Data Mining using Neural Networks

MAZIN OMAR KHAIRO

Management of Information Technology Department, Umm Al-Qura University, Saudi Arabia

ABSTRACT:

While the current IT plethora is replicating enormous data and it need to have tremendous
processing power by the servers to maintain this valuable data and storages. Therefore in order
to provide ease to data storage Erasure coding exhibits much success in the area of data mining
as it can reduce the space and bandwidth overheads of redundancy in fault-tolerance delivery
systems, so the exploration of erasure coding in concurrency with the metadata will be appreciable;
Research also on the other side of the coin shows as few have analyzed the understanding of
consistent hashing too will proved productive for certain related issues and also the neural
networks can be used for maintaining and exploring new data sciences in order to provide
encouraging frameworks in managing infinite volumes of data we have at our disposal. In this
work, we prove the visualization of simulated annealing in order to render solution at global
maxima and provide provision of improvements to the specified framework or model. We also
analyzed and state the disconfirmation about the fact that write-back caches and neural networks
are never incompatible

KEYWORDS: Neural networks; IT Plethora; Data

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