Prediction of Suitable Crops Using Stacked Scaling Conjugant Neural Classifier  

作　　者：P.Nithya A.M.Kalpana 

机构地区：[1]Government College of Engineering,Salem,636011,India

出　　处：《Intelligent Automation & Soft Computing》2023年第3期3743-3755,共13页智能自动化与软计算（英文）

摘　　要：Agriculture plays a vital role in economic development.The major pro-blem faced by the farmers are the selection of suitable crops based on environ-mental conditions such as weather,soil nutrients,etc.The farmers were following ancestral patterns,which could sometimes lead to the wrong selection of crops.In this research work,the feature selection method is adopted to improve the performance of the classification.The 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 weights.The data set used for analysis contain various parameters such as soil characteristics,geographical loca-tion,and environmental factors such as temperature and rainfall.The proposed method recommends suitable crops for cultivation based on site-specific para-meters.Experimental 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 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]