artificial neural network applications for power system protection

... EVOLUTION OF ARTIFICIAL NEURAL NETWORK CONTROLLER FOR A BOOST CONVERTER VASANTH SUBRAMANYAM (B E., Anna University, India) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING ... Algorithm for Evolving an Artificial Neural Network Controller”, Congress of Evolutionary Computation, IEEE International Conference on, Singapore, 2007 110 APPENDIX Software Codes for the DLPSO ... 37 4.4 SUMMARY 38 CHAPTER 39 PROPOSED DESIGN APPROACH FOR ARTIFICIAL NEURAL NETWORK CONTROLLER 39 5.1 CONTROL SCHEME OF THE ANN CONTROLLER 40

Ngày tải lên: 05/10/2015, 22:04

... in Table for CFB gasifiers and in Table for BFB gasifiers 2.2 Artificial neural networks topology An artificial neural network is a system based on the operation of biological neural networks, ... these models Different kinds of models have been implemented for gasification systems, including equilibrium, kinetic and artificial neural networks According to Villanueva et al [1], equilibrium ... Interpreting neural- network connection weights AI Expert 1991;6:47e51 [19] Khataee AR, Mirzajani O UV/peroxydisulfate oxidation of C I Basic Blue 3: modeling of key factors by artificial neural network

Ngày tải lên: 02/08/2016, 09:34

... reduce the need for large training samples Abbreviations ANN: Artificial neural network; CV: Cross validation; GRRANN: Gene regulatory network- based regularized artificial neural network; GRN: ... overfitting To this end, we design a gene regulatory network based artificial neural neural network model together with regularization methods for simultaneous shrinkage of gene-sets based on ‘active’ ... Kang et al BMC Bioinformatics (2017) 18:565 DOI 10.1186/s12859-017-1984-2 RESEARCH ARTICLE Open Access A biological network- based regularized artificial neural network model for robust phenotype

Ngày tải lên: 25/11/2020, 16:43

... the network? ??s output, y,) was computed The computed errors were used by the network performance function to optimize the network and the default network performance function for feedforward networks ... computation model Artificial Neural Network has been found to be very effective in prediction problems and useful in the development of models [11] Artificial Neural Network (ANN) is one of the artificial ... developing an optimal artificial neural network based on experimental data, Int Commun Heat Mass 77 (2016) 4953 [12] H Elỗiỗek, E Akdogan, S Karagöz, The use of artificial neural network for prediction

Ngày tải lên: 19/11/2022, 11:43

... to train the neural network The results were a data set consisting of 122 samples During neural network training, the data set is divided into 80% data for training and 20% data for testing Data ... rated power of the i = f1 − f is the frequency attenuation; fn is the rated frequency of the power system When the generator outage, the difference between the generation power and the load power ... patterns and training neural networks [Vol-6, Issue-12, Dec-2020] ISSN: 2454-1311 The construction of the data set is performed as follows: PowerWorld GSO 19 software is used for off-line simulation

Ngày tải lên: 18/02/2023, 08:20

... DC Motor Drive System Dynamics 16 2.5 ANN Structure for the Motor Controller 19 2.5.1 Feedforward neural network structure (FFNN) 19 2.5.2 Artificial Neural Network Structure for motor drive ... scope of applications of high- Artificial neural network based adaptive controller for DC motors Chapter Introduction performance electric motors in various industrial processes In high-performance ... tested for proper functioning, performance evaluation of the ANNbased adaptive controller is performed through extensive experimentation Artificial neural network based adaptive controller for DC

Ngày tải lên: 30/09/2015, 14:16

... training, model prediction performance analysis, neural network model changes and model verification Neural network model For utilizing a neural network model (NNM), the prediction model has to ... order to devise neural network prediction model for the syngas composition Neural 100 200 300 400 500 600 700 800 900 Time [min] Fig 11 Neural network model verification test for syngas composition ... xxx–xxx Fig 12 Results of the neural network model for hourly averaged syngas composition prediction (H2) – Pirna gasifier Fig 13 Results of the neural network model for current (left) and hourly

Ngày tải lên: 01/08/2016, 09:32

... lehongha1979@gmail.com (Ha, L H.) 51 Artificial Neural Network (ANN) is an Artificial Intelligence technique which have broad applications in risk management [8] McKim used the neural network for id [9] Wenxi used ... assess Neural risk and Network to evaluate their impacts to the project’s profit for new Artificial projects The following sections will explain the research approach in detail Artificial Neural Network ... information processing technology tha human brain and the nervous system ANN was first introduced in 1943 by Warren M Artificial Neural Network Walter Pits [13] Like the human brain, neural networks

Ngày tải lên: 11/02/2020, 12:51

... turning using artificial neural network Neural Computing & Applications, 14(4), 319-324 Quiza, R., Figueira, L., & Davim, J P (2008) Comparing statistical models and artificial neural networks on ... parameters for surface roughness in turning.Materials & design, 28(4), 1379-1385 Nalbant, M., Gokkaya, H., & Toktas, I (2007) Comparison of regression and artificial neural network models for surface ... Residuals vs fitted value for Ra 10 12 14 16 18 Observation Order 20 22 24 26 Fig Residuals vs order of the data for Ra Another predictive model based on ANN (Artificial neural network) is employed,

Ngày tải lên: 14/05/2020, 22:03

... ship berthing using artificial neural network, some new ideas are proposed in this research Firstly, head-up coordinate system is suggested to consider two new inputs for neural controller, a ... Automatic Ship Berthing Based on Artificial Neural Network Controller Using Head-up Coordinate System Van-Suong Nguyen Department of Maritime Transportation System Engineering, Graduate School ... Abstract Artificial Neural Network (ANN) has been known as one of most effective theories for automatic ship berthing because it has the learning ability and mimics action of human’s brain in performing

Ngày tải lên: 18/05/2021, 22:42

... Integrating artificial neural network and classical methods for unsupervised classification of optical remote sensing data Ahmed AK Tahir Abstract A novel system named unsupervised multiple classifier system ... of system performance”, the performance of the system is evaluated and finally some concluding remarks are given in the last section (UMCS); the proposed system In this article, the proposed system ... (classical) and artificial neural network The system is based on new integration method of the dynamic classifier selectionbased type This method is based on class-distance maps (CDM) for the individual

Ngày tải lên: 02/11/2022, 11:36

... data and to provide powerful tools for non-linear, multidimensional interpolations The back-propagation artificial neural network (BP-ANN) is a kind of artificial neural network model consisting ... high pressure values of AHP Back-propagation artificial neural network (BP-ANN).  Artificial neural networks (ANNs) are adaptive and have parallel information-processing structures, which have ... prediction of grinding mill liners using an artificial neural network Minerals Engineering 53, 1–8 (2013) 19 Z G Tian, L Wong & N Safaei A neural network approach for remaining useful life prediction

Ngày tải lên: 04/12/2022, 15:03

... Vision System based on an Artificial Neural Network for Microstructure Segmentation and Fo Quantification), developed during this work and here presented, that uses an artificial rP neural network ... in images acquired for that purpose To accomplish this, it has developed the already referred SVRNA system, which is based on an Artificial Neural Network (ANN) As the nervous system, ANN not possess ... SVRNA system Our SVRNA system was implemented in C++ using the environment Builder from Borland, runs in Microsoft Windows XP platforms and, as already referred, uses an Fo artificial neural network,

Ngày tải lên: 05/01/2023, 15:21

... for the development of modern power systems Thus, the damping ability of excitation system can be reduced, leading the low frequency oscillation of power system is inc reased Currently, the power ... Research on Adaptive Neural Fuzzy Inference System (ANFIS) controller for power system stability By Phan Xuan Le A dissertation submitted for the degree of Doctor of (Engineering） ... All problems above will steady the power system Th erefore, countries on the world have used the power system stability to enhance damping ability of excitation system leading to reduce low frequency

Ngày tải lên: 15/08/2023, 18:29

... played by power system protection systems An understanding of power systems along with correct management, will increase your plant efficiency and performance as well as increasing safety for all ... values, 21 formulae for, 20–1 Petersen coil, 29 Pilot wire monitor, 172 Power and power factor, 13–15 Power system protection: components, functions, quality, requirements, speed of, Protection: ... Engineer: Date: 270 Practical Power Systems Protection A typical test format for a motor protection relay with various protective functions could be as below P & B Golds Motor Protection Station: Circuit:

Ngày tải lên: 12/12/2013, 21:37

... or early visions by minimizing “energy” through the network dynamics We [11] proposed a neural- network $mode1^{r}toa^{r}repetitive^{s}networkfor^{-}1earning^{t}ofthe^{1}vector$ model, $recently^{o}developed$ ... problens for redundant manipulators (Fig 2) Hierarchical neural network for control and learning Ito [5] proposed that the cerebrocerebellar communication loop is used as a reference model for the ... control Fig A repetitive neural network model learns and minimizes energy for generation of torque waveforms which realize minimum torque-change arm trajectory Fig Two schemes for learning inverse

Ngày tải lên: 28/04/2014, 10:16

... introduced into power system applications in 1990, it has been widely used for power system transient studies [8, 9], but rarely used for power quality studies In this section, the basis for Prony ... transform is normally used to supervise power system harmonics in power systems To demonstrate the effectiveness of the Prony analysis for harmonic supervision, the outputs from the Fouriertransform-based ... Scientist at The Center for Advanced Power Systems at Florida State University Her research areas include power system modeling and simulations, real-time digital simulations, power system stability,

Ngày tải lên: 22/06/2014, 23:20

... If we could make a neural network model which has the same capability for pattern recognition as a human being, it would give us a powerful clue to the understanding of the neural mechanism ... ability for pattern recognition was not so high. In this paper, we propose an improved neural network model. The structure of this network has been suggested by that of the visual nervous system ... Kinuta, Setagaya, Tokyo, Japan Abstract. A neural network model for a mechanism of visual pattern recognition is proposed in this paper. The network is self-organized by "learning without

Ngày tải lên: 08/07/2014, 17:02

... Developing neural network applications, Al Expert, 34-41 Curak Marijana, Klime Pososki & Curk Ivan, Forecasting economic growth using financial variables- Comparision of linear regression and neural network ... Signals Systems, 2, 303-314 Greg Tkacz (2001), Neural Network Forecasting of Canada GDP Growth, International journal of Forcasting, 17, 57-69 Guoqiang Zhang, B.Eddy Patuwo & Micheal Y.Hu, Forecasting ... Meural Networks and Principal Component Analysis: Learning from Examples without Local Minima, Neural Network, 2, 53 58 15 Pengyi Shi, Zhuo Chen & Gaungming Xie (2006), Using Artificial neural network

Ngày tải lên: 24/11/2014, 01:42

... systems Another area of work that may be conducted is to develop an Elman network based fault tolerant scheme for MIMO systems For MIMO systems which have only linear coupling, a MISO Elman network ... algorithm for on-line training of recurrent network trajectories Neural Computation 2, 490–501 Xuemei, Ren and Fei Shumin (2000) Recurrent neural networks for identification of nonlinear systems ... by neural network the type of neural network as well as the training algorithm should be chosen carefully The type of neural network in Figure 2.1 can be a MLP, a Radial Basis Networks

Ngày tải lên: 26/11/2015, 22:57