The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the va...

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...

This paper proposes a new heuristic for the dynamic version of the Steiner Tree Problem in Networks (SPN). The heuristic adopts a Random Neural Network (RNN) to improve solutions obtained by previously proposed dynamic algorithms. The Random Neural Network model is adapted to map the intrinsic features of the multicast transmission on a computer network. Exhaustive experiments are carried out t...

In this paper, a new architecture combining dynamic neural units and fuzzy logic approaches is proposed for a complex chemical process modeling. Such processes need a particular care where the designer constructs the neural network, the fuzzy and the fuzzy neural network models which are very useful in black box modeling. The proposed architecture is specified to the pH chemical reactor due to ...

In this paper we present a novel method for jointly extracting beats and downbeats from audio signals. A recurrent neural network operating directly on magnitude spectrograms is used to model the metrical structure of the audio signals at multiple levels and provides an output feature that clearly distinguishes between beats and downbeats. A dynamic Bayesian network is then used to model bars o...

artificial neural networks are used in many smart apparatus and different fields such as signal processing pattern diagnoses, military systems, medicine, financial systems, and artificial intelligence. in this article using quality of neural networks in optimizing energy cost in moving limb and its effectiveness in organization a cognitive function founded by presenting an algorithm for use in ...

The present work makes a contribution to the systematic integration of artificial neural networks into adaptive control systems. Besides the basic principles of mapping non-linear dynamic processes using neural networks, a structured methodology for the network design is illustrated, which allows a statistical evaluation of the learning success. In addition, to allow for an improved transparenc...

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...

In this paper, the author proposes a sensorless direct torque control (DTC) of an induction motor (IM) fed by seven-level NPC inverter using artificial neural networks (ANN) and fuzzy logic controller. Fuzzy PI controller is used for controlling the rotor speed and ANN applied in switching select stator voltage. The control method proposed in this paper can reduce the torque, stator flux and to...