Controlling parameter values of the tested algorithms. حسب WanRu Zhao (18980374)

الموضوعات:

Concept of the ISEEML classifier and its main characteristics. حسب Artem S. Kasianov (8783363)

ANOVA was performed to test the differences between the algorithms for each indicator. حسب Jihui Hu (19812736)

الموضوعات:

The results of Wilcoxon’s rank-sum test between DEGH and its variants with different <i>F</i> values. حسب Xuxu Zhong (10099054)

DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf حسب Florian Barkmann (15152004)

"…</p>Approach<p>Within the open-source inverse planning toolkit matRad, we implement a prototypical algorithmic framework for superiorization using the well-established Agmon, Motzkin, and Schoenberg (AMS) feasibility-seeking projection algorithm and common nonlinear dose optimization objective functions. …"

DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf حسب Florian Barkmann (15152004)

"…</p>Approach<p>Within the open-source inverse planning toolkit matRad, we implement a prototypical algorithmic framework for superiorization using the well-established Agmon, Motzkin, and Schoenberg (AMS) feasibility-seeking projection algorithm and common nonlinear dose optimization objective functions. …"

DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf حسب Florian Barkmann (15152004)

"…</p>Approach<p>Within the open-source inverse planning toolkit matRad, we implement a prototypical algorithmic framework for superiorization using the well-established Agmon, Motzkin, and Schoenberg (AMS) feasibility-seeking projection algorithm and common nonlinear dose optimization objective functions. …"

CNN’s optimal hyperparameters utilizing the APSO-WOA-CNN algorithm. حسب Ahmed Bahaa (12887063)

الموضوعات:

APSO–WOA–CNN and FNN algorithms’ accuracy training sets. حسب Ahmed Bahaa (12887063)

الموضوعات:

APSO–WOA–CNN and FNN algorithms’ accuracy validation sets. حسب Ahmed Bahaa (12887063)

الموضوعات:

Evaluation information for eight different denoising algorithms. حسب Wuyi Li (2984439)

Enhanced USV path planning through integrated Bi-RRT and DWA algorithms considering environmental factors حسب Yanghua Zhou (20449441)

"…Furthermore, the evaluation function of the DWA algorithm undergoes enhancements, incorporating elements from heuristic functions within the A* algorithm and radar-based assessment of search range. …"

The distribution function graphs of prediction errors for CLPREM model and its comparative models in three different environments, as well as the root mean square error of predicti... حسب Xiaorui Wu (8322705)

Function convergence curve. حسب Guilin Yang (583364)

"…Introducing nonlinear convergence factors based on positive cut functions to changing the convergence of algorithms, the early survey capabilities and later development capabilities of the algorithm are balanced. …"

Sinusoidal chaotic map and its variant. حسب Yanqin Fan (7515125)

Pair Potentials as Machine Learning Features حسب Jun Pei (1765720)

"…Finally, the importance of the RF algorithm and force field parameters were also tested and the comparison results suggest that both the RF algorithm and force field potentials are important with the ML scoring function achieving its best performance only by combining them together. …"

Pair Potentials as Machine Learning Features حسب Jun Pei (1765720)

"…Finally, the importance of the RF algorithm and force field parameters were also tested and the comparison results suggest that both the RF algorithm and force field potentials are important with the ML scoring function achieving its best performance only by combining them together. …"

Pair Potentials as Machine Learning Features حسب Jun Pei (1765720)

"…Finally, the importance of the RF algorithm and force field parameters were also tested and the comparison results suggest that both the RF algorithm and force field potentials are important with the ML scoring function achieving its best performance only by combining them together. …"

The phase-field function for three different network configurations considered in this work. حسب Martina Bukač (20161460)

Idea of the search for a domain/motif within the range from 1 to W positions (in the window) instead of an only predetermined position. حسب Alexander V. Spirov (11302085)