Statistical tests of ACC on the regular network. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Statistical tests of APL on the regular network. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Experiment 5: Clustering networks that are only partially clusterable. by Yasamin Tabatabaee (18095491)

Optimal configuration of RC frames considering ultimate and serviceability limit state constraints by Marcela Alejandra Juliani (10449275)

“…Structural analyses are performed by using the MASTAN2 software, taking into account geometric nonlinearities and a simplified physical nonlinearity method. The objective function considers the cost of concrete, reinforcement and formwork, and the optimization problems are solved by genetic algorithms. …”

Testing algorithm for modified 2-tiered approaches to Lyme disease diagnosis. by Richard Porwancher (11413931)

Genetic algorithm meta-parameters. by Larasmoyo Nugroho (18078260)

“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”

The entity relationship of DDPG algorithm. by Larasmoyo Nugroho (18078260)

“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”

Post scan feature estimates and confidence ratings. by Sam Hall-McMaster (10343795)

Decoding results. by Sam Hall-McMaster (10343795)

Decoding evidence for feature triplets on test tasks. by Sam Hall-McMaster (10343795)

“…<p>Another neural hypothesis formulated based on the SF&GPI algorithm is that feature triplets associated with the optimal training policies should be reactivated on test trials. …”

Codes for high-order analytical continuation algorithms based on direct derivation and recursion methods by Jian Ma (19747060)

“…The optimal order of the analytical continuation algorithm is contingent upon the noise level of gravity data. …”

Performance comparison of four optimization methods. by Xuexing Du (20624042)

“…(B) Relative error convergence of four optimization methods, plotted as a function of the logarithm of iterations. …”

The architecture of LSTM cell. by Asmaa Ahmed Awad (16726315)

SBH17: Benchmark Database of Barrier Heights for Dissociative Chemisorption on Transition Metal Surfaces by T. Tchakoua (7202804)

“…The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. …”

Supporting data for "Two Essays on Consumers' Relative Preference for Algorithm-based Versus Human Recommendations" by Xunchang Fang (9070241)

“…<p>Recommendation systems, the information filtering tools that provide options of products or services to customers, are powered by programmed algorithms or human experts. Both algorithm-based and human recommendation systems are widely adopted by companies to help consumers make optimal purchasing decisions amid their access to product information. …”

Closed search (±5ppm) comparison against Crux and MSFragger using real-world data from PRIDE repository PXD000612 (top), PXD009861 (middle), and PXD001468 (bottom). by Muhammad Usman Tariq (11022141)

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Training parameters for SpeCollate. by Muhammad Usman Tariq (11022141)

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Peptides. by Muhammad Usman Tariq (11022141)

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Fig 9 - by Muhammad Usman Tariq (11022141)

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UMAP. by Muhammad Usman Tariq (11022141)

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