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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

Issue per Year : 12

Volume Published : 11

Issue Published : 118

Article Submitted : 21508

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Total Authors : 22399

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Paper Title: INNOVATIVE IDEA FOR MONITORING AGRICULTURAL PRODUCTION USING MACHINE LEARNING
Authors Name: M.Umamaheswara Rao , M.Satish , G. Sai MaheshVardhan , K. Sandeep kumar , Mrs.R Nivetha
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IJRTI_186172
Published Paper Id: IJRTI2304161
Published In: Volume 8 Issue 4, April-2023
DOI:
Abstract: As a coastal nation, Tamil Nadu faces agricultural uncertainty, that's decreasing its manufacturing. With more people and locations, extra output may be produced, however this can't be. In the beyond, farmers had phrase of mouth, but now they can not be used because of climatic conditions. Agricultural information and parameters provide the perception of agricultural information. The advent of the technology of records brings some vital tendencies to the agricultural sciences to assist farmers maintain particular agricultural information. In this taking walks situation, the facts on the usefulness of modern technological strategies in agriculture are accurate. Machine learning techniques without a doubt provide an explanation for styles with statistics and help us make predictions. Agricultural problems related to crop availability, crop rotation, water call for, fertilizer need and safety may be solved. Due to unique climatic conditions, it's far very essential to have an green system to facilitate the cultivation of plant life and assist farmers in production and control. This will help future farmers to improve agriculture. The farmer may be given a device tip to assist him get his vegetation via the mines. To enforce this method, flowers covers are advocated in terms of their climatic factors and quantity. Data analytics paves the manner for developing useful extracts from agricultural databases. The harvest dataset was analyzed and harvest recommendation became made primarily based on yield and season.
Keywords: ML, predictions, random forest, crop yielding.
Cite Article: "INNOVATIVE IDEA FOR MONITORING AGRICULTURAL PRODUCTION USING MACHINE LEARNING", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 4, page no.992 - 997, April-2023, Available :http://www.ijrti.org/papers/IJRTI2304161.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2304161
Registration ID:186172
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 992 - 997
Country: chennai, Tamil Nadu, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2304161
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2304161
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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