Results 61 to 70 of about 24,415 (308)

A hybrid framework based on genetic algorithm and simulated annealing for RNA structure prediction with pseudoknots

Journal of King Saud University: Computer and Information Sciences, 2022
RNA structure prediction with pseudoknots is an NP-complete problem, in which an optimal RNA structure with minimum energy is to be computed. In past decades, several methods have been developed to predict RNA structure with pseudoknots.
Md. Shahidul Islam, Md. Rafiqul Islam
doaj   +1 more source

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza, Raja Muhammad Afzal, Felipe Gomes Camacho, Nader Mahinpey   +3 more
wiley   +1 more source

MTS-PRO2SAT: Hybrid Mutation Tabu Search Algorithm in Optimizing Probabilistic 2 Satisfiability in Discrete Hopfield Neural Network

Mathematics
The primary objective of introducing metaheuristic algorithms into traditional systematic logic is to minimize the cost function. However, there is a lack of research on the impact of introducing metaheuristic algorithms on the cost function under ...
Ju Chen, Yuan Gao, Mohd Shareduwan Mohd Kasihmuddin, Chengfeng Zheng, Nurul Atiqah Romli, Mohd. Asyraf Mansor, Nur Ezlin Zamri, Chuanbiao When   +7 more
doaj   +1 more source

Comparison of recent metaheuristic optimization algorithms to solve the SHE optimization problem in MLI

, 2022
Multilevel inverters (MLIs) are one of the most popular topics of power electronics. Selective harmonic elimination (SHE) method is used to eliminate low-order harmonics in the MLI output voltage by determining the optimum switching angles.
Mirjalili, S, Ürgün, S, Yiğit, H
core   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Metaheuristics for pharmacometrics

CPT: Pharmacometrics & Systems Pharmacology, 2021
Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature‐inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be ...
Seongho Kim, Andrew C. Hooker, Yu Shi, Grace Hyun J. Kim, Weng Kee Wong   +4 more
doaj   +1 more source

Explainable hybrid stacking ensemble method for hard rock pillar stability prediction and engineering applications

Deep Underground Science and Engineering, EarlyView.
This research proposes an interpretable hybrid stacking ensemble framework, optimized by the Sparrow Search Algorithm, to enhance hard rock pillar stability prediction. By integrating six machine learning models—k‐nearest neighbors, support vector machines, random forests, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, and Light Gradient ...
Ning Wang, Guoyan Zhao, Meng Wang, Taraka Pattela   +3 more
wiley   +1 more source

An improved African vultures optimization algorithm based on tent chaotic mapping and time-varying mechanism.

PLoS ONE, 2021
Metaheuristic optimization algorithms are one of the most effective methods for solving complex engineering problems. However, the performance of a metaheuristic algorithm is related to its exploration ability and exploitation ability.
Jiahao Fan, Ying Li, Tan Wang
doaj   +1 more source

Metaheuristic Algorithms in Optimal Design of Engineering Problems

Metaheuristic optimization algorithms (MOAs) are widely used to optimize the design process of engineering problems [...
Łukasz Knypiński, Ramesh Devarapalli, Marcin Kamiński   +2 more
core   +1 more source

Comparative Assessment and Benchmarking of Metaheuristic Algorithms for Dynamic Photovoltaic Array Reconfiguration Under Diverse Shading Environments

Energy Science &Engineering, EarlyView.
ABSTRACT The solar photovoltaic (PV) installations, which are essential for renewable energy systems, are vulnerable to partial shading, resulting in considerable power losses and operational inefficiencies. The dynamic reconfiguration of PV arrays has become an effective strategy to mitigate these effects by adaptively modifying the array topology to ...
Manoharan Premkumar, Ravichandran Sowmya, Jagarapu S. V. Siva Kumar, Mustafa Abdullah   +3 more
wiley   +1 more source