Analysis of weather data using various regression algorithms

被引:0
|
作者
Jahnavi, Yeturu [1 ]
机构
[1] Department of Computer Science and Engineering, Geethanjali Institute of Science and Technology, Andhra Pradesh, Nellore,524137, India
关键词
Multilayer neural networks - Weather forecasting - Support vector machines - Regression analysis - Atmospheric humidity - Errors - Mean square error - Meteorology;
D O I
10.1504/IJDS.2019.100321
中图分类号
学科分类号
摘要
Weather forecasting is a vital application in meteorology and has been one of the most challenging problems around the world. Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predictions. This is carried out using several regression algorithms. This paper focuses on weather analysis using various regression algorithms in data mining. In this work, linear regression, classification and regression tree, multilayer perceptron neural network and support vector machine (SVM) are used. For weather analysis various primary atmospheric parameters such as average temperature, average pressure and relative humidity are considered. The performance is analysed using various evaluation measures. Evaluation criteria like root mean square error, mean absolute error, relative absolute error and root relative square error are used for measuring the performance of regression algorithms. Copyright © 2020 Inderscience Enterprises Ltd.
引用
下载
收藏
页码:117 / 141
相关论文
共 50 条
  • [41] Mars weather data analysis using machine learning techniques
    Ishaani Priyadarshini
    Vikram Puri
    Earth Science Informatics, 2021, 14 : 1885 - 1898
  • [42] Analysis of Crash Data Using Quantile Regression for Counts
    Wu, H.
    Gao, L.
    Zhang, Z.
    JOURNAL OF TRANSPORTATION ENGINEERING, 2014, 140 (04)
  • [43] Accelerated Lifetime Data Analysis Using Quantile Regression
    Roh, Chee Youn
    Kim, Heejeong
    Na, Myung Hwan
    KOREAN JOURNAL OF APPLIED STATISTICS, 2008, 21 (04) : 631 - 638
  • [44] Using smiulated data in support of research on regression analysis
    Hill, CM
    Malone, LC
    PROCEEDINGS OF THE 2004 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2004, : 967 - 973
  • [45] Comparative investigation of Source Term Estimation algorithms using FUSION field trial 2007 data: linear regression analysis
    Platt, Nathan
    DeRiggi, Dennis
    INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION, 2012, 48 (1-4) : 13 - 21
  • [46] Classification and prediction of student performance data using various machine learning algorithms
    Pallathadka H.
    Wenda A.
    Ramirez-Asís E.
    Asís-López M.
    Flores-Albornoz J.
    Phasinam K.
    Materials Today: Proceedings, 2023, 80 : 3782 - 3785
  • [47] Analysis of breast cancer event logs using various regression techniques
    Saravanan, M. S.
    Patil, Pradnya
    Subbaiah, K. Venkata
    2021 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI), 2021,
  • [48] Quantile regression using metaheuristic algorithms
    Rahman, Mohammad Arshad
    INTERNATIONAL JOURNAL OF COMPUTATIONAL ECONOMICS AND ECONOMETRICS, 2013, 3 (3-4) : 205 - 233
  • [49] REGRESSION CALCULUS USING SIMPLEX ALGORITHMS
    ZORILESC.D
    REVUE FRANCAISE D INFORMATIQUE DE RECHERCHE OPERATIONNELLE, 1969, 3 (NV2): : 113 - &
  • [50] Potentiometric and economic analysis of using air and water-side economizers for data center cooling based on various weather conditions
    Deymi-Dashtebayaz, Mahdi
    Namanlo, Sajad Valipour
    INTERNATIONAL JOURNAL OF REFRIGERATION, 2019, 99 : 213 - 225