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Multimodal Machine Learning Based crop recommendation and Yield Prediction Model

Intelligent Automation & Soft Computing 2023年第4期36卷 313-326页

作者： P.S.S.Gopi M.Karthikeyan Department of Computer and Information Science Faculty of ScienceAnnamalai UniversityChidambaram608002India

Agriculture plays a vital role in the Indian *** recommen-dation for a speciﬁc region is a tedious process as it can be affected by various variables such as soil type and climatic *** the same time,crop yield prediction was based on several features like area,irrigation type,temperature,*** recent advancements of artiﬁcial intelligence(AI)and machine learning(ML)models pave the way to design effective crop recommendation and crop pre-diction *** this view,this paper presents a novel Multimodal Machine Learning Based crop recommendation and Yield Prediction(MMML-CRYP)*** proposed MMML-CRYP model mainly focuses on two processes namely crop recommendation and crop *** the initial stage,equilibrium optimizer(EO)with kernel extreme learning machine(KELM)technique is employed for effectual recommendation of ***,random forest(RF)tech-nique was executed for predicting the crop yield *** reporting the improved performance of the MMML-CRYP system,a wide range of simulations were carried out and the results are investigated using benchmark ***-mentation outcomes highlighted the signiﬁcant performance of the MMML-CRYP approach on the compared approaches with maximum accuracy of 97.91%.

关键词： Agriculture crop recommendation yield prediction machine learning artiﬁcial intelligence

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Prediction of Suitable crops Using Stacked Scaling Conjugant Neural Classifier

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Intelligent Automation & Soft Computing 2023年第3期35卷 3743-3755页

作者： P.Nithya A.M.Kalpana Government College of Engineering Salem636011India

Agriculture plays a vital role in economic *** major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,*** farmers were following ancestral patterns,which could sometimes lead to the wrong selection of *** this research work,the feature selection method is adopted to improve the performance of the classiﬁ*** most relevant features from the dataset are obtained using a Probabilistic Feature Selection(PFS)approach,and classiﬁ-cation is done using a Neural Fuzzy Classiﬁer(NFC).Scaling Conjugate Gradient(SCG)optimization method is used to update the *** data set used for analysis contain various parameters such as soil characteristics,geographical loca-tion,and environmental factors such as temperature and *** proposed method recommends suitable crops for cultivation based on site-speciﬁc *** result shows that the proposed method provides high accu-racy and efﬁciency as compared to existing methodologies.

关键词： Feature selection neural fuzzy classiﬁer optimization crop recommendation

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Automatic crop Expert System Using Improved LSTM with Attention Block

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Computer Systems Science & Engineering 2023年第11期47卷 2007-2025页

作者： Shahbaz Sikandar Rabbia Mahum Suliman Aladhadh Computer Science Department University of Engineering and TechnologyTaxilaPakistan Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

Agriculture plays an important role in the economy of any *** half of the population of developing countries is directly or indirectly connected to the agriculture *** farmers do not choose the right crop for cultivation depending on their soil type,crop type,and climatic requirements like *** wrong decision of crop selection directly affects the production of the crops which leads to yield and economic loss in the *** parameters should be observed such as soil characteristics,type of crop,and environmental factors for the cultivation of the right *** decision-making is time-taking and requires extensive ***,there should be an automated system for the right crop recommendation to reduce human efforts and *** automated crop recommender system should take these parameters as input and suggest the farmer’s right ***,in this paper,a long short-term memory Network with an attention block has been *** proposed model contains 27 layers,the first of which is a feature input *** exist 25 hidden layers between them,and an output layer completes the *** these levels,the proposed model enables a successful recommendation of the ***,the dropout layer’s regularization properties aids in reduction of overfitting of the *** this paper,a customized novel long short-term memory(LSTM)model is proposed with a residual attention block that recommends the right crop to *** metrics used for the proposed model include f1-score,recall,precision,and accuracy attaining values as 95.69%,96.56%,96.9%,and 97.26%respectively.

关键词： crop recommendation LSTM deep neural network

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