A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks

Data mining is an information exploration methodology with fascinating and understandable patterns and informative models for vast volumes of data. Agricultural productivity growth is the key to poverty alleviation. However, due to a lack of proper technical guidance in the agriculture field, crop y...

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Autores principales:	Aghila Rajagopal, Sudan Jha, Manju Khari, Sultan Ahmad, Bader Alouffi, Abdullah Alharbi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	data mining crop production recurrent cuckoo search optimization algorithm Discrete DBN-VGGNet classifier Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/4f9d6183b0034d05b60b206f41f3490c
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id	oai:doaj.org-article:4f9d6183b0034d05b60b206f41f3490c
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spelling	oai:doaj.org-article:4f9d6183b0034d05b60b206f41f3490c2021-11-11T14:57:55ZA Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks10.3390/app112198162076-3417https://doaj.org/article/4f9d6183b0034d05b60b206f41f3490c2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9816https://doaj.org/toc/2076-3417Data mining is an information exploration methodology with fascinating and understandable patterns and informative models for vast volumes of data. Agricultural productivity growth is the key to poverty alleviation. However, due to a lack of proper technical guidance in the agriculture field, crop yield differs over different years. Mining techniques were implemented in different applications, such as soil classification, rainfall prediction, and weather forecast, separately. It is proposed that an Artificial Intelligence system can combine the mined extracts of various factors such as soil, rainfall, and crop production to predict the market value to be developed. Smart analysis and a comprehensive prediction model in agriculture helps the farmer to yield the right crops at the right time. The main benefits of the proposed system are as follows: Yielding the right crop at the right time, balancing crop production, economy growth, and planning to reduce crop scarcity. Initially, the database is collected, and the input dataset is preprocessed. Feature selection is carried out followed by feature extraction techniques. The best features were then optimized using the recurrent cuckoo search optimization algorithm, then the optimized output can be given as an input for the process of classification. The classification process is conducted using the Discrete DBN-VGGNet classifier. The performance estimation is made to prove the effectiveness of the proposed scheme.Aghila RajagopalSudan JhaManju KhariSultan AhmadBader AlouffiAbdullah AlharbiMDPI AGarticledata miningcrop productionrecurrent cuckoo search optimization algorithmDiscrete DBN-VGGNet classifierTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9816, p 9816 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	data mining crop production recurrent cuckoo search optimization algorithm Discrete DBN-VGGNet classifier Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	data mining crop production recurrent cuckoo search optimization algorithm Discrete DBN-VGGNet classifier Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Aghila Rajagopal Sudan Jha Manju Khari Sultan Ahmad Bader Alouffi Abdullah Alharbi A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks
description	Data mining is an information exploration methodology with fascinating and understandable patterns and informative models for vast volumes of data. Agricultural productivity growth is the key to poverty alleviation. However, due to a lack of proper technical guidance in the agriculture field, crop yield differs over different years. Mining techniques were implemented in different applications, such as soil classification, rainfall prediction, and weather forecast, separately. It is proposed that an Artificial Intelligence system can combine the mined extracts of various factors such as soil, rainfall, and crop production to predict the market value to be developed. Smart analysis and a comprehensive prediction model in agriculture helps the farmer to yield the right crops at the right time. The main benefits of the proposed system are as follows: Yielding the right crop at the right time, balancing crop production, economy growth, and planning to reduce crop scarcity. Initially, the database is collected, and the input dataset is preprocessed. Feature selection is carried out followed by feature extraction techniques. The best features were then optimized using the recurrent cuckoo search optimization algorithm, then the optimized output can be given as an input for the process of classification. The classification process is conducted using the Discrete DBN-VGGNet classifier. The performance estimation is made to prove the effectiveness of the proposed scheme.
format	article
author	Aghila Rajagopal Sudan Jha Manju Khari Sultan Ahmad Bader Alouffi Abdullah Alharbi
author_facet	Aghila Rajagopal Sudan Jha Manju Khari Sultan Ahmad Bader Alouffi Abdullah Alharbi
author_sort	Aghila Rajagopal
title	A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks
title_short	A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks
title_full	A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks
title_fullStr	A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks
title_full_unstemmed	A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks
title_sort	novel approach in prediction of crop production using recurrent cuckoo search optimization neural networks
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4f9d6183b0034d05b60b206f41f3490c
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A Novel Approach in Prediction of Crop Production Using Recurrent Cuckoo Search Optimization Neural Networks

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