Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

“…Then the reserve pool parameters of the ESN are optimized using the local and global optimization search capability of IGWO, and the IGWO-ESN network model is constructed, and the processed dataset is used for the training of the remaining life prediction model of the PEMFC, and finally it is compared with the traditional ESN for verification. …”
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Improved aquila optimizer for swarm-based solutions to complex engineering problems by Himanshu Sharma, Krishan Arora, Raghav Mahajan, Syed Immamul Ansarullah, Farhan Amin, Hussain AlSalman

“…Time complexity analysis shows that the best time is 0.00015225 which is better as compared to other algorithms also Wilcoxon ranksum test is carried out to calculate the p-value is less than 0.05 rejecting the null hypothesis. …”
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Single and multi-objective real-time optimisation of an industrial injection moulding process via a Bayesian adaptive design of experiment approach by Mandana Kariminejad, David Tormey, Caitríona Ryan, Christopher O’Hara, Albert Weinert, Marion McAfee

“…The multi-objective optimisation techniques, composite desirability function and Nondominated Sorting Genetic Algorithm (NSGA-II) using the Response Surface Methodology (RSM) model, are compared with the real-time novel ADoE approach. …”
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A Quantum Framework for Combinatorial Optimization Problem over Graphs by Meng Shi, Sai Wu, Ying Li, Gongsheng Yuan, Chang Yao, Gang Chen

“…In this paper, we propose a general quantum algorithm framework searching for approximate solutions to combinatorial optimization problems with linear objective functions. …”
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Reinforcement learning-based alpha-list iterated greedy for production scheduling by Kuo-Ching Ying, Pourya Pourhejazy, Shih-Han Cheng

“…Metaheuristics can benefit from analyzing patterns and regularities in data to perform more effective searches in the solution space. In line with the emerging trend in the optimization literature, this study introduces the Reinforcement-learning-based Alpha-List Iterated Greedy (RAIG) algorithm to contribute to the advances in machine learning-based optimization, notably for solving combinatorial problems. …”
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DGA domain detection and botnet prevention using Q-learning for POMDP by Y. V. Bubnov, N. N. Ivanov

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Comparative analysis of efficacy of different combination therapies of α-receptor blockers and traditional Chinese medicine external therapy in the treatment of chronic prostatitis... by Kaiyu Zhang, Yi Zhang, Shengwei Hong, Yutian Cao, Chengjiang Liu

“…Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy.…”
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Multi-Objective Parameter Optimization of Rotary Screen Coating Process for Structural Plates in Spacecraft by Yanhui Guo, Yanpeng Chen, Peibo Li, Xinfu Chi, Yize Sun

“…The enhanced Levy strategy helps the algorithm to escape local optimizations, increases the population diversity, and possesses dual searching capabilities. …”
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Optimal Multi-Objective Reconfiguration in distribution systems using the Novel Intelligent Water Drops approach by Hajar Bagheri Tolabi, Mohd Hasan Ali

“…The obtained results prove the proposed technique is more accurate than other well known methods such as Genetic Algorithm, Particle Swarm Optimization, and Harmony Search algorithm meanwhile it has an efficient convergence property in compared with other intelligent search algorithms. …”
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Network- and Demand-Driven Initialization Strategy for Enhanced Heuristic in Uncapacitated Facility Location Problem by Jayson Lin, Shuo Yang, Kai Huang, Kun Wang, Sunghoon Jang

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On the equivalence of characteristics and specularity in the construction of traditional and MIMO radars with a parallel view of space based on antenna arrays by B. M. Vovshin, A. A. Pushkov, E. M. Khalturina

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Predicting Optimum Moisture Content by the individual and hybrid approach of machine learning by Yinghui Yang, Yahui Dai, Qunting Yang

“…To further enhance the predictive accuracy of these models, two meta-heuristic optimization techniques—Atom Search Optimization (ASO) and Reptile Search Algorithm (RSA)—are employed. …”
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Forecasting and decision making of firm’s financial indicators based on the SSA-MLP-BPNN model by Xin Xu

“…By comparing the prediction results of SSA-MLP-BP model with other optimization algorithms, it is found that the SSA optimization algorithm performs superiorly in improving the performance of the MLP-BP model, and it is easier to find the global optimal solution, which improves the prediction accuracy of the model. …”
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An Optimization Method for Green Permutation Flow Shop Scheduling Based on Deep Reinforcement Learning and MOEA/D by Yongxin Lu, Yiping Yuan, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…Subsequently, the solutions generated by the DRL-PFSP model are used as the initial population for the MOEA/D, and the proposed job postponement energy-saving strategy is incorporated to enhance the solution effectiveness of the MOEA/D. Finally, by comparing the GDRL-MOEA/D with the MOEA/D, NSGA-II, the marine predators algorithm (MPA), the sparrow search algorithm (SSA), the artificial hummingbird algorithm (AHA), and the seagull optimization algorithm (SOA) through experimental tests, the results demonstrate that the GDRL-MOEA/D has a significant advantage in terms of solution quality.…”
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Effective Modeling of Photovoltaic Modules Using Sailfish Optimizer by Mohammed Bilal Danoune, A. Djafour, Youcef Rehouma, A. Degla, Zied Dress

“…This unique propriety can substantially augment the probability of locating the global optimum as well as accelerating the search process. Moreover, to show the efficacy of the algorithm, the results are compared with some literature techniques such as Salp-Swarm-Optimizer (SSA), Whale Optimization (WOA), Artificial-Bee-Colony (ABC), and Particle-Swarm Optimization (PSO) methods. …”
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A Longitudinal Perspective on Digital Skills for Everyday Life: Measurement and Empirical Evidence by Kiran Kappeler

“…To address these gaps, this article compares self-reported measures of digital skills and knowledge of datafication and algorithmization in everyday internet use and maps the evolution of their relevance for digital everyday life. …”
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A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources by Zihao Wang, Shenhua Wang, Hanwen Ni, Junyin Wang, Jun Zhang

“…Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. …”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

“…To overcome these limitations, a novel Multi-Agent Reinforcement Learning (MARL) algorithm is proposed in this research, combined with Golden Jackal Optimization (GJO). …”
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Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Int... by Min-Young Yu, Hae Young Yoo, Ga In Han, Eun-Jung Kim, Youn-Jung Son

“…Our systematic search yielded 10 retrospective studies, with a total sample size of 89,702 individuals. …”
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An enhanced Walrus Optimizer with opposition-based learning and mutation strategy for data clustering by Laith Abualigah, Saleh Ali Alomari, Mohammad H. Almomani, Raed Abu Zitar, Hazem Migdady, Kashif Saleem, Aseel Smerat, Vaclav Snasel, Absalom E. Ezugwu

“…The effectiveness of IWO is validated through extensive experiments on multiple benchmark clustering datasets and compared against several state-of-the-art metaheuristic algorithms, including PSO, GWO, AOA, and others. …”
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