance matrix. The seco...

Clustering algorithm for the moving or trajectory data provides new and helpful information. It has wide application on various location aware services. In this study the Self Organizing Map is used to form the cluster on trajectory data. The self-organizing map (SOM) is an important tool in exploratory phase of data mining. It projects input space on prototypes of a low-dimensional regular gri...

Self-Organizing Maps possess unique properties that remove redundancies in a high-dimensional input space and map that input space to a low dimensional output space, thereby showing non-linear relationships in the input data. This ability makes Self-Organizing Maps attractive for measuring inter-limb coordination patterns. The current study takes previously published data (Bartlett, Bussey, & F...

Under mild conditions, it can be induced from the Karush–Kuhn–Tucker condition that the Pareto set, in the decision space, of a continuous Multiobjective Optimization Problems(MOPs) is a piecewise continuous ( 1) m D   manifold(where m is the number of objectives). One hand, the traditional Multiobjective Optimization Algorithms(EMOAs) cannot utilize this regularity property; on the other han...

This paper presents a self-organizing power system stabilizer (SOPSS) which use the fuzzy Auto-Regressive Moving Average (FARMA) model. The control rules and the membership functions of proposed the fuzzy logic controller are generated automatically without using any plant model. The generated rules are stored in the fuzzy rule space and updated on-line by a self-organizing procedure. To show t...