Corresponding Markov Chain Model representing the probability of quantum state transition over an infinitesimal time step. by Nicholas H. Vitale (20469289)

Steps for obtaining a complete Pareto frontier. by Tao Dong (15551)

Internal cross-validation step of S component in 3Mont. by Miray Unlu Yazici (14792680)

Graphical overview of processing steps. by Stefan Donovan Klimaj (9211901)

Matlab code of a function used in S2 File. by Hiroko Kato Solvang (5718250)

Parameterization of the feature selection algorithm. by Chenyi Zhu (9383370)

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Comparison of metaheuristic algorithm parameterization. by Chenyi Zhu (9383370)

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The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

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Microkinetic Model Fitted with a Genetic Algorithm to Experimental XPS Coverages at High Pressure–CO Hydrogenation on Rh(111) by Mikael Valter-Lithander (18955053)

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Summary of recent and state-of-the-art optimization algorithms. by Mahmood A. Jumaah (22272371)

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Closed-loop step responses of AFR system tuned ImpAO, AO, SMA, MFO and ABC methods. by Davut Izci (15927452)

Flow chart of the analysis steps in this study. by Junjie Su (368807)

The TPC algorithm. by Rahul Biswas (14117086)

Sorting time is nominally similar between automated and manual sorting, but automation enables walk-away functionality. by Diane M. Wiener (1956583)

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The collective motion, collision avoidance, and CMCA score of the VCMCA algorithm, VCMCA algorithm without CA, and random walk over the simulation steps for <i>n</i> = 30 repetitio... by David L. Krongauz (15447260)

Example of an application of functional safety-critical energy optimization reallocation tasks. by Zhiqun Lin (1429501)

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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. …”

Descriptions of the selected CEC 2017 benchmark functions. by ZeSheng Lin (20501356)

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Descriptions of the selected CEC 2005 benchmark functions. by ZeSheng Lin (20501356)

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