• Corpus ID: 32987554

Big Data Weather Analytics Using Hadoop

  title={Big Data Weather Analytics Using Hadoop},
  author={Veershetty Dagade and Mahesh Lagali and S. Avadhani and Priya Kalekar}
Big Data Technique for the Weather Prediction using Hadoop MapReduce
This paper focuses on analyzing the weather dataset using Hadoop/MapReduce and the historical dataset from NOAA, and the temperature, humidity and visibility attributes has been extracted from the dataset by the MapReduce Algorithm into structure data.
For the efficient feature selection in the Hadoop framework, a new feature selection algorithm has been suggestedrelation based Feature Selection (CFS), Genetic Algorithm (GA) and Honey Bee Mating Optimization (HBMO) algorithm, which helps in decreasing the problem dimension and noise and improvising the algorithm speed by the removal of irrelevant or superfluous features.
Big Data Prediction Framework for Weather Temperature
This project aims to build analytical Big Data prediction framework for weather temperature based on MapReduce algorithm and can perform administered grouping methodology on immense measures of information on a conveyed framework utilizing Hadoop Map Reduce.
Big Data Analytics Implementation In Banking Industry – Case Study Cross Selling Activity In Indonesia’s Commercial Bank
This paper aims to create a design of big data analytics application architecture, suitable business rule and model for cross selling analysis in the Bank, leveraging Cloudera Hadoop, Aster Analytics, TeraData RDMS, and tableau for data visualization to perform cross selling analytics.
An Adaptive Model for Forecasting Seasonal Rainfall Using Predictive Analytics
  • P. Reddy, A. Sureshbabu
  • Environmental Science
    International Journal of Intelligent Engineering and Systems
  • 2019
India is a country which has exemplary climate circumstances comprising of different seasons and topographical conditions like high temperatures, cold atmosphere, and drought, heavy rainfall seasonal
Weather Data Analysis Using Hadoop: Applications and Challenges
A system that uses the historical weather data of a region and applies the MapReduce and Hadoop techniques to analysis these historical data to solve the huge challenge of storing and processing big data for accurate weather prediction.
Multi-dimensional geospatial data mining in a distributed environment using MapReduce
The results from the proposed platform were found to be better and are also available faster due to application of distributed processing, and a novel technique of transforming the spectral space to the geometrical space is also proposed.
Novel Weather Data Analysis Using Hadoop and MapReduce – A Case Study
A system that adopts the historical weather data of a region is developed that applies the MapReduce and Hadoop methods to analyze this data.
Distributed Web Usage Mining Based Recommender System in Big Data Analytics using Hybrid Firefly Algorithm
This work hybridized a nature inspired, meta heuristic algorithms Firefly and Teaching Learning Based Optimization (FA-TLBO) using the K-Means algorithm to obtain optimal cluster centres and indicated the fact that novel FA- TLBO with K-means was more efficient compared to TLBO algorithm.
Comprehensive Analysis of Big Data Tools
This paper discusses some focused challenges of big data along with some basic big data tools and techniques, and compares all the tools to demonstrate that which big data tool is better for big data analysis and visualization.