This article presents numerical studies on semi-active seismic response control of structures equipped with Magneto-Rheological (MR) dampers. A multi-layer artificial neural network (ANN) was employed to mitigate the influence of time delay, This ANN was trained using data from the El-Centro earthquake. The inputs of ANN are the seismic responses of the structure in the current step, and the ou...

The artificial neural network (ANN) is a widely used mathematical model composed of interconnected simple artificial neurons, which has been applied in a variety of applications. However, how to determine number of neurons in the hidden layers is an important part of deciding overall neural network architecture. Many rule-of-thumb methods for determining the appropriate number of neurons in the...

Research in AIA neural network is an artificial representation of the human brain that tries to simulate its learning process. An artificial neural network (ANN) is often called a "Neural Network” or simply Neural Net (NN). In this paper I provide the survey which I found more interesting facts in my research. That is 1.The brief study of human brain and nervous system 2. What actually an intel...

In recent years, biodiesel has been considered as a good alternative of diesel fuels. Density and viscosity are two important properties of these fuels. In this study, density and kinematic viscosity of biodiesel-diesel blends were estimated by using artificial neural network (ANN). A three-layer feed forward neural network with Levenberg-Marquard (LM) algorithm was used for learning empirical ...

kashan aquifer is adjacent to salt lake. because of this adjacency, the saline water of the lake has moved to the aquifer. in this study groundwater quality of the aquifer was simulated using artificial neural network (ann) model. for this purpose, the dominant ion of water was first determined by piper diagram. results showed that the sodium chloride is the dominant ion of water and so it was ...

abstract from longley, the various equations for determining the runoff to water management are presented by the researchers that are widely used in hydrologic sciences. in this study by using observational data, was evaluated empirical, artificial neural network (ann) and ca-active neuro-fuzzy inference system (canfis) models in estimation of runoff. for this purpose, by using climatic and phy...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

The paper deals with training the neural models of microwave structures. The first, an artificial neural network (ANN) is trained with basic genetic algorithm (GA). Training abilities are discussed. Further, the modification of GA and an approach to learning artificial neural networks (ANN) with backpropagation is described. Neural networks are implemented in MATLAB. Results of training abiliti...