Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/367912
Title: Development of Improved Clustering Protocol to Enhance the Lifetime of Wireless Sensor Network
Researcher: Rani, Uma
Guide(s): DAlal, Surjeet
Keywords: Computer Science
Computer Science Artificial Intelligence
Engineering and Technology
University: SRM University, Delhi-NCR, Sonepat
Completed Date: 2021
Abstract: The traditional Decision support system has studied that concludes the existing system do not work upon the fuzzy inherent as in human thinking. Moreover, the decision support system used before human dependent. All the limits of the function were defined by the humans who might be error prone eventually and produces less efficient results. Decision making by use of traditional methods were complicated as well as difficult to evaluate due to which computer based information systems are proposed where decision making activities becomes simple. Decision support systems are useful in making decisions in different forms as they analyse issues in semi structured and in structured form. Gradually it has been started using in small subset of the available data which was helpful for small business. Regarding its various benefits to businesses it becomes prominent field of information processing and technology databases. Fuzzy logic has been used by various applications to get optimized results but in certain cases it may not be as reliable as required. In such case fuzzy logic has to be optimized before getting an optimum solution to the problem. The fuzzy decision support system has initialized where three different components are involved. Each component in the system is self-dependent. Consequently, the evaluation of each component s rating is not relying on the other component. Moreover, it includes multiparameters for interpretation of rating. After getting each component s rating, it has optimized through firefly optimization algorithm. Before optimization the acquired rating value was minor and the performance of the system was degraded. Alternatively, optimization has applied over each component s rating value and rating value has increased so is the performance of the system. Furthermore, the hierarchical approach is applied where proposed system works in levels. At each level, an output has produced and correspondingly this output has become the input for the next level. For the achievement of the proposed work
Pagination: xiii, 162
URI: http://hdl.handle.net/10603/367912
Appears in Departments:Library

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03_cartificate.pdf53.09 kBAdobe PDFView/Open
04_abstract.pdf215.79 kBAdobe PDFView/Open
05_acknowledgement.pdf211.74 kBAdobe PDFView/Open
06_contents.pdf227.14 kBAdobe PDFView/Open
07_list of tables.pdf211.74 kBAdobe PDFView/Open
08_list of figures.pdf224.56 kBAdobe PDFView/Open
09_list of abbreviations.pdf225.03 kBAdobe PDFView/Open
10_chapter 1.pdf1.07 MBAdobe PDFView/Open
11_chapter 2.pdf602.43 kBAdobe PDFView/Open
12_chapter 3.pdf585.05 kBAdobe PDFView/Open
13_chapter 4.pdf1.18 MBAdobe PDFView/Open
14_chapter 5.pdf985.02 kBAdobe PDFView/Open
15_chapter 6.pdf384.19 kBAdobe PDFView/Open
16_reference.pdf926.55 kBAdobe PDFView/Open
2_declaration.pdf53.5 kBAdobe PDFView/Open
80_recommendation.pdf618.98 kBAdobe PDFView/Open
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