This paper presents a method for prediction short-term power demand of a vehicular power system. The forecasting of power demand is presented using wavelet decomposition and artificial neural network, a hybrid model which absorbs some merits of wavelet transform and neural network. The power demand time series is first decomposed into a certain number of levels with discreet wavelet transform a...

Introduction: Evoked potentials arisen by stimulating the brain can be utilized as a communication tool  between humans and machines. Most brain-computer interface (BCI) systems use the P300 component,  which is an evoked potential. In this paper, we evaluate the use of the hidden Markov model (HMM) for  detection of P300.  Materials and Methods: The wavelet transforms, wavelet-enhanced indepen...

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 ...

correct estimation of water inflow into underground excavations can decrease safety risks and associated costs. researchers have proposed different methods to asses this value. it has been proved that water transmissivity of a rock joint is a function of factors, such as normal stress, joint roughness and its size and water pressure therefore, a laboratory setup was proposed to quantitatively m...

background and aims: depression disorder is one of the most common diseases, but the diagnosis is widely complicated and controversial because of interventions, overlapping and confusing nature of the disease. so, keeping previous patients’ profile seems effective for diagnosis and treatment of present patients. use of this memory is latent in synthetic neuro-fuzzy algorithm. present article in...

Function approximation, which finds the underlying relationship from a given finite input-output data is the fundamental problem in a vast majority of real world applications, such as prediction, pattern recognition, data mining and classification. Various methods have been developed to address this problem, where one of them is by using artificial neural networks. In this paper, the radial bas...

ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...

A novel approach for classifying different types of faults occurring in power transmission lines is proposed by considering wavelet transform, singular value decomposition and Fuzzy Reasoning Spiking Neural P Systems (FRSNPS). In this approach, singular value decomposition in wavelet domain is used to extract features of fault current components recorded from power transmission lines; FRSNPS is...

In this paper, Haar wavelet-based neural network is described for the identification and control of discrete-time nonlinear dynamical systems. Wavelets are suited to depict functions with local nonlinearities and fast variations because of their intrinsic properties of finite support and self-similarity. Due to the orthonormal properties of Haar wavelet functions, wavelet neural networks result...