Analyzing the Link Between Agricultural Inputs and Productivity Through Analytics and Perceptron Neural Networks

Abstract

Technological advancements in the areas of sensors, GPS, drones, and precision fertilization are driving precision agriculture, which uses sophisticated algorithms and artificial intelligence to optimize agricultural efficiency and generate large volumes of data, known as Big Data. This data contains valuable information that can be used to support more efficient and effective decisions in agribusiness. Efficient management of rural properties is challenging due to several variables, which make effective decision-making difficult. However, appropriate technology, such as the use of Perceptron and Analytics, can overcome these limitations and provide a more comprehensive view for agricultural decision-making. The application of these tools in the management of rural properties offers a complete approach, allowing for more accurate decisions and contributing to efficient and competitive management in the agricultural sector. In view of the above, this article presents a data preparation process, essential to guarantee the quality and effectiveness of the analysis that contributes to the continued success of agribusiness.