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This paper presents online tools based decision tree (DT) and artificial neural network (ANN) to identify the critical operating scenarios and enhance the system dynamic performance considering stochastic behavior of wind energy. The stochastic behavior of wind speed requires a fast generation rescheduling to meet the load demand that may force the system towards stability limits. The objective is...
This work presents a metaheuristic hybrid optimization technique developed to synthesize frequency selective surface (FSS) structures, composed of triangular patch elements and printed on FR-4 dielectric substrates for microwave filtering applications. The optimization technique is based on the combination of genetic algorithm (GA) and Multilayer Perceptron (MLP) artificial neural network (ANN). The...
Electromyography (EMG) signal can be defined as a measure of electrical activity produced by skeletal muscles. It can be used in handling electronic devices or prosthesis. If we are able recognize the hand gesture captured using EMG signal with greater reliability and classification rate, it could serve a good purpose for handling the prosthesis and to provide the good quality of life to amputees...
This paper presents a solar radiation forecasting method using nonlinear autoregressive neural networks (NAR). NAR predicts a clearness index that is used to forecast global solar radiations. The NAR model is based on the feed forward multilayer perception model with two inputs and one output. Data of three years (2012-2014) of global solar radiation time-series for Ghardaïa site (desert area), south...
Reducing carbon emissions has accelerated the use of various renewable resources for electricity generation. Wind generation, in this context has seen increasing installations globally. Managing the intermittency of wind towards existing power system operation and control therefore becomes crucial. One effective solution is to predict the future values of wind power production. This paper focuses...
This paper proposes a method to determine the optimum Battery Energy Storage System (BESS) size, considering how the location of BESS affects the micro-grid and analysis of power loss for the consideration of different locations of BESS. The possibility of installing an optimum BESS as the distributed BESS at different locations is proposed. Artificial neural network (ANN) was established to evaluate...
An Artificial Neural Network (ANN) based approach is carried out for power system unsymmetrical fault classification and localization using Continuous Wavelet Transform (CWT) in Hybrid Distributed Generation (HDG) System. In this study, CWT is used as a signal processing tool to extract features of HDG System current signals captured from distribution substation. The extracted features are applied...
This study proposes a new forecasting method for short-term spot prices in the Nordic power market. It proposes a Cuckoo search Levenberg–Marquardt (CSLM)-trained, CSLM feed-forward neural network (CSLM-FFNN) for the solving process that combines the improved Levenberg Marquardt and Cuckoo search algorithms. The proposed model considers actual power generation and system load as input sets to facilitate...
In the field of High Speed SerDes (HSS) channel analysis and design, the most widely accepted metrics for gauging signal integrity are Time Domain (TD) metrics: Bit Error Rate (BER), Eye-Height (EH) and Eye-Width (EW). With increasing bit-rates, TD simulations are getting compute-time intensive especially as the BER criterion is getting lower. Learning based mapping of Frequency Domain (FD) S-Parameter...
Even when the conditions to achieve robust chaotic response in nonlinear MEMS oscillators are verified, the attainment of the proper parameters for chaotic signal generation is not immediate. This paper presents for the first time a control method based on fuzzy logic and artificial neural networks to maximize the chaotic response, and tests its effectiveness through numerical simulations of a cc-beam...
The time series analysis and forecasting is an essential tool which can be widely applied for identifying the meaningful characteristics for making future ad-judgements; especially making decisions in finance under the numerous type of economic policies and reforms have been regarding as the one of the biggest challenge in the modern economy today.
The past decade has witnessed an increasing interest in applying internet and internet of things for problems involved behavioural intervention, and using these technologies to supervise the collection, analysis, and guidance of optimised interventions. In this paper, we presented a web-based multipurpose behaviour intervention investigation solution. This multipurpose behaviour intervention system...
In this paper the implementation of a virtual sensor is presented, using an artificial neural network (ANN) in an FPGA system, which will serve to estimate the speed of a DC motor. The acquisition and processing of signals RNA training and detailed architecture implemented in the FPGA is shown. Finally the behavior of the virtual sensor is analyzed in normal and abnormal operating conditions.
An artificial neural network (ANN) based maximum power point tracking (MPPT) algorithm has been developed. The proposed ANN based controller has the ability to estimate wind speed by tracking the maximum power point (MPP) and the optimal rotor speed with very low error compared to the conventional MPPT methods. The algorithm is based on two series neural networks, one for wind speed estimation and...
Lending loans to borrowers is considered one of the main profit sources for banks and financial institutions. Thus, careful assessment and evaluation should be taken when deciding to grant credit to potential borrowers. With the rapid growth of credit industry and the massive volume of financial data, developing effective credit scoring models is very crucial. The literature in this area is very dense...
Tongue is one of the most important sensory organs of our system. With the help of tongue, we are able to distinguish between the various food items which we eat or drink. The sensors on the tongue identify the tastes which are classified as bitter, sour, salty, sweet, umami (delicious). These are the parameters that help in determining and distinguishing the liquids like beer, tea, coffee, honey,...
This paper determine the resonant frequency of a rectangular patch antenna using Artificial Neural Network (ANN) at a given length, width, height and dielectric constant. The result of ANN model is compare with theoretical design equation of rectangular patch antenna. The resonant frequency is maintained at Ku (12 GHz–18 GHz) band which is used for satellite communication and radar applications. The...
Optical Character Recognition (OCR) is the mechanical or electronic conversion of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used as a form of data entry. This paper proposes an approach to design and implement an off-line OCR system that recognizes Arabic handwritten characters; in this approach Artificial Neural Networks (ANNs) were used as...
The paper presents a unique and optimal modeling of elevator system to achieve excellence in energy efficient & low cost operation of elevators. The traffic control and time management has been crucial issue in group elevator control. Here an attempt is made to optimize this using soft computing techniques i.e. ANN and Fuzzy logic; a comparison between them for optimal choice.
The main body of the literature states that Artificial Neural Networks must be regarded as a "black box" without further interpretation due to the inherent difficulties for analyze the weights and bias terms. Some authors claim that ANN trained as a regression device tend to organize itself by specializing some neurons to learn the main relationships embedded in the training set, while other...
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