Analysis of Remote Sensed Data Using Neuro- Fuzzy Algorithm: A Case Study of Hyderabad Region

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Hari Kumar Singh, Ajay Yadav,Atul Katiyar


In this paper we are presenting the Estimation of space in Hyderabad using Neuro
Fuzzy approach in Digital image processing. Digital image processing is the science of
manipulation of an image by means of a processor. The advantage of combining neural networks
with fuzzy logic is that, it is better in noisy environment as picture not to do and it has fault
tolerance capability better than individual approach, so we are working for a better result using
this approach in image processing.
Every intelligent technique has particular computational properties (e.g. ability to learn,
explanation of decisions) that make them suited for particular problems and not for others. For
example, while neural networks are good at recognizing patterns, they are not good at explaining
how they reach their decisions. Fuzzy logic systems, which can reason with imprecise
information, are good at explaining their decisions but they cannot automatically acquire the rules
they use to make those decisions. Hybrid systems are also important when considering the varied
nature of application domains. Many complex domains have many different component problems,
each of which may require different types of processing. Fuzzy logic provides an inference
mechanism under cognitive uncertainty,computational neural networks offer exciting advantages,
such as learning, adaptation, fault-tolerance, parallelism and generalization.


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How to Cite
Hari Kumar Singh, Ajay Yadav,Atul Katiyar. (2021). Analysis of Remote Sensed Data Using Neuro- Fuzzy Algorithm: A Case Study of Hyderabad Region. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 9(1), 181–190.
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