[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119103-en":3,"doc-seo-119103-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},119103,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",8,"Research & Report","Application of Machine Learning to the Process of Crop Selection Based on Land Dataset - Paper","The study proposes a machine learning framework for crop selection to support farmers and improve agricultural planning. It argues that Indian agriculture often repeats similar crops and inputs, creating the need for data-driven reforms. The research focuses on crop prediction from land-related information and evaluates model performance. Random Forest is used to estimate crop outcomes, then compared against competing techniques, aiming to maximize crop yields and strengthen agricultural productivity.","INTERNATIONAL JOURNAL ON ORANGE TECHNOLOGY  \n[https://journals.researchparks.org/index.php/IJOT](https://journals.researchparks.org/index.php/IJOT) e-ISSN: 2615-8140 | p-ISSN: 2615-7071 Volume: 5 Issue: 6 | Jun 2023  \nApplication of Machine Learning to the Process of Crop Selection Based on Land  \nDataset  \nS. Suman Rajest  \nProfessor, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India  \nS. Silvia Priscila  \nAssociate Professor, Department of Computer Science, Bharath Institute of Higher Education  \nand Research, Tamil Nadu, India  \nR. Regin  \nAssistant Professor, Department of Computer Science and Engineering, SRM Institute of Science  \nand Technology, Ramapuram, India  \n[regin12006@yahoo.co.in](regin12006@yahoo.co.in)  \nShynu T  \nMaster of Engineering, Department of Biomedical Engineering, Agni College of Technology, Chennai,  \nTamil Nadu, India  \nSteffi. R  \nAssistant Professor, Department of Electronics and Communication, Vins Christian College  \nof Engineering, Tamil Nadu, India  \n***  \n----- - -------------------- -- ------ ---------------------------- ----------------------- ----- -- -------------------------------  \nAnnotation: We are well recognised that the vast majority of Indians work in agriculture. Most farmers always grow the same thing, always use the same amount of fertilizer, and always plant what the people want. Recently, there have been many breakthroughs in the use of machine learning in many fields of study and business. Thus, we intend to establish a framework for the application of machine learning in agriculture for the benefit of farmers. India's economy relies heavily on the nation's agricultural output. Agriculture, then, has the potential to serve as the backbone of the Philippine economy. Choosing the right crop every time is crucial when making agricultural plans. Researchers have utilised machine learning to explore agricultural issues such as crop yield, weather prediction, soil categorization, and crop labelling. Our Indian economy really needs the agricultural sector to undergo significant reforms. Simple applications of machine learning systems in agriculture have the potential to significantly enhance this industry. In addition to the considerable role played by improvements in farming machinery and technology, functional information about many subjects also plays an important role. The main idea of this study is to use the crop selection approach in order to address numerous issues in farming. This increases the wealth of India by increasing crop yields to their maximum potential. In our study, we use the method Random Forest (RF) to estimate a crop and then evaluate its performance relative to that of competing techniques.  \nKeywords: Artificial Neural Network, Convolutional Neural Network, Research on Cancer, Computer Aided Detection, Data Flow Diagram.  \nINTERNATIONAL JOURNAL ON ORANGE TECHNOLOGY  \n[https://journals.researchparks.org/index.php/IJOT](https://journals.researchparks.org/index.php/IJOT) e-ISSN: 2615-8140 | p-ISSN: 2615-7071 Volume: 5 Issue: 6 | Jun 2023  \nIntroduction  \nSince it is common knowledge that the vast majority of Indians work in the agricultural sector. Most farmers always grow the same thing, always use the same amount of fertilizer, and always plant what the people want [1] . Recently, there have been many breakthroughs in the use of machine learning in many fields of study and business [2]. Thus, we intend to establish a framework for the application of machine learning in agriculture for the benefit of farmers. India's economy relies heavily on the nation's agricultural output [3]. Agriculture, then, has the potential to serve as the backbone of the Philippine economy. Choosing the right crop every time is crucial when making agricultural plans. Researchers have utilised machine learning to explore agricultural issues such as crop yield, weather prediction, soil categorization, and crop labelling. Our Indian economy really needs the agricultur","cbCaiazv7UYvway3","https://ap.wps.com/l/cbCaiazv7UYvway3","pdf",775799,1,22,"English","en",105,"# Introduction\n## Machine learning background\n## Motivation for crop selection\n# Related tasks and evaluation approach","[{\"question\":\"Why is a machine learning framework needed for crop selection?\",\"answer\":\"The document highlights that many farmers repeat the same crops and input practices, so selecting the right crop each time is crucial. Machine learning can support reforms by improving decisions in agricultural planning.\"},{\"question\":\"Which machine learning method is used for crop estimation?\",\"answer\":\"Random Forest (RF) is used to estimate crop outcomes in the study.\"},{\"question\":\"How does the study evaluate the crop selection approach?\",\"answer\":\"The document states that the RF method’s performance is evaluated relative to competing techniques, focusing on predictive effectiveness for crop outcomes.\"}]","Application of Machine Learning to the Process of Crop Selection Based on Land Dataset - Paper | PDF",1785722403,55,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"application-of-machine-learning-to-the-process-of-crop-selection-based-on-land-dataset-paper","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/application-of-machine-learning-to-the-process-of-crop-selection-based-on-land-dataset-paper/119103/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is a machine learning framework needed for crop selection?","Question",{"text":75,"@type":76},"The document highlights that many farmers repeat the same crops and input practices, so selecting the right crop each time is crucial. 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