HV comparison of QLNSGA-II and baseline algorithms on real-world multi-objective problems (RWMOP). The best value in each row is highlighted in bold. by Zhongfeng Li (3965060)

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<b>Optimized Artificial Neural Network-Based Mathematical Model and Software Application for Predicting Raw Mix Lime Saturation Factor for High-Quality Cement Production</b> by LATEEF ADAMOLEKUN (17918045)

Model performance comparison based on <i>R²</i>, <i>RMSE</i>, <i>MAE</i> and <i>Adjusted R².</i> by Fanlong Zeng (1968649)

Flowchart of the CDOS (Conjugate Direction with Orthogonal Shift) Algorithm. by Hoang Minh Dang (22208489)

Comparing ROSE and the NBI algorithms with varying sizes of the Pareto set/levels of recursion of the ROSE algorithm when applied to the BIOBJ problem: (a) 5 points/two recursion l... by Ihab Hashem (21156806)

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Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

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The weight optimization process. by Guomei Cui (20721578)

“…The dataset covers multiple tests of multiple athletes, ensuring the diversity of samples. Secondly, an optimized machine learning algorithm based on decision tree is adopted. …”

Overnight technician routing and scheduling problem with time windows and balanced workloads: a bi-objective zebra optimization algorithm by Abolfazl Gharaei (21803416)

“…The performance evaluation and validation results revealed that the proposed ML-based BOZOA provides very good performance in solving TRSPTWs at a variety of scales with respect to the optimality criteria, including, number of taken iterations, infeasibility, optimality error and complementarity compared with both an exact solver and two inspired algorithms from ZOA.…”

Optimized fuzzy rules illustration. by Yanyan Dong (1304145)

“…The collected inputs are explored using fuzzy systems that use the multivariate and salp optimization algorithm at every step to improve the overall system efficiency. …”

Optimal ovarian cancer BNs learned by CausNet and CausNet-partial. by Nand Sharma (21519845)

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Optimal parameters for each machine learning model are selected through the grid search. by Wonseok Jeong (5777678)

Final Path Smoothing Optimization: Step-by-step results of smoothing optimization applied to the adjusted path. It shows how the path becomes more continuous and efficient through... by Yan Chen (4308)

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Data and Scripts for 'Application of Multidimensional Cognitive Ability Tests in Computer-Assisted Diagnosis of Attention-Deficit/Hyperactivity Disorder and Its Subtypes in Children: Based on A Genetic Algorithm Optimized Back-Propagation Neural Network Predictive Model' by Wang (20310746)

“…Using <a href="" target="_blank">multidimensional cognitive ability tests</a> and a <a href="" target="_blank">back-propagation neural network</a> optimized by a genetic algorithm, this study developed a computer-aided diagnostic model to distinguish children with attention-deficit/hyperactivity disorder and its specific subtypes. …”

Comparison of the cutting plans by Dijkstra’s, WACO, ACO, rkGa, and APOA algorithms. by Chattriya Jariyavajee (12822281)

Comparison of the results achieved by the algorithm with the best <i>F</i>2 score against the results presented in [9]. by André G. Coimbra (21354135)

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BM3D algorithmic process. by Xiyu Zheng (21703063)

Solving the three-objectives numerical problem from [36] using a generalized version of the ROSE algorithm for three-objective problems: (a) The Pareto front representation corresp... by Ihab Hashem (21156806)

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Steady-State Simulation Performance at 1000 <i>W</i>/<i>m</i>² (a) Conventional P&O Algorithm, (b) Proposed SF Algorithm. by Rana Ahmed (4923127)

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Algorithm for MFISTA-VA [30]. by Faisal Najeeb (20542714)

“…GRASP uses Temporal Total Variation (TV) norm as a sparsity transform to promote sparsity among multi-coil MRI data and Nonlinear Conjugate Gradient (NL-CG) algorithm to obtain an optimal solution. Additionally, GRASP uses NUFFT gridding to map Golden-angle-radial data to Cartesian grid before NL-CG based CS reconstruction. …”

Hyperparameter settings for DQN-based scheduling. by Yousef Sanjalawe (22216626)