Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/468735
Title: An optimization framework for Weather forecast prediction and Analysis
Researcher: Krishnaveni, N
Guide(s): Padma, A
Keywords: Engineering and Technology
Computer Science
Computer Science Information Systems
prediction and Analysis
Weather forecast
optimization framework
University: Anna University
Completed Date: 2021
Abstract: Weather forecasting is an emerging domain that predicts the weather condition at a particular time and location. Weather forecasting is considered one of the most sensitive research fields which facing a lot of real-time issues such as inaccurate prediction, lack of handling huge data volume and inadequate technology advancement. newlineEven after the technological and scientific development, the accuracy in forecasting weather has never been satisfactory. Even at present, this domain remains as an area of research in which experts and statisticians are working to produce a model or an algorithm that predicts weather accurately. There have been huge enhancements in the sensors which are responsible for recording the data from the atmosphere and removes the noise present in them. This innovative models which contain different attributes related to weather have been recommended to make a precise prediction. newlineData mining is one of the most extensively used techniques for forecasting weather at present. Data mining can be used for predictions by analyzing data and extracting rules statistically. Currently, it is being used in many fields such as disease prediction, stock market, banking sector etc. Researchers have now understood that data mining can be used as a tool for forecasting weather as well. A decision tree is one of the most influential and extensively used techniques for classification and prediction. newlineDecision Tree Mining is a category of data mining technique that is used to construct classification models. A decision tree is a classification algorithm which is used regularly and has an easy structure to clarify. Decision Tree converts a huge fact into a decision tree based on rules.SPRINT(Scalable Parallelizable Introduction of Classification Tree) is a usual decision-tree-based classification algorithm in which decision trees are built in a top-down recursive divide-and-conquer manner by adapting a greedy approach. newline
Pagination: xiii,112p.
URI: http://hdl.handle.net/10603/468735
Appears in Departments:Faculty of Information and Communication Engineering

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02_prelim pages.pdf2.17 MBAdobe PDFView/Open
03_content.pdf13.86 kBAdobe PDFView/Open
04_abstract.pdf10.16 kBAdobe PDFView/Open
05_chapter 1.pdf844.94 kBAdobe PDFView/Open
06_chapter 2.pdf965.37 kBAdobe PDFView/Open
07_chapter 3.pdf696.58 kBAdobe PDFView/Open
08_chapter 4.pdf776.61 kBAdobe PDFView/Open
09_chapter 5.pdf1.06 MBAdobe PDFView/Open
10_annexures.pdf149.37 kBAdobe PDFView/Open
80_recommendation.pdf79.89 kBAdobe PDFView/Open
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