AIMC Topic: Population Dynamics

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Predicting the seasonal dynamics of Dalbulus maidis (Hemiptera: Cicadellidae) in corn using artificial neural networks.

Neotropical entomology
This study addresses the challenge of predicting Dalbulus maidis (DeLong & Wolcott) (Hemiptera: Cicadellidae) density in cornfields by developing an artificial neural network (ANN). Over two years, we collected data on meteorological variables (atmos...

Integrating dynamic models and neural networks to discover the mechanism of meteorological factors on Aedes population.

PLoS computational biology
Aedes mosquitoes, known as vectors of mosquito-borne diseases, pose significant risks to public health and safety. Modeling the population dynamics of Aedes mosquitoes requires comprehensive approaches due to the complex interplay between biological ...

Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning.

The Science of the total environment
Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquati...

From expansion to efficiency: Machine learning-based forecasting of Japan's building material stocks under demographic declines.

The Science of the total environment
Japan's unique demographic trajectory, marked by population decline and aging, coupled with continued urbanization, presents distinct challenges for aligning built environment capacity with resource efficiency. This study aims to investigate the hist...

Using neural ordinary differential equations to predict complex ecological dynamics from population density data.

Journal of the Royal Society, Interface
Simple models have been used to describe ecological processes for over a century. However, the complexity of ecological systems makes simple models subject to modelling bias due to simplifying assumptions or unaccounted factors, limiting their predic...

Dynamic analysis of a fuzzy Bobwhite quail population model under g-division law.

Scientific reports
This paper is concerned with a kind of Bobwhite quail population model where the parameters and initial values are positive parabolic fuzzy numbers. According to g-division of fuzzy sets and based on the symmetrical parabolic fuzzy numbers, the cond...

The marital and fertility sentiment orientation of Chinese women and its influencing factors - An analysis based on natural language processing.

PloS one
BACKGROUND: With the evolution of China's social structure and values, there has been a shift in attitudes towards marriage and fertility, with an increasing number of women holding diverse perspectives on these matters. In order to better comprehend...

A large-scale neural network training framework for generalized estimation of single-trial population dynamics.

Nature methods
Achieving state-of-the-art performance with deep neural population dynamics models requires extensive hyperparameter tuning for each dataset. AutoLFADS is a model-tuning framework that automatically produces high-performing autoencoding models on dat...

A deep learning framework for inference of single-trial neural population dynamics from calcium imaging with subframe temporal resolution.

Nature neuroscience
In many areas of the brain, neural populations act as a coordinated network whose state is tied to behavior on a millisecond timescale. Two-photon (2p) calcium imaging is a powerful tool to probe such network-scale phenomena. However, estimating the ...

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

eLife
Microorganisms growing in their habitat constitute a complex system. How the individual constituents of the environment contribute to microbial growth remains largely unknown. The present study focused on the contribution of environmental constituent...