Finding ideal geographical location for businesses using machine learning technique

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.

Bibliographische Detailangaben
Hauptverfasser:	Mahmud, Mir Ibtid, Chowdhury, Onez, Alvee, Yashwant, Sadman, Tawsif, Shaon, Imrul Haque
Weitere Verfasser:	Ashraf, Faisal Bin
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2022
Schlagworte:	Data analysis Geo analytics Decision tree Linear regression analysis K-Means clustering Machine learning
Online Zugang:	http://hdl.handle.net/10361/15860

Ähnliche Einträge

Correlating lockdowns, mortality rates and air pollution: a deep learning imbued study of COVID-19
von: Tabassum, Tahia, et al.
Veröffentlicht: (2021)

Where will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishment
von: Shihab, Ibne Farabi, et al.
Veröffentlicht: (2018)

Predicting the length of stay in a hospital for a particular disease using machine learning algorithms
von: Imam, Saif
Veröffentlicht: (2021)

Identifying the best metrics to find the best quality clusters of genes from gene expression data
von: Choudhury, Joydhriti, et al.
Veröffentlicht: (2019)

LRFMV: an efficient customer segmentation model for superstores
von: Toyeb, Md., et al.
Veröffentlicht: (2021)

Customer segmentation using K-means
von: Mahdee, Nafis, et al.
Veröffentlicht: (2022)

Early grade prediction using profile data
von: Iqbal, Sumaiya, et al.
Veröffentlicht: (2021)

UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
von: Araf, Sadman, et al.
Veröffentlicht: (2021)

Identification and comparative analysis of potholes using image processing algorithms
von: Anik, Fahim Shahriare, et al.
Veröffentlicht: (2018)

A novel approach to reduce air pollution through machine learning based PM2.5 prediction
von: Alif, Omar Farhad, et al.
Veröffentlicht: (2023)

Generating and compressing images from a large volume of discrete datasets using GANs along with different compression techniques and studying the results
von: Sajid, Mayeen Abedin, et al.
Veröffentlicht: (2023)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
von: Rahee, Arnob, et al.
Veröffentlicht: (2021)

Pilot study on the development of a low cost land observation and geo-information retrieval system for emergency monitoring of agricultural crop and disaster-induced damages
von: Haque, Md. Mojammel, et al.
Veröffentlicht: (2016)

Machine learning for stress prediction
von: Salehin, Sherajus, et al.
Veröffentlicht: (2023)

Intelligent assisted living in pregnancy
von: Zaman, S. M. Tanveer, et al.
Veröffentlicht: (2022)

Automated fabric color prediction
von: Muhtashima, Fawzia, et al.
Veröffentlicht: (2024)

Application of CNN based architectures in detection of distracted drivers
von: Arafin, Irfana, et al.
Veröffentlicht: (2023)

A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
von: Farabe, Abdullah Al, et al.
Veröffentlicht: (2021)

A feature selection approach to determine obesity using machine learning method
von: Antor, Shahidul Alam, et al.
Veröffentlicht: (2021)

Ideal solution of college linear algebra : theory of matrices /
von: Rahman, Md. Abdur
Veröffentlicht: (1986)

A voice signal based gender prediction model using random forest classifier
von: Ahmed, Saif, et al.
Veröffentlicht: (2018)

Automatic text summarization using Gensim Word2Vec and K-Means Clustering Algorithm
von: Haider, Mofiz Mojib, et al.
Veröffentlicht: (2021)

The economics of clusters

Geo-politics, democratization and external influence: the Bangladesh case
von: Chowdhury, Faiz Ahmed
Veröffentlicht: (2019)

LRFS: online shoppers’ behavior based efficient customer segmentation model
von: Khan, Riyo Hayat
Veröffentlicht: (2023)

Data analysis on the Bangladesh share market using Machine-Learning
von: Sadman, Syed Hassan, et al.
Veröffentlicht: (2021)

Cardiovascular disease prediction model using Machine Learning Algorithm
von: Arefin Mirdha, MD Shamsul
Veröffentlicht: (2023)

Effectiveness of data mining in predicting heart diseases
von: Afrin, Shahria, et al.
Veröffentlicht: (2018)

Anomaly clustering based on correspondence analysis
von: Islam, Humayra
Veröffentlicht: (2018)

Polycystic ovary syndrome detection using neural network.
von: Istiyaq, Tahsin, et al.
Veröffentlicht: (2024)

Finding suitable locations for live campaigns using different machine learning techniques
von: Qudar, Mohiuddin Md. Abdul, et al.
Veröffentlicht: (2018)

Weather forecasting using Deep Learning
von: Fahad, Sheikh Abdul, et al.
Veröffentlicht: (2023)

Detecting tweet sentiment and sarcasm on online learning during covid-19
von: Das, Shishir Kumar, et al.
Veröffentlicht: (2024)

The applications of data mining and machine learning in Bangladesh for disease pattern analysis and prediction
von: Mahmud, Mahmudul Hasan
Veröffentlicht: (2021)

LRFMVD : a customer segmentation model
von: Sagor, Kawsar Mahmud, et al.
Veröffentlicht: (2023)

Fake profile detection in social media using image processing and machine learning
von: Sen, Shuva, et al.
Veröffentlicht: (2021)

Flood prediction using machine learning models
von: Syeed, Miah Mohammad Asif, et al.
Veröffentlicht: (2022)

Modelling and forecasting energy demand of Bangladesh using AI based algorithms
von: Mahmud, Booshra Nazifa, et al.
Veröffentlicht: (2019)

Heart disease prediction using techniques of classification in machine learning
von: Afrose, Sadia, et al.
Veröffentlicht: (2021)

Bengali text summarization using TextRank, Fuzzy C-means and aggregated scoring techniques
von: Rahman, Alvee, et al.
Veröffentlicht: (2019)