Cost-Effective Flight Sequencing and Gate Assignment Considering Transfer Time under Pandemic Conditions by Mei Xiao, Yu Liu, Steven Chien, Ching-Jung Ting

“…The objective of this study is to minimize the total cost by optimizing the flight sequencing and gate assignment and by considering the realistic transfer delay under pandemic situations. A genetic algorithm with an elite selection strategy is developed to search for the optimal solution, which significantly reduces the total cost by 25% compared with that under existing operations, and the relations between optimized solutions and various model parameters are explored.…”
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Optimal Integration of Multiple Shunt Reactive Compensators in Radial Distribution Systems for Loss Reduction using Modified Mountain Gazelle Optimizer (MMGO) by A. F. S. Yussif, E. Twumasi, E. A. Frimpong

“…This approach reduces the search space and improves the efficiency of the optimization process. …”
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Optimized Trust Prediction and Multi-Criteria Framework for Task and Data Collector Selection Using Deep Learning in Ubiquitous Environments by Ahmed A. A. Gad-Elrab

“…Natural optimization algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulating Annulling (SA), and Cuckoo Search are employed to fine-tune hyperparameters of the predictive models. …”
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A Time Delay Prediction Model of 5G Users Based on the BiLSTM Neural Network Optimized by APSO-SD by Xiaozheng Dang, Di He, Cong Xie

“…Then, an adaptive particle swarm optimization algorithm based on a search perturbation mechanism and differential enhancement strategy (APSO-SD) is proposed for the parameters’ optimization of BiLSTM neural networks. …”
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Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network by Qiuxia Fan, Xinqi Zhang, Zhuang Wen, Lei Xu, Qianqian Zhang

“…First, the Latin hypercube sampling method and the Levy flight method are introduced into the snake optimization (SO) algorithm, which enhances the global search ability and diversity preservation ability of the SO algorithm and effectively solves the common overfitting and local optimal problems in the training process of the gradient descent method. …”
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Hybrid Blockchain-Based Multi-Operator Resource Sharing and SLA Management by Sidra Tul Muntaha, Qasim Z. Ahmed, Faheem A. Khan, Zaharias D. Zaharis, Pavlos I. Lazaridis

“…For the upper-layer game, we determine the pricing strategies of seller MNOs using Pattern Search Algorithm (PSA), Genetic Algorithm (GA), and Fmincon, comparing their performances. …”
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Extracting fluorescent reporter time courses of cell lineages from high-throughput microscopy at low temporal resolution. by Mike J Downey, Danuta M Jeziorska, Sascha Ott, T Katherine Tamai, Georgy Koentges, Keith W Vance, Till Bretschneider

“…In our approach, cell nuclei are identified using Hoechst, and a characteristic drop in Hoechst fluorescence helps to detect dividing cells. We first compare the efficiency and accuracy of different segmentation methods and then present a statistical scoring algorithm for cell tracking, which draws on the combination of various features, such as nuclear intensity, area or shape, and importantly, dynamic changes thereof. …”
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Physical-Abstract Bidirectional-Guided Learning for High-Resolution Radar Target Recognition by Yuying Zhu, Yinan Zhao, Zhaoting Liu, Meilin He

“…Second, a soft-threshold based target region extraction algorithm is developed, significantly reducing the parameter search space. …”
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Hierarchical guided manta ray foraging optimization for global continuous optimization problems and parameter estimation of solar photovoltaic models by Zhentao Tang, Kaiyu Wang, Lan Zhuang, Mingxin Zhu, Yongxuan Yao, Huiqin Chen, Jing Li, Xiaoxiang Wu, Shangce Gao

“…To validate the effectiveness of HGMRFO, we compared it with seven state-of-the-art algorithms on 29 IEEE CEC2017 benchmark functions, achieving an average win rate of 73.15%. …”
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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

“…Moreover, incorporating the gradient information of the traffic flow in the optimization search algorithm can further improve the solution performance. …”
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Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller by Monika Gupta, P. M. Tiwari, R. K. Viral, Ashish Shrivastava, Basem Abu Zneid, Iryna Hunko

“…The proposed GWO-PID method overcomes these limitations by leveraging the GWO algorithm’s global search capability to dynamically optimize the PID gains (Kp, Ki, Kd) based on a composite fitness function that minimizes Mean Squared Error (MSE) and THD. …”
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Grey Wolf Optimizer Termodifikasi Menggunakan Chaotic Uniform Initialization Untuk Estimasi Effort Cocomo by Ardiansyah, Sri Handayaningsih, Deva Fathurrizki

“…The proposed method is then compared with the standard GWO algorithm and a current GWO variant. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Therefore, the BWO is proposed to optimize these parameters, with sample entropy and error reconstruction serving as key fitness function indicators. Compared to other optimization algorithms such as genetic algorithm (GA) and whale optimization algorithm (WOA), the BWO algorithm demonstrates significant per-formance, with faster running speed, stronger stability, and greater robustness. …”
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Research on the Influence of Composite Modification Design on Tooth Surface Wear of Transmission Gears by Bai Xiaoning, Li Yonghua, Wang Denglong, Zhang Dongxu

“…Moreover, the sparrow search algorithm (SSA) improved by the Sine chaotic mapping is used to optimize the back propagation (BP) neural network, and the accuracy of Sine-SSA-BP is verified by comparing it with the traditional BP, so as to characterize the implicit relationship between the modification parameters and the gear wear. …”
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Design and Simulation of an Infinite Impulse Response Filter with Memristor by Ahmad Maleki, Vahid Rashtchi, Jalil Mazloum

“…During running an advanced search algorithm, the memristor values ââwere set at six, seven, and eight bits of resolution; these values cause memristors have the lowest error rate in generating coefficients. …”
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Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis by Suruthy Sivanathan, Ting Hu

“…The multiscale interactome network is a computational tool that can identify potential therapeutic candidates by comparing mechanisms of the drug and disease. Communities that could be potentially experimentally validated are detected in the multiscale interactome network using the algorithm CRank. …”
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A corrective direction particle swarm optimization for large-scale multi-objective optimization by Weichao Chen, Ziyang Li, Xue Li

“…Moreover, a novel exploration mechanism is used by the elite particles, which spreads the exploration across each dimension of the decision variables and adaptively adjusts the velocity components in each dimension to enhance the algorithm’s performance further. Experimental results show that our proposed CDPSO exhibits strong competitiveness compared to the other nine state-of-the-art algorithms when tested on both benchmark problems and real-world problems.…”
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A Two-Step Approach for Airborne Delay Minimization Using Pretactical Conflict Resolution in Free-Route Airspace by Ramazan Kursat Cecen, Cem Cetek

“…To obtain feasible solutions, genetic algorithm and tabu search algorithms are implemented in the first step. …”
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An Optimized 1-D CNN-LSTM Approach for Fault Diagnosis of Rolling Bearings Considering Epistemic Uncertainty by Onur Can Kalay

“…From this standpoint, the present study combined a 1-D convolutional neural network (1-D CNN) with a long short-term memory (LSTM) algorithm for classifying different ball-bearing health conditions. …”
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Dynamic UAV Task Allocation and Path Planning with Energy Management Using Adaptive PSO in Rolling Horizon Framework by Zhen Han, Weian Guo

“…We introduce an enhanced Particle Swarm Optimization (PSO) algorithm, incorporating adaptive perturbation strategies and a local search mechanism based on simulated annealing, to optimize UAV task assignments and routes. …”
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