Finding ideal geographical location for businesses using machine learning technique

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Sonraí bibleagrafaíochta
Príomhchruthaitheoirí:	Mahmud, Mir Ibtid, Chowdhury, Onez, Alvee, Yashwant, Sadman, Tawsif, Shaon, Imrul Haque
Rannpháirtithe:	Ashraf, Faisal Bin
Formáid:	Tráchtas
Teanga:	English
Foilsithe / Cruthaithe:	Brac University 2022
Ábhair:	Data analysis Geo analytics Decision tree Linear regression analysis K-Means clustering Machine learning
Rochtain ar líne:	http://hdl.handle.net/10361/15860

id	10361-15860
record_format	dspace
spelling	10361-158602022-01-26T10:21:47Z Finding ideal geographical location for businesses using machine learning technique Mahmud, Mir Ibtid Chowdhury, Onez Alvee, Yashwant Sadman, Tawsif Shaon, Imrul Haque Ashraf, Faisal Bin Department of Computer Science and Engineering, Brac University Data analysis Geo analytics Decision tree Linear regression analysis K-Means clustering Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 43-44). The world has become a place where the economy is at the epicenter of it all. World economic growth has paved the way for people to enrich their lives with all sorts of blessings. A major chunk of this shift in the world's treasury all comes from the tireless endeavors of a uent and ourishing businesses. The more a business thrives, the more economic sustainability it brings upon the society. And one of the key factors of building up a thriving business is what motivated us to forgo on our research. Location analytics in recent times plays an important role in making a sustainable and pro table business. Very often trade and commerce rely on uninformed struggles to analyze the perfect location for their establishment. Hence, we used unsupervised learning to evaluate a dataset and create a decision making model to accurately investigate whether a location will be be tting for a particular business model based on customer behaviour and interests. As such we built a dataset concentrating on questionnaire responses taken via online survey and tested our model on the gathered data. We exercised the analyzed dataset in di erent clustering algorithms such as kmeans, minibatch kmeans and hierarchical clustering. Finally, using a decision tree model, we were able to extract an explanatory rule in terms of quantitative values, which were further discerned in making an elaborate assumption. Hence, based on consumer habits and interests, we concluded that we could analyze which location or marketplace would be better suited for which accessories a seller is selling, and hence suggest the perfect location for his business to thrive upon. Mir Ibtid Mahmud Onez Chowdhury Yashwant Alvee Tawsif Sadman Imrul Haque Shaon B. Computer Science 2022-01-11T05:02:57Z 2022-01-11T05:02:57Z 2021 2021-09 Thesis ID 17101351 ID 21341063 ID 16341010 ID 17101107 ID 17301045 http://hdl.handle.net/10361/15860 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 44 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Data analysis Geo analytics Decision tree Linear regression analysis K-Means clustering Machine learning
spellingShingle	Data analysis Geo analytics Decision tree Linear regression analysis K-Means clustering Machine learning Mahmud, Mir Ibtid Chowdhury, Onez Alvee, Yashwant Sadman, Tawsif Shaon, Imrul Haque Finding ideal geographical location for businesses using machine learning technique
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
author2	Ashraf, Faisal Bin
author_facet	Ashraf, Faisal Bin Mahmud, Mir Ibtid Chowdhury, Onez Alvee, Yashwant Sadman, Tawsif Shaon, Imrul Haque
format	Thesis
author	Mahmud, Mir Ibtid Chowdhury, Onez Alvee, Yashwant Sadman, Tawsif Shaon, Imrul Haque
author_sort	Mahmud, Mir Ibtid
title	Finding ideal geographical location for businesses using machine learning technique
title_short	Finding ideal geographical location for businesses using machine learning technique
title_full	Finding ideal geographical location for businesses using machine learning technique
title_fullStr	Finding ideal geographical location for businesses using machine learning technique
title_full_unstemmed	Finding ideal geographical location for businesses using machine learning technique
title_sort	finding ideal geographical location for businesses using machine learning technique
publisher	Brac University
publishDate	2022
url	http://hdl.handle.net/10361/15860
work_keys_str_mv	AT mahmudmiribtid findingidealgeographicallocationforbusinessesusingmachinelearningtechnique AT chowdhuryonez findingidealgeographicallocationforbusinessesusingmachinelearningtechnique AT alveeyashwant findingidealgeographicallocationforbusinessesusingmachinelearningtechnique AT sadmantawsif findingidealgeographicallocationforbusinessesusingmachinelearningtechnique AT shaonimrulhaque findingidealgeographicallocationforbusinessesusingmachinelearningtechnique
_version_	1814309430293954560

Finding ideal geographical location for businesses using machine learning technique

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