Impact of Climate Change on Food Agriculture (International Journal of Food and Nutritional Sciences, 2022)
The escalating impact of climate change on food agriculture necessitates advanced analyticalapproaches for accurate forecasting and mitigation strategies. This study employs StackedLong Short-Term Memory (LSTM) networks, a sophisticated variant of Recurrent NeuralNetworks (RNNs), to analyze and predict the influence of climate change on agriculturaloutputs. Stacked LSTMs, known for their efficacy in processing sequential and time-seriesdata, are utilized to decipher the complex interdependencies between various climatic factorsand agricultural productivity