Scatter diagram of different principal elements. حسب Jizhong Wang (7441697)

Performance of machine learning algorithms. حسب Wenxue Liu (6877754)

ML algorithms in cyber security. حسب Abdullah Asım Yılmaz (20715311)

Convergence curve of the DBO algorithm. حسب Ma Haohao (22177538)

"…The improved Dung Beetle Optimization algorithm, Back Propagation Neural Network, Finite Element Analysis, and Response Surface Methodology provide a strong guarantee for the selection of robot polishing process parameters. …"

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33]. (b) An alternating active-phase... حسب Zhao Li (300229)

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). حسب Johannes Weyer (13392175)

Element model generation method with geometric distribution errors حسب Yiqi Liu (21357815)

"…The product surface geometric distribution error is directly attached to the element nodes of the product ideal element model using the error surface reconstruction method and the replacement algorithm of the element node vector height based on the product’s point cloud data. …"

Comparison of results based on CycleGAN method. حسب Xiaojun Wang (50332)

الموضوعات:

Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. حسب Tomokaze Shiratori (9635271)

الموضوعات:

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. حسب Abdullah Asım Yılmaz (20715311)

Multi-material topology optimization using scaled boundary finite element method حسب Mohammed Saif Zamiruddin Siddiqui (22384884)

"…SBFEM is implemented and its performance is tested across different density interpolation-based MMTO methods: the Alternating Active-Phase (AAP) algorithm, SIMP with mapping based interpolation, and polygonal mesh based MMTO, PolyMat which uses Discrete Material Optimization (DMO) combined with Zhang–Paulino–Ramos (ZPR) update scheme. …"

Computation time as a function of the sample size on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

الموضوعات:

Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

الموضوعات:

Computation time as a function of the sample size on the random graph dataset. حسب Tomokaze Shiratori (9635271)

الموضوعات:

F1 score of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

الموضوعات:

Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

الموضوعات:

Examples of ground-truth graph structures with (<i>p</i>, <i>n</i>_≠0) = (10, 10). حسب Tomokaze Shiratori (9635271)

الموضوعات:

Number of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

الموضوعات:

Number of edges selected through cross-validation on the random graph dataset. حسب Tomokaze Shiratori (9635271)

الموضوعات:

Graphs of the regularization terms. حسب Tomokaze Shiratori (9635271)

الموضوعات: