Biodiversity assessment based on artificial intelligence and neural network algorithms

摘要: Abstract Together with its associated economic activities, Biodiversity has the impact of increasing global environment to an unprecedented extent. Around world, countries are focusing on resource consumption and ecosystem's ability deliver them. The order is effectively preserved, decision-makers in need biodiversity indicators knowledge which needs be common such a way that they can utilized effectively. High-throughput environmental sensing technology increasingly important monitoring human activities ecosystems. More recently, passive acoustic sensors, boom provided wide range efficient, non-invasive, taxonomic tools for studying wildlife populations communities, responding changes. A proposed best practice criteria detailed guidelines achieving scores used assessment studies based species distribution models. Artificial Intelligence Neural Network Algorithms highly efficient overall detection low model, improves usual takes much time. To establish clear trend, biological assessments lesser extent than data model evaluation. agree relevant standards promote transparency reproducibility argues implementation will lead high-quality models inferences final assessment. expansion encourages wider community participate ongoing improvement.