Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010) by Ghalayini, Iman Adnan

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Scatter search for protein structure prediction. (c2008) by Kehyayan, Christine Houry

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Heuristic Algorithm for Obtaining Approximate Optimum Stratification With Mixture of Ratio and Product Estimators by S. E. H. Rizvi (22052105)

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Design of acoustic absorbing metasurfaces using a data-driven approach by Hamza Baali (14603380)

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Bird’s Eye View feature selection for high-dimensional data by Samir Brahim Belhaouari (16855434)

“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”

Using genetic algorithms to optimize software quality estimation models by Azar, Danielle

“…Most such models are constructed using statistical or machine learning techniques. …”
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Detection of statistically significant network changes in complex biological networks by Raghvendra Mall (581171)

“…</p><h3>Methods</h3><p dir="ltr">In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. The proposed procedure exploits a more effective model selection criteria to generate <i>p</i>-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. …”

A hybrid heuristic approach to optimize rule based software quality estimation models. (c2008) by Korkmaz, Rita

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Salp swarm algorithm: survey, analysis, and new applications by Abualigah, Laith

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Arithmetic optimization algorithm: a review and analysis by Abualigah, Laith

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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy by Haitao Xu (435549)

“…This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. Combining statistical and ranking analyses confirms that the Levenberg–Marquardt (LM) is the most efficient optimization technique for training the MLPNN model. …”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

Applications of Kepler Algorithm-Based Controller for DC Chopper: Towards Stabilizing Wind Driven PMSGs under Nonstandard Voltages by Basiony Shehata Atia (21398774)

Social spider optimization algorithm: survey and new applications by Abualigah, Laith

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A New Penalty Function Algorithm For Convex Quadratic Programming by Bendaya, M.

“…In this paper, we develop an exterior point algorithm for convex quadratic programming using a penalty function approach. …”
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Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review by Francisco Monteiro-Guerra (16864122)

A Scatter search algorithm for exam scheduling. (c2006) by Isahakian, Vatche Raffi

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Cohen syndrome and early-onset epileptic encephalopathy in male triplets: two disease-causing mutations in VPS13B and NAPB by Alice AbdelAleem (17753799)

“…<p dir="ltr">Cohen syndrome (CS) is a rare multisystem autosomal recessive disorder associated with mutations in VPS13B (vacuolar protein sorting homolog 13B). The NAPB-related neurodevelopmental disorder is characterized mainly by early-onset epileptic encephalopathy (EOEE) and is associated with mutations in NAPB that encodes for SNAP-beta (soluble NSF attachment protein beta). …”

Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms by Humna Khan (17541972)

“…Statistical parameters i.e., mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²), were used to assess the prediction accuracy of the models. …”

A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…The simulation results show good tracking performance in the presence of noise with erroneous model parameters and noise statistics. An open-loop control is also proposed to improve the tracking rate of the proposed ILC algorithms.…”
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