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## Use of A algorithm for obstacle avoidancePosted by: nit_cal Created at: Friday 30th of October 2009 05:56:55 AM Last Edited Or Replied at :Friday 30th of October 2009 05:56:55 AM | hc12 obstacle avoidance code ,
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me, if h(n) is very high relative to g(n), then only h(n) plays a role, and A* turns into BFS. So we have an interesting situation in that we can decide what we want to get out of A*. At exactly the right point, we'll get shortest paths really quickly. If we're too low, then we'll continue to get shortest paths, but it'll slow down. If we're Loo high, then we give up shortest paths, but A* will run faster.In a game, this property of A* can be very useful. For example, we may find that in some situations, we would rather have a good path than a perfect path. To shift the balance between g(.................. [:=> Show Contents <=:] | |||

## GENETIC PROGRAMMING A SEMINAR REPORTPosted by: Computer Science Clay Created at: Saturday 13th of June 2009 03:13:46 PM Last Edited Or Replied at :Tuesday 28th of February 2012 10:05:49 PM | genetic programming code ,
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single best program in the population produced during the run (the best-so-far individual) is
harvested and designated as the result of the run. If the run is successful, the result may be a
solution (or approximate solution) to the problem. 4.3 EXAMPLES OF GP Â¢ Symbolic regression - is the process of discovering both the functional form of a target function and all of its necessary coefficients, or at least an approximation to these. This is distinct from other forms of regression such as polynomial regression in which you are merely trying to find the coefficients of a polynomial of a.................. [:=> Show Contents <=:] | |||

## Securing the Network Routing Algorithms Download Full Seminar ReportPosted by: computer science crazy Created at: Thursday 09th of April 2009 02:28:25 AM Last Edited Or Replied at :Thursday 09th of April 2009 02:28:25 AM | crossbar network routing algorithm,
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ir general working and the various security problems, which th..................[:=> Show Contents <=:] | |||

## Self Organizing MapsPosted by: computer science crazy Created at: Wednesday 08th of April 2009 12:13:21 AM Last Edited Or Replied at :Wednesday 08th of April 2009 12:13:21 AM | signature recognition using self organizing map algorithm ,
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ubsequent information, in a much reduced fashion. We will know which information is more likely.
This black box will certainly have learned. It may permit us to perceive some order in what
otherwise was a mass of unrelated information to see the wood for the trees. In any learning system, we need to make full use of the all the available data and to impose any constrains that we feel are justified. If we know that what groups the information must fall into, that certain combinations of inputs preclude others, or that certain rules underlie the production of the information then we must use .................. [:=> Show Contents <=:] | |||

## WEB MININGPosted by: seminar projects crazy Created at: Friday 30th of January 2009 01:22:16 PM Last Edited Or Replied at :Saturday 16th of February 2013 12:13:10 AM | web mining business value ,
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n rise to the interest in Text Mining methods for modeling documents in terms of properties of
documents. Learning from the hyperlink structure has given rise to graph-based methods, and server
logs are used to learn about user behavior. Instead of searching for a document that matches keywords, it should be possible to combine information to answer questions. Instead of retrieving a plan for a trip to Hawaii, it should be possible to automatically construct a travel plan that satisfies certain goals and uses opportunities that arise dynamically. This gives rise to a wide range of challenge.................. [:=> Show Contents <=:] | |||

## HEURISTIC ALGORITHM FOR CLIQUE PROBLEMPosted by: seminar projects crazy Created at: Friday 30th of January 2009 12:13:43 PM Last Edited Or Replied at :Friday 30th of January 2009 12:13:43 PM | algorithms analysis ,
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ms. No polynomial-time algorithm has yet been discovered for an NP-Complete problem, nor has any one
yet been able to prove a superpolynomial-time lower bound for any of them. This so called whether P
? NP question has been one of the deepest, most perplexin..................[:=> Show Contents <=:] | |||

## Fast Convergence Algorithms for Active Noise Controlin VehiclesPosted by: computer science crazy Created at: Sunday 21st of September 2008 11:57:31 PM Last Edited Or Replied at :Sunday 21st of September 2008 11:57:31 PM | algorithms and flowcharting ,
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orthogonalization of the input signal.An ALP structure, with the acoustic reference has input
signal, before a FxLMS makes up the FxGAL algorithm. Due to the orthogonalization, FxGAL can be
significantly faster compared to FxLMS with reference from a microphone. When compared to FxLMS with
tachometer signal, it is not faster but it can cancel every periodic noise, independently of the
harmonical relation between them, as well as the underlined broad band noise. INTRODUCTION The Filtered-x Least Mean Square (FxLMS) algorithm(1) is the most widely used in the context of adaptive active cont.................. [:=> Show Contents <=:] | |||

## Neural Networks And Their ApplicationsPosted by: computer science crazy Created at: Sunday 21st of September 2008 11:28:39 PM Last Edited Or Replied at :Sunday 21st of September 2008 11:28:39 PM | an introduction to neural networks gurney,
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ical nervous systems, such as the brain, process information. The key element of this paradigm is
the novel structure of the information processing system. It is composed of a large number of highly
interconnected processing elements (neurons) working in unison to solve specific problems. ANNs,
like people, learn by example. An ANN is configured for a specific application, such as pattern
recognition or data classification, through a learning process. Learning in biological systems
involves adjustments to the synaptic connections that exist between the neurons. This is true of
ANNs as well. .................. [:=> Show Contents <=:] |

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