Crop prediction based on geographical and climatic data using machine learning and deep learning

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

書目詳細資料
Main Authors:	Alif, Al Amin, Shukanya, Israt Farhana, Afee, Tasnia Nobi
其他作者:	Arif, Hossain
格式:	Thesis
語言:	English
出版:	BRAC University 2019
主題:	Agriculture Crop selection Machine learning Artificial neural network
在線閱讀:	http://hdl.handle.net/10361/11429

id	10361-11429
record_format	dspace
spelling	10361-114292022-01-26T10:05:01Z Crop prediction based on geographical and climatic data using machine learning and deep learning Alif, Al Amin Shukanya, Israt Farhana Afee, Tasnia Nobi Arif, Hossain Department of Computer Science and Engineering, BRAC University Agriculture Crop selection Machine learning Artificial neural network Machine learning This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Includes bibliographical references (pages 46). Cataloged from PDF version of thesis. Agriculture is the basic source of food supply in all the countries of the world—whether underdeveloped, developing or developed. Besides providing food, this sector has contributions to almost every other sector of a country. According to the Bangladesh Bureau of Statistics (BBS), 2017, about 17 % of the country’s Gross Domestic Product (GDP) is a contribution of the agricultural sector, and it employs more than 45% of the total labor force. In light of the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture now-a-days is selecting the right crop for the right piece of land at the right time. Therefore, in our research we have proposed a method which would help suggest the most suitable crop(s) for a specific land based on the analysis of the data of previous years on certain affecting parameters using machine learning. In our work, we have implemented Random Forest Classifier, Gaussian Naïve Bayes, Logistic Regression, Support Vector Machine, k-Nearest Neighbor, and Artificial Neural Network for crop selection. We have trained these algorithms with the training data and later these were tested with test dataset. We then compared the performances of all the tested methods to arrive at the best outcome. Keywords: Crop Selection, Machine Learning Algorithms, Artificial Neural Network. Al Amin Alif Israt Farhana Shukanya Tasnia Nobi Afee B. Computer Science and Engineering 2019-02-18T04:58:16Z 2019-02-18T04:58:16Z 2018 2018-12 Thesis ID 14101009 ID 14101186 ID 14301052 http://hdl.handle.net/10361/11429 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. 46 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Agriculture Crop selection Machine learning Artificial neural network Machine learning
spellingShingle	Agriculture Crop selection Machine learning Artificial neural network Machine learning Alif, Al Amin Shukanya, Israt Farhana Afee, Tasnia Nobi Crop prediction based on geographical and climatic data using machine learning and deep learning
description	This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
author2	Arif, Hossain
author_facet	Arif, Hossain Alif, Al Amin Shukanya, Israt Farhana Afee, Tasnia Nobi
format	Thesis
author	Alif, Al Amin Shukanya, Israt Farhana Afee, Tasnia Nobi
author_sort	Alif, Al Amin
title	Crop prediction based on geographical and climatic data using machine learning and deep learning
title_short	Crop prediction based on geographical and climatic data using machine learning and deep learning
title_full	Crop prediction based on geographical and climatic data using machine learning and deep learning
title_fullStr	Crop prediction based on geographical and climatic data using machine learning and deep learning
title_full_unstemmed	Crop prediction based on geographical and climatic data using machine learning and deep learning
title_sort	crop prediction based on geographical and climatic data using machine learning and deep learning
publisher	BRAC University
publishDate	2019
url	http://hdl.handle.net/10361/11429
work_keys_str_mv	AT alifalamin croppredictionbasedongeographicalandclimaticdatausingmachinelearninganddeeplearning AT shukanyaisratfarhana croppredictionbasedongeographicalandclimaticdatausingmachinelearninganddeeplearning AT afeetasnianobi croppredictionbasedongeographicalandclimaticdatausingmachinelearninganddeeplearning
_version_	1814307187473776640

Crop prediction based on geographical and climatic data using machine learning and deep learning

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