A Practical Algorithm to Solve the Near-Congruence Problem for Rigid Molecules and Clusters حسب José Manuel Vásquez-Pérez (12843737)

"…We present an improved algorithm to solve the near-congruence problem for rigid molecules and clusters based on the iterative application of assignment and alignment steps with biased Euclidean costs. …"

Library of the 55 different classification and regression machine-learning algorithms used by the ensemble predictor SuperLearner (SL.library) in the CBDA 2.0 implementation. حسب Simeone Marino (81051)

MSE for ILSTM algorithm in binary classification. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …"

RosettaAMRLD: A Reaction-Driven Approach for Structure-Based Drug Design from Combinatorial Libraries with Monte Carlo Metropolis Algorithms حسب Yidan Tang (6623693)

"…The Rosetta automated Monte Carlo reaction-based ligand design (RosettaAMRLD) integrates a Monte Carlo Metropolis (MCM) algorithm and reaction-driven molecule proposal to enhance structure-based <i>de novo</i> drug discovery. …"

Comparison of ranks for classification algorithms across performance metrics. حسب Stephen R. Piccolo (8367780)

Tradeoff between execution time and predictive performance for classification algorithms. حسب Stephen R. Piccolo (8367780)

Relative classification performance per combination of feature-selection and classification algorithm. حسب Stephen R. Piccolo (8367780)

Relative performance of classification algorithms using gene-expression and clinical predictors and performing feature selection. حسب Stephen R. Piccolo (8367780)

Homomorphic binary tree. حسب Jianhua He (341366)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm حسب Hussein Ali Bardan (21976208)

"…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …"

Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF حسب Maya Khatun (7437011)

"…While generating the trial geometries, a Tabu list is used for storing the information of the already used trial geometries to avoid using the similar trial geometries. …"

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing hyperparameter optimization. حسب Stephen R. Piccolo (8367780)

The flowchart of the proposed algorithm. حسب Muhammad Ayyaz Sheikh (18610943)

"…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …"

Flat optimization method. حسب Nisha Ann Viswan (20371285)

Summary of predictive performance per dataset when using gene-expression predictors. حسب Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using clinical predictors. حسب Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors. حسب Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing feature selection. حسب Stephen R. Piccolo (8367780)

Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf حسب Georg Hahn (12530469)

"…<p>We are interested in benchmarking both quantum annealing and classical algorithms for minimizing quadratic unconstrained binary optimization (QUBO) problems. …"

Datasets and their properties. حسب Olaide N. Oyelade (14047002)

"…In addition, we designed nested transfer (NT) functions and investigated the influence of the function on the level-1 optimizer. The binary Ebola optimization search algorithm (BEOSA) is applied for the level-1 mutation, while the simulated annealing (SA) and firefly (FFA) algorithms are investigated for the level-2 optimizer. …"