A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

-value on CEC2022 (dim = 20). by Yuqi Xiong (12343771)

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Precision elimination strategy. by Yuqi Xiong (12343771)

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Results of low-light image enhancement test. by Yuqi Xiong (12343771)

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Evaluation metrics obtained by SBOA and MESBOA. by Yuqi Xiong (12343771)

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Lens imaging opposition-based learning. by Yuqi Xiong (12343771)

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Data_Sheet_1_Modified Particle Swarm Optimization Algorithms for the Generation of Stable Structures of Carbon Clusters, Cn (n = 3–6, 10).doc by Gourhari Jana (4015469)

“…<p>Particle Swarm Optimization (PSO), a population based technique for stochastic search in a multidimensional space, has so far been employed successfully for solving a variety of optimization problems including many multifaceted problems, where other popular methods like steepest descent, gradient descent, conjugate gradient, Newton method, etc. do not give satisfactory results. Herein, we propose a modified PSO algorithm for unbiased global minima search by integrating with density functional theory which turns out to be superior to the other evolutionary methods such as simulated annealing, basin hopping and genetic algorithm. …”

Data_Sheet_2_Modified Particle Swarm Optimization Algorithms for the Generation of Stable Structures of Carbon Clusters, Cn (n = 3–6, 10).doc by Gourhari Jana (4015469)

“…<p>Particle Swarm Optimization (PSO), a population based technique for stochastic search in a multidimensional space, has so far been employed successfully for solving a variety of optimization problems including many multifaceted problems, where other popular methods like steepest descent, gradient descent, conjugate gradient, Newton method, etc. do not give satisfactory results. Herein, we propose a modified PSO algorithm for unbiased global minima search by integrating with density functional theory which turns out to be superior to the other evolutionary methods such as simulated annealing, basin hopping and genetic algorithm. …”

Reward function related parameters. by Honglei Pang (22693724)

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Fuzzy membership function for yaw with . by Yasir Mehmood (744452)

Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. …”

Details the DLKA structure, which includes the DLKA-Attention module and the FFN module. The DLKA-Attention module mainly consists of the DLKA module, which comprises deformable de... by Xunqian Xu (21261899)

Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

Fuzzy membership function for the longitudinal velocity with s. by Yasir Mehmood (744452)

3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

Search-based testing (Genetic Algorithm) - Chapter 11 of the book "Software Testing Automation" by Saeed Parsa (13893726)

“…</p> <p><br></p> <p>3. Algorithm</p> <p>Below is the main body of the test data generator program:</p> <p>  </p> <p>the main body of a Python program to generate test data for Python functions.…”

Four typical nonlinear transformation function curves. by Yuqi Xiong (12343771)

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3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

Information of nodes and pipes of NYN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

The topology of the NYN. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”