Optimized Back-propagation Artificial Neural Network Algorithm for Smart Agriculture Applications

Abstract

Agriculture is a very important sector in building the national economy. National Development of the 21st century will still be broadly based on agriculture. The agribusiness-based activities and business will become the main trend in national development. However, this development is not in line with the condition where climate change, soil and irrigation factors are uncertain in almost regions. To cope with this problem a reliable technique such as implementing artificial intelligence is required. Several studies have been conducted and one of these studies used artificial neural networks (ANN). This paper discusses about the modified artificial neural networks backpropagation using the Smart Agriculture dataset, using parameters such as temperature, humidity, wind speed, solar radiation and soil water tension.