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AUTOCONFIGURING ARTIFICIAL NEURAL NETWORK APPLIED TO FAULT DIAGNOSIS IN POWER SYSTEMS


Posted by: computer science technology
Created at: Sunday 24th of January 2010 06:39:12 AM
Last Edited Or Replied at :Monday 06th of February 2012 12:24:21 AM
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iv. Learning phase: adjust weight and bias accordingly using
perceptron learning rule.
FOR POWER SYSTEM 1:
The input layer of the neural network contains informations about the
above mentioned 10 circuit breakers and 9 protective relays.
The input layers are (from the left):
CB1, CB2, CB3, CB4, CB5, CB6, CB7, CB8, CB9,
CB10,LIM,LIB,L2M,L2B,L3M,L3B,L4M,L4B,L5M,L5B,T1M,T2M,X1B, X2B
Where:
CB*=circuit breaker
L*M=main relay associated with line
L*B=back up relay associated with line
T*M=main relay associated with transformer
X*=main relay associated with bus
The possible faul..................[:=> Show Contents <=:]



TACTILE SENSING SYSTEM USING ARTIFICIAL NEURAL NETWORKS full report


Posted by: computer science technology
Created at: Sunday 24th of January 2010 04:06:02 AM
Last Edited Or Replied at :Sunday 24th of January 2010 04:06:02 AM
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having moments with change in the position, size and orientation of the objects. The trained network was linked with the momentâ„¢s module and derived moments were input to the neural network. Target pattern was set at less than 0.5 for output not belonging to the class and greater than 0.5 for correct class.

For this experiment the position of the object is varied over the array of the sensor. And the moments were calculated for the same object. Then the network was trained with the help of three sets of data by varying its position. Then was observed that network was..................[:=> Show Contents <=:]



cellular neural networks


Posted by: electronics seminars
Created at: Monday 28th of December 2009 05:07:40 AM
Last Edited Or Replied at :Monday 02nd of May 2011 03:07:21 AM
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lizes a pair of series connected r.t.d's & one transistor to store one bit by exploiting the two stable equilibrium states of r.t.d. the one t s-ram cell exhibits excellent high frequency characteristics with cutoff frequency and maximum frequency of oscillation over 100 GHz . recently another approach based on a slew rate based accessing method has been reported which allows to store and access n bits in a series connection of n vertically integrated r.t.ds. The q writes FET works as a variable resistor whose value is set by the voltage in the word line. The bit line is activated with a st..................[:=> Show Contents <=:]



Digit Recognition using Neural Network


Posted by: Electrical Fan
Created at: Saturday 14th of November 2009 05:33:37 AM
Last Edited Or Replied at :Thursday 19th of January 2012 10:33:35 PM
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tion is the process of recognizing and classifying handwritten digits without human interaction. Its application field is very wide, for example Postal code recognition (Automatic sorting of mail by destination ZIP code), Digitizing hand written spreadsheets, tax forms etc. Patterns slightly shifted, distorted and even overwritten can be correctly recognized. Neural network aids in efficient recognition. A Multilayer Neural network trained with Backpropagation algorithm is used. Kirsch masks are adopted for extracting feature vectors and a multy layer clustered neural network is used for class..................[:=> Show Contents <=:]



Face Recognition Using Artificial Neural Networks


Posted by: nit_cal
Created at: Saturday 31st of October 2009 04:58:30 AM
Last Edited Or Replied at :Saturday 20th of April 2013 12:55:41 AM
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its experiential knowledge next time. This biologically inspired method is being touted as the wave of the future in computing, relieving the programmer from the cubicle of traditional algorithmic pro..................[:=> Show Contents <=:]



Emerging Trends In Robotics Downlaod Seminar Report


Posted by: Computer Science Clay
Created at: Thursday 30th of July 2009 06:46:58 AM
Last Edited Or Replied at :Thursday 30th of July 2009 06:46:58 AM
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Continuous-path servo-controlled robots..................[:=> Show Contents <=:]



Cellular Neural Network


Posted by: Computer Science Clay
Created at: Tuesday 24th of February 2009 12:56:26 PM
Last Edited Or Replied at :Sunday 21st of November 2010 10:46:10 PM
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coordinates (i,j) i=1,2¦..M, j=12¦...N.

A class -1 m*n standard CNN is defined by a m*n rectangular array of cells cij located at site (i,j) i= 1,2 ¦¦.m ,j=1,2,¦.n is defined mathematically by
(dXij/dt )= -Xij + A(I,j,k,l) Ykl + B(i,j,k,l) + Zij..................[:=> Show Contents <=:]



Industrial Applications using Neural Networks


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:08:04 AM
Last Edited Or Replied at :Thursday 05th of August 2010 12:43:13 PM
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mple, the model can be incorporated within a model based predictive control (MBPC) algorithm, such as Generalised Predictive Control.

Alternatively, for process monitoring, the residuals (prediction errors) from such models can be analyzed to detect abnormal operation. Such monitoring and control schemes have found widespread application in industry and have led to significant improvements in process operations. Unfortunately, the models employed within the schemes tend to be linear in form. Although linear models can provide acceptable performance for many systems, they may be unsuitable i..................[:=> Show Contents <=:]



Transient Stability Assessment using Neural Networks


Posted by: computer science crazy
Created at: Monday 22nd of September 2008 12:07:56 AM
Last Edited Or Replied at :Tuesday 19th of October 2010 05:02:49 AM
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x) such that s(x) = { >=0 for a secure x) {<=0 for an insecure x)
this function is called a classifier, at once the classifier obtained, for sample x one can classify the sample as stable or unstable very rapidly. The most important task in the application of pattern recognition is the selection of primary variables because the lower limit for the classification error depends on the primary variables.

Draw backs of conventional methods
1. The online transient stability assessment of the electrical power systems is an extremely difficult task with the available techniques.
2. Each contin..................[:=> Show Contents <=:]



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