AIMC Topic: Population Dynamics

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The impact of sparsity in low-rank recurrent neural networks.

PLoS computational biology
Neural population dynamics are often highly coordinated, allowing task-related computations to be understood as neural trajectories through low-dimensional subspaces. How the network connectivity and input structure give rise to such activity can be ...

Prediction of Labor Unemployment Based on Time Series Model and Neural Network Model.

Computational intelligence and neuroscience
With the advent of big data, statistical accounting based on artificial intelligence can realistically reflect the dynamics of labor force and market segmentation. Therefore, based on the combination of machine learning algorithm and traditional stat...

Robots as models of evolving systems.

Proceedings of the National Academy of Sciences of the United States of America
Experimental robobiological physics can bring insights into biological evolution. We present a development of hybrid analog/digital autonomous robots with mutable diploid dominant/recessive 6-byte genomes. The robots are capable of death, rebirth, an...

A low-cost, long-term underwater camera trap network coupled with deep residual learning image analysis.

PloS one
Understanding long-term trends in marine ecosystems requires accurate and repeatable counts of fishes and other aquatic organisms on spatial and temporal scales that are difficult or impossible to achieve with diver-based surveys. Long-term, spatiall...

Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework.

PLoS computational biology
Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by sp...

TiDEC: A Two-Layered Integrated Decision Cycle for Population Evolution.

IEEE transactions on cybernetics
Agent-based simulation is a useful approach for the analysis of dynamic population evolution. In this field, the existing models mostly treat the migration behavior as a result of utility maximization, which partially ignores the endogenous mechanism...

Aedes-AI: Neural network models of mosquito abundance.

PLoS computational biology
We present artificial neural networks as a feasible replacement for a mechanistic model of mosquito abundance. We develop a feed-forward neural network, a long short-term memory recurrent neural network, and a gated recurrent unit network. We evaluat...

Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.

Scientific reports
Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle an epidemiological process that evolves rapidly and is spatially heterogeneous. On the other hand, ma...

Complex population dynamics in a spatial microbial ecosystem with Physarum polycephalum.

Bio Systems
This research addresses the interactions between the unicellular slime mold Physarum polycephalum and a red yeast in a spatial ecosystem over week-long imaging experiments. An inverse relationship between the growth rates of both species is shown, wh...

Towards sustainable demersal fisheries: NepCon image acquisition system for automatic Nephrops norvegicus detection.

PloS one
Underwater video monitoring systems are being widely used in fisheries to investigate fish behavior in relation to fishing gear and fishing gear performance during fishing. Such systems can be useful to evaluate the catch composition as well. In deme...