Supervised Rainfall Learning Model Using Machine Learning Algorithms

被引：5
|
作者：
Sharma, Amit Kumar [1 ]
Chaurasia, Sandeep [1 ]
Srivastava, Devesh Kumar [1 ]
机构：
[1] Manipal Univ, Jaipur, Rajasthan, India
来源：
INTERNATIONAL CONFERENCE ON ADVANCED MACHINE LEARNING TECHNOLOGIES AND APPLICATIONS (AMLTA2018) | 2018年 / 723卷
关键词：
Supervised learning; Normalization; Mean Thresholds; Rainfall dataset; Feature selection; Machine learning; Naive Bayes; Random forest; MLP; SMO;
D O I：
10.1007/978-3-319-74690-6_27
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Unpredictable and uncertain volume of the rainfall is the serious nature disaster. In current, available rainfall forecasting model predict rainfall volume hourly, weekly or monthly. This work proposed a supervised learning model which is based on machine leaning algorithms of data mining. This approach classify the low, mid and high volume of rainfall. Proposed approach is practically implemented on different uncertain heavy rainfall regions and compare the accuracy and measured the accuracy by ROC area of classifiers such as Random Forest, SMO, Naive Bayes and Multilayer Perceptron (MLP).
引用
收藏
页码：275 / 283
页数：9
相关论文
共 50 条
  • [1] Protostellar classification using supervised machine learning algorithms
    Miettinen, O.
    [J]. ASTROPHYSICS AND SPACE SCIENCE, 2018, 363 (09)
  • [2] Protostellar classification using supervised machine learning algorithms
    O. Miettinen
    [J]. Astrophysics and Space Science, 2018, 363
  • [3] A Review of Supervised Machine Learning Algorithms
    Singh, Amanpreet
    Thakur, Narina
    Sharma, Aakanksha
    [J]. PROCEEDINGS OF THE 10TH INDIACOM - 2016 3RD INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT, 2016, : 1310 - 1315
  • [4] Prediction of Cardiac Disease using Supervised Machine Learning Algorithms
    Princy, R. Jane Preetha
    Parthasarathy, Saravanan
    Jose, P. Subha Hency
    Lakshminarayanan, Arun Raj
    Jeganathan, Selvaprabu
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS 2020), 2020, : 570 - 575
  • [5] Predicting cash holdings using supervised machine learning algorithms
    Şirin Özlem
    Omer Faruk Tan
    [J]. Financial Innovation, 8
  • [6] SMS Spam Filtering using Supervised Machine Learning Algorithms
    Navaney, Pavas
    Dubey, Gaurav
    Rana, Ajay
    [J]. PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE CONFLUENCE 2018 ON CLOUD COMPUTING, DATA SCIENCE AND ENGINEERING, 2018, : 43 - 48
  • [7] Text Message Classification Using Supervised Machine Learning Algorithms
    Merugu, Suresh
    Reddy, M. Chandra Shekhar
    Goyal, Ekansh
    Piplani, Lakshay
    [J]. ICCCE 2018, 2019, 500 : 141 - 150
  • [8] Predicting cash holdings using supervised machine learning algorithms
    Ozlem, Sirin
    Tan, Omer Faruk
    [J]. FINANCIAL INNOVATION, 2022, 8 (01)
  • [9] Cryptocurrency Price Prediction Using Supervised Machine Learning Algorithms
    Chaudhary, Divya
    Saroj, Sushil Kumar
    [J]. ADCAIJ-ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2023, 12 (01):
  • [10] Supervised prediction of production patterns using machine learning algorithms
    Kim, Jungyeon
    [J]. LINGUISTICS VANGUARD, 2024,
12345