Braking system model. حسب Honglei Pang (22693724)

الموضوعات:

Vehicle parameters. حسب Honglei Pang (22693724)

الموضوعات:

HIL test results of curved road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. حسب Honglei Pang (22693724)

الموضوعات:

Comparison of average reward values in various simulation scenarios. حسب Honglei Pang (22693724)

الموضوعات:

HIL test results of split-μ road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. حسب Honglei Pang (22693724)

الموضوعات:

Table3_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX حسب Zhen Wang (72451)

"…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …"

Table2_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX حسب Zhen Wang (72451)

"…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …"

Table1_Comprehensive analysis of the progression mechanisms of CRPC and its inhibitor discovery based on machine learning algorithms.XLSX حسب Zhen Wang (72451)

"…Weighted gene coexpression network analysis (WGCNA) and two machine learning algorithms were employed to identify potential biomarkers for CRPC. …"

Metapopulation model notation. حسب Jeffrey Keithley (14626551)

"…We provide a theoretical explanation for this effectiveness by showing that the approximation factor (a measure of how well the algorithmic output for a problem instance compares to its theoretical optimum) of these algorithms depends on the <i>submodularity ratio</i> of the objective function <i>g</i>. …"

Estimates of for each problem instance. حسب Jeffrey Keithley (14626551)

"…We provide a theoretical explanation for this effectiveness by showing that the approximation factor (a measure of how well the algorithmic output for a problem instance compares to its theoretical optimum) of these algorithms depends on the <i>submodularity ratio</i> of the objective function <i>g</i>. …"

Approximation factors for each problem instance. حسب Jeffrey Keithley (14626551)

"…We provide a theoretical explanation for this effectiveness by showing that the approximation factor (a measure of how well the algorithmic output for a problem instance compares to its theoretical optimum) of these algorithms depends on the <i>submodularity ratio</i> of the objective function <i>g</i>. …"

R-squared comparison of test function. حسب 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. …"

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit حسب Gonzalo Colmenarejo (650249)

"…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …"

Results obtained by different algorithms on 23 benchmark functions. حسب Yuqi Xiong (12343771)

الموضوعات:

Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling حسب Giacomo Janson (8138517)

"…This program implements the “modeling by satisfaction of spatial restraints” strategy and its core algorithm has not been altered significantly since the early 1990s. …"

Benchmark functions. حسب Wei Liu (20030)

"…The convergence of SGWO was analyzed by mathematical theory, and the optimization ability of SGWO and the prediction performance of SGWO-Elman were examined using comparative experiments. The results show: (1) the global convergence probability of SGWO was 1, and its process was a finite homogeneous Markov chain with an absorption state; (2) SGWO not only has better optimization performance when solving complex functions of different dimensions, but also when applied to Elman for parameter optimization, SGWO can significantly optimize the network structure and SGWO-Elman has accurate prediction performance.…"

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz حسب Faizan Ali (21689861)

الموضوعات:

Algorithm used for important sampling of the likelihood function. حسب Zhiyong Huang (3620000)

Convergence curves of different algorithms on the benchmark functions. حسب Aihua Guo (13267712)

Schematic diagram of MHSA mechanism. حسب Guofeng Qin (11025170)

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