Hybrid Prediction Models For Rainfall Forecasting

Hybrid Prediction Models For Rainfall Forecasting

₹4,000.00
Product Code: Python
Availability: In Stock
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Product Description

Aim:

Analyze the rainfall data from database for rainfall prediction.

Synopsis:                          

In recent years countries like United States of America, Japan, China, Taiwan etc, were suffering from extreme and dangerous natural disasters due to impact of climate. The flood is one of the main reasons for the damages caused in the Asian countries like, India, Bangladesh, Sri Lanka, China etc. These floods increase the risk of death by 75%. The advancement in the information technology, the need for easy accessibility of large cloud storage and processing power is available. Data mining technologies helps us to provide reference for decision makers as summarized information even from the large amount of data. Among many data mining techniques, classification is a widely used one. Past studies proposed many techniques that could be applied to classification, such as decision trees, neural networks, Bayesian classifiers, support vector machines.

Proposed System:

To overcome the fallback in the existing system we propose a machine learning based system to increase the efficiency and accuracy. To handle voluminous data we are using Hadoop to store and retrieve data from the distributed hadoop file system (hdfs).  Hadoop allows the user to load data into a cluster. Random forest algorithm is to be implemented for forecasting rainfall.

Modules:

  •         Data collection and pre-processing
  •         Random Forest model generation
  •         Prediction, result presentation

Software Requirement:

         Operating System                   : Windows 7 and above (64-bit).

         Python                                     : 3.6

         Java                                         : Jdk1.8

Hardware Requirement:

         Hard disk                                : 500 GB and above.

         Processor                                 : i3 and above.

         Ram                                         : 4GB and above.

Technologies used:

  •                    Random forest 

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.