ssuserb22f5a

crop yield prediction agriculture soil deep learning accuracy convolutional neural network weather climate deep neural network support vector machines artificial neural network recall precision online learning data mining fuzzy logic agro 6 decision support systems multiple linear regression xy fusion bayesian networks hedge backpropagation hedging strategy online gradient descent lem2 algorithm dndc w-som rmse anfis preprocessing multi model ensemble with dnn statistical model irrigation humidity rainfall food crop commercial crop capacity ph temperature tillage depth self organising map crop using deep learning unsupervised machine learning supervised machine learning machine learning data mining techniques linear regression multi layer perception naïve bayesian classification k-nearest neighbour relif f attribute evaluator information gain principal component analysis rain fall ph accuracy level evaluation metrics result analysis feature selection extraction residue climate control classification methods survey local minima slow convergence multicollinearity mme - mdadnn mme-edadnn mme- dadnn cross validity residuals f-measure dadnn depth adaptive multi model ensemble deep neural networks ridge regression