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Delhi Weather Analysis : A Mongo Db Approach

Aliya A. Kazi1 , Shifa Shaikh2 , Shahbaj Shaikh3 , Shakila Shaikh4

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-10 , Page no. 156-158, Oct-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i10.156158

Online published on Oct 31, 2019

Copyright © Aliya A. Kazi, Shifa Shaikh, Shahbaj Shaikh, Shakila Shaikh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Aliya A. Kazi, Shifa Shaikh, Shahbaj Shaikh, Shakila Shaikh, “Delhi Weather Analysis : A Mongo Db Approach,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.10, pp.156-158, 2019.

MLA Style Citation: Aliya A. Kazi, Shifa Shaikh, Shahbaj Shaikh, Shakila Shaikh "Delhi Weather Analysis : A Mongo Db Approach." International Journal of Computer Sciences and Engineering 7.10 (2019): 156-158.

APA Style Citation: Aliya A. Kazi, Shifa Shaikh, Shahbaj Shaikh, Shakila Shaikh, (2019). Delhi Weather Analysis : A Mongo Db Approach. International Journal of Computer Sciences and Engineering, 7(10), 156-158.

BibTex Style Citation:
@article{Kazi_2019,
author = {Aliya A. Kazi, Shifa Shaikh, Shahbaj Shaikh, Shakila Shaikh},
title = {Delhi Weather Analysis : A Mongo Db Approach},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2019},
volume = {7},
Issue = {10},
month = {10},
year = {2019},
issn = {2347-2693},
pages = {156-158},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4912},
doi = {https://doi.org/10.26438/ijcse/v7i10.156158}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i10.156158}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4912
TI - Delhi Weather Analysis : A Mongo Db Approach
T2 - International Journal of Computer Sciences and Engineering
AU - Aliya A. Kazi, Shifa Shaikh, Shahbaj Shaikh, Shakila Shaikh
PY - 2019
DA - 2019/10/31
PB - IJCSE, Indore, INDIA
SP - 156-158
IS - 10
VL - 7
SN - 2347-2693
ER -

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Abstract

The application of science and technology in predicting the weather of a given area is weather forecasting. The whole world is experiencing extreme climatic change which causes side effects .In order to reduce these side effects we use mathematical algorithms and techniques on big data of weather data to analyse the current situation and predict the future weather conditions. In this research we will use be using Mongo DB to analyse the data on weather in Delhi. The outcomes shows us the analysis of the weather data available.

Key-Words / Index Term

MongoDb, Weather, Analysis, Queries

References

[1] Garima Jain1 , Bhawna Mallick2 Student, “A Review on Weather Forecasting Techniques”, International Journal of Advanced Research in Computer and Communication Engineering ISO 3297:2007 Certified Vol. 5, Issue 12, December 2016 Department of Computer Science and Engineering, Galgotias Educational Institutions, Greater Noida, Uttar Pradesh, India1 Head of Department (Computer Science), Galgotias Educational Institutions, Greater Noida, Uttar Pradesh, India.
[2] Sushmitha Kothapalli, S. G. Totad, “A Real-Time Weather Forecasting and Analysis”, IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI-2017), pp 1567- 1570
[3] Tiwari, R. Sam and S. Shaikh, "Analysis and prediction of churn customers for telecommunication industry," 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, 2017, pp. 218-222. doi: 10.1109/I-SMAC.2017.8058343
[4] S. Navadia, P. Yadav, J. Thomas and S. Shaikh, "Weather prediction: A novel approach for measuring and analyzing weather data," 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, 2017, pp. 414-417. doi: 10.1109/I-SMAC.2017.8058382
[5] S. Shaikh, S. Rathi and P. Janrao, "IRuSL: Image Recommendation Using Semantic Link," 2016 8th International Conference on Computational Intelligence and Communication Networks (CICN), Tehri, 2016, pp. 305-308. doi: 10.1109/CICN.2016.66
[6] S. Shaikh, S. Rathi and P. Janrao, "Recommendation System in E-Commerce Websites: A Graph Based Approached," 2017 IEEE 7th International Advance Computing Conference (IACC), Hyderabad, 2017, pp. 931-934. doi: 10.1109/IACC.2017.0189
[7] Farhad Soleimanian Gharehchopogh, Tahmineh Haddadi Bonaband Seyyed Reza Khaze, “ A linear regression approach to prediction of stock market trading volume: a case study” Vol.4, No. 3, September 2013, International Journal of Managing Value and Supply Chains (IJMVSC).
[8] Behrouz Minaei-Bidgoli, Deborah A. Kashy, Gerd Kortemeyer , William F. Punch, “Predicting student performance: an application of data mining methods with the educational web-based system lon-capa”, November 5- 8, 2003, Boulder, CO 33rd ASEE/IEEE Frontiers in Education Conference,ISSN: 0-7803-7444-4/03/$17.00
[9] Ranzato , M., Y., Boureau, 1.., Chopra, S., &LeCun, Y. "A unified energy-based framework for unsupervised learning," In Proc.Conference on AI and Statistics (AIStats), vol. 20, 2007.
[10] Linkon Chowdhury , Md.Sarwar Kamal & Sonia Farhana Nimmy, “Artificial System to Compare Energy Status in the Context of Europe Middle East”, Global Journal of Computer Science and Technology Volume 12 Issue 8 Version 1.0 ,April 2012, pp25-30
[11] Han, J., Kamber, M.: “Data Mining Concepts and Techniques”, Morgan Kaufmann Publishers, 2006.
[12] A. aGautm and P. Bedi, "MR-VSM: Map Reduce based vector SpaceModel for user profiling-an empirical study on News data," 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Kochi, 2015, pp. 355-360.
[13] Agrawal, R., Jain, R.C., Jha, M.P. and Singh, D. (1980): Forecasting of rice yield using climatic variables. Indian Journal of Agricultural Science, Vol. 50, No. 9, pp. 680-684.
[14] Lee, S., Cho, S.& Wong, P.M., (1999) : Rainfall prediction using artificial neural network.― J. Geog. Inf. Decision Anal. 2, 233–242 1998. [10] Wong, K. W., Wong, P. M., Gedeon, T. D. & Fung, C. C. ―Rainfall Prediction Using Neural Fuzzy Technique.
[15] C. Hamzacebi, “Improving artificial neural networks’ performance in seasonal time Series Forecasting”, Information Sciences 178 (2008), pages: 4550-4559.