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Inverse binary optimization of convolutional neural network in active learning efficiently designs nanophotonic structures [PDF]

Scientific Reports
Binary optimization using active learning schemes has gained attention for automating the discovery of optimal designs in nanophotonic structures and material configurations.
Jaehyeon Park, Zhihao Xu, Gyeong-Moon Park, Tengfei Luo, Eungkyu Lee   +4 more
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Hypervolume Niche Dynamics and Global Invasion Risk of Phenacoccus solenopsis under Climate Change [PDF]

Insects
As a globally invasive quarantine pest, the cotton mealybug, Phenacoccus solenopsis, is spreading rapidly, posing serious threats against agricultural and forestry production and biosecurity.
Shaopeng Cui, Huisheng Zhang, Lirui Liu, Weiwei Lyu, Lin Xu, Zhiwei Zhang, Youzhi Han   +6 more
doaj   +2 more sources

GPU-Accelerated Infill Criterion for Multi-Objective Efficient Global Optimization Algorithm and Its Applications

Applied Sciences, 2022
In this work, a novel multi-objective efficient global optimization (EGO) algorithm, namely GMOEGO, is presented by proposing an approach of available threads’ multi-objective infill criterion.
Shengguan Xu, Jiale Zhang, Hongquan Chen, Yisheng Gao, Yunkun Gao, Huanqin Gao, Xuesong Jia   +6 more
doaj   +1 more source

A Two-Stage Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization

Mathematics, 2023
Many-objective optimization is a critical research topic in the evolutionary computing community. Many algorithms have been proposed to tackle this problem, with evolutionary algorithms based on the hypervolume being among the most effective ones ...
Chengxin Wen, Hongbin Ma
doaj   +1 more source

The species chromatogram, a new graphical method to represent, characterize, and compare the ecological niches of different species

Ecology and Evolution, 2022
The ecological niche sensu Hutchinson is defined as the set of environmental conditions allowing a species to grow, maintain, and reproduce. This conception of the niche, which is assimilated to a p‐dimensional hypervolume, with p representing all ...
Loïck Kléparski, Grégory Beaugrand
doaj   +1 more source

Differences in functional niche hypervolume among four types of forest vegetation and their environmental determinants across various climatic regions in China

Frontiers in Plant Science, 2023
Functional traits play an important role in studying the functional niche in plant communities. However, it remains unclear whether the functional niches of typical forest plant communities in different climatic regions based on functional traits are ...
Jihong Huang, Jihong Huang, Ruoyun Yu, Ruoyun Yu, Ruoyun Yu, Runguo Zang, Runguo Zang   +6 more
doaj   +1 more source

Using local and regional trait hypervolumes to study the effects of environmental factors on community assembly

Ecosphere, 2022
Determining how local and environmental conditions affect community assembly processes is critical to understanding and preserving ecosystem functions.
Wei Mao, Zhibin Sun, Elisabeth J. Forrestel, Robert Griffin‐Nolan, Anping Chen, Melinda D. Smith   +5 more
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The Dynamic Hypercube as a Niche Community Model

Frontiers in Ecology and Evolution, 2021
Different models of community dynamics, such as the MacArthur–Wilson theory of island biogeography and Hubbell’s neutral theory, have given us useful insights into the workings of ecological communities.
John M. Halley, Stuart L. Pimm
doaj   +1 more source

A unifying framework for quantifying and comparing n‐dimensional hypervolumes

Methods in Ecology and Evolution, 2021
The quantification of Hutchinson's n‐dimensional hypervolume has enabled substantial progress in community ecology, species niche analysis and beyond. However, most existing methods do not support a partitioning of the different components of hypervolume.
Muyang Lu, Kevin Winner, Walter Jetz
doaj   +1 more source

Improving the Performance of Multiobjective Genetic Algorithms: An Elitism-Based Approach

Information, 2020
Today, many complex multiobjective problems are dealt with using genetic algorithms (GAs). They apply the evolution mechanism of a natural population to a “numerical” population of solutions to optimize a fitness function.
Giorgio Guariso, Matteo Sangiorgio
doaj   +1 more source