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Biological Evolution

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Machine learning in evolutionary studies comes of age.

Proceedings of the National Academy of Sciences of the United States of America

How signals interact in multimodal displays: Insights from a robotic frog.

The Journal of animal ecology
Caldart, M. V., M. B. dos Santos & G. Machado (2021). Function of a multimodal signal: a multiple hypothesis test using a robot frog Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13620. Animals can communicate using signals perceived b...

Discovering Parametric Activation Functions.

Neural networks : the official journal of the International Neural Network Society
Recent studies have shown that the choice of activation function can significantly affect the performance of deep learning networks. However, the benefits of novel activation functions have been inconsistent and task dependent, and therefore the rect...

Coalescent-based species delimitation meets deep learning: Insights from a highly fragmented cactus system.

Molecular ecology resources
Delimiting species boundaries is a major goal in evolutionary biology. An increasing volume of literature has focused on the challenges of investigating cryptic diversity within complex evolutionary scenarios of speciation, including gene flow and de...

mCNN-ETC: identifying electron transporters and their functional families by using multiple windows scanning techniques in convolutional neural networks with evolutionary information of protein sequences.

Briefings in bioinformatics
In the past decade, convolutional neural networks (CNNs) have been used as powerful tools by scientists to solve visual data tasks. However, many efforts of convolutional neural networks in solving protein function prediction and extracting useful in...

Path planning for autonomous mobile robots using multi-objective evolutionary particle swarm optimization.

PloS one
In this article, a new path planning algorithm is proposed. The algorithm is developed on the basis of the algorithm for finding the best value using multi-objective evolutionary particle swarm optimization, known as the MOEPSO. The proposed algorith...

Evolutionary Game Analysis of Farmers' Conservation Tillage Behavior in Black Soil Areas Guided by Deep Learning.

Computational intelligence and neuroscience
To better protect the rights and interests of farmers, the evolutionary game theory and deep learning (DL) technology are used to analyze the conservation tillage behavior of farmers in black soil areas. Firstly, the basic hypotheses are put forward ...

Training a Feedforward Neural Network Using Hybrid Gravitational Search Algorithm with Dynamic Multiswarm Particle Swarm Optimization.

BioMed research international
One of the most well-known methods for solving real-world and complex optimization problems is the gravitational search algorithm (GSA). The gravitational search technique suffers from a sluggish convergence rate and weak local search capabilities wh...

Medical Image Captioning Using Optimized Deep Learning Model.

Computational intelligence and neuroscience
Medical image captioning provides the visual information of medical images in the form of natural language. It requires an efficient approach to understand and evaluate the similarity between visual and textual elements and to generate a sequence of ...

The automatic parameter-exploration with a machine-learning-like approach: Powering the evolutionary modeling on the origin of life.

PLoS computational biology
The origin of life involved complicated evolutionary processes. Computer modeling is a promising way to reveal relevant mechanisms. However, due to the limitation of our knowledge on prebiotic chemistry, it is usually difficult to justify parameter-s...