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The Advancement of Nature-Inspired Algorithms for Agriculture

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2018 ASABE Annual International Meeting  1800243.(doi:10.13031/aim.201800243)
Authors:   Yanbo Huang
Keywords:   Bionics engineering, Nature-inspired algorithm, Precision agriculture

Abstract. Bionics is the study and design of advanced technology and engineering systems through applying nature-inspired methods and systems. Bionics engineering is the development and implementation of such technology and systems. In the past decade, various nature-inspired systems have been developed through the study of bionics. Compared to systems development, nature-inspired algorithms with biological mimicking have had further advances. In artificial intelligence, machine learning algorithms from artificial neurons and artificial neural networks have been developed to mimic the human brain with synthetic neurons. This research can be traced back to the 1940s and has been expanded to agricultural problem solving in the last three decades. Now, the research and applications have entered the stage of deep learning with multiple layers and various neurons that have complex connections to extract deep features of the target. In this paper, the development of artificial neural networks and deep learning algorithms is presented and discussed in conjunction with their biological connections for agricultural applications. At the same time, the algorithms motivated from recent bionics studies are be compared and discussed for their potentials for agriculture.

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