In this paper, model reference neural network structure is used as a controller for vibration suppression of the Euler–Bernoulli beam under the excitation of moving mass travelling along a vibrating path. The non-dimensional equation of motion the beam acted upon by a moving mass is achieved.  A Dirac-delta function is used to describe the position of the moving mass along the beam and its iner...

It is suggested that a quantum neural network (QNN), a type of artificial neural network, can be built using the principles of quantum information processing. The input and output qubits in the QNN can be implemented by optical modes with different polarization, the weights of the QNN can be implemented by optical beam splitters and phase shifters. Since it was first proposed by Feynman [1], th...

Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...

The parts of speech disambiguation in corpora is most challenging area in Natural Language Processing. However, someworkshave been done in the past to overcome the problem of bilingual corpora disambiguation forHindi using Hidden Markov Model and Neural Network. In this paper,Quantum Neural Network (QNN) forHindi parts of speech tagger has been used.To analyze the effectiveness of the proposed ...

facts technology has considerable applications in power systems, such as; improving the steady stateperformance, damping the power system oscillations, controlling the power flow, and etc. statcom is oneof the most important facts devices used in the parallel compensation, enhancing transient stability andetc. since three phase fault is widespread in power systems, in this paper statcom is used...

The amount of data processed in the cloud, development Internet-of-Things (IoT) applications, and growing privacy concerns force transition from cloud-based to edge-based processing. Limited energy computational resources on edge push traditional von Neumann architectures In-memory Computing (IMC), especially for machine learning neural network applications. Network compression techniques are a...

this paper presents a fuzzy search controller approach along with the look-up tables, to optimize the efficiency of a pump-induction motor drive. the induction motor and the converter are modeled based on thermal loss; and for modeling the pump and the hydraulic system, which are non-linear and relatively complicated, the neural network is used. in the designed system, in order to optimize the ...

in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

Quantum Neural Networks (QNN) are considered a candidate for achieving quantum advantage in the Noisy Intermediate Scale computer (NISQ) era. Several QNN architectures have been proposed and successfully tested on benchmark datasets machine learning. However, quantitative studies of QNN-generated entanglement investigated only up to few qubits. Tensor network methods allow emulate circuits with...