Schematic diagram of the improved RNNs structure. by Ting Wang (16292)

“…Then, the sparrow search algorithm in artificial intelligence algorithm is taken to optimize the parameter search of the recurrent neural network and automatically extract the target scene. …”

Scene extraction accuracy of different models. by Ting Wang (16292)

“…Then, the sparrow search algorithm in artificial intelligence algorithm is taken to optimize the parameter search of the recurrent neural network and automatically extract the target scene. …”

YOLOv7 network structure composition diagram. by Ting Wang (16292)

“…Then, the sparrow search algorithm in artificial intelligence algorithm is taken to optimize the parameter search of the recurrent neural network and automatically extract the target scene. …”

ProSAAS is expressed in multiple cell types in a mixed species meta-analysis. by Nicholas Schaffer (21376843)

“…<p>Log-transformed transcriptional counts of proSAAS (<b><i>Red</i></b>); clusterin (CLU, <b><i>Blue</i></b>); and αcrystallin-β (CRYAB, <b><i>Green</i></b>) transcripts in human and mouse studies obtained from ARCHS4, were normalized using the ComBat batch correction algorithm. …”

Test data on the ability to escape local optima. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Summary of the notations. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Comparison of population diversity. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Test data on mining capacity. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Comparison of standard GEP and DGEP. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Test data on population diversity. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Flowchart of the DGEP process. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Comparison of the ability to escape local optima. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

Statistical analysis of DGEP vs. standard GEP. by Kejia Liu (5699651)

“…<div><p>The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. …”

The study flowchart. by Rui Guo (134395)

The modified SarcGraph pipeline. by Saeed Mohammadzadeh (13492285)

High and low immune infiltration subtypes of CAS samples in the GSE43292 cohort distinguished via consensus clustering. by Yi Zhang (9093)

DEGs. by Rui Guo (134395)

The results of fitting the parameters of a synaptic connection based on simulated voltage-clamp recordings. by Máté Mohácsi (20469514)

“…Note that the error function had only a single component in this use case, and therefore only single-objective optimization algorithms were compared.…”

Enrichment analysis and hub gene screening. by Yi Zhang (9093)

“…Red to yellow indicates that genes rank from high to low in the interaction network, with <i>PTPRC</i> being the highest-ranking gene identified via the maximum neighborhood component algorithm. …”

The results of fitting the passive biophysical parameters of a morphologically detailed multi-compartmental model to experimental recordings from a hippocampal pyramidal neuron. by Máté Mohácsi (20469514)

“…<p>The plots in all four panels are analogous to those in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012039#pcbi.1012039.g001" target="_blank">Fig 1</a>. Only single-objective methods were tested in this use case because only a single error function (mean squared difference) was used to compare model outputs to the target data. …”