Lévy Flight Shuffle Frog Leaping Algorithm Based on Differential Perturbation and Quasi-Newton Search by Xinming Zhang, Zihao Fu, Haiyan Chen, Wentao Mao, Shangwang Liu, Guoqi Liu

“…Finally, quasi-Newton local search is integrated into DLSFLA near the end of the algorithm to improve the convergence speed. Experimental results on the complex functions from CEC-2014 show that DQLSFLA’s convergence quality and optimization efficiency are much better than LSFLA’s and that compared with quite a few other state-of-the-art algorithms, DQLSFLA has better performance. …”
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Federated learning and GWO-enabled consumer-centric healthcare internet of things for pancreatic tumour by Nuha Alruwais, Ghada Moh. Samir Elhessewi, Muhammad Kashif Saeed, Menwa Alshammeri, Othman Alrusaini, Abdulwhab Alkharashi, Samah Al Zanin, Yahia Said

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A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading by Mohammed Taha Kaaitan, Rashid Ali Fayadh, Zuhair S. AL-sagar, Salam J. Yaqoob, Mohit Bajaj, Mebratu Sintie Geremew

“…Performance evaluation against benchmark algorithms—Perturb & Observe (P&O), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—revealed that STOA consistently outperformed its counterparts. …”
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IECO: an improved educational competition optimizer for state-of-the-art engineering optimization by Xiaojie Tang, Junbo Jacob Lian, Ling Ma, Xincan Wu, Rui Zhong, Yujun Zhang, Huiling Chen

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Binary Secretary Bird Optimization Clustering by Novel Fitness Function Based on Voronoi Diagram in Wireless Sensor Networks by Mohammed Abdulkareem, Hadi S. Aghdasi, Pedram Salehpour, Mina Zolfy

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Q-learning-based exponential distribution optimizer with multi-strategy guidance for solving engineering design problems and robot path planning by Fengbin Wu, Shaobo Li, Junxing Zhang, Liya Yu, Xuan Xiong, Libang Wu

“…Finally, a Q-learning-based switching parameter adaptive mechanism improves the adaptability of the algorithm under different conditions. The QMEDO’s performance was verified on the Institute of Electrical and Electronics Engineers (IEEE) Congress on Evolutionary Computation (CEC) 2020 and 2022 test functions. …”
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Algorithms to reconstruct past indels: The deletion-only parsimony problem. by Jordan Moutet, Eric Rivals, Fabio Pardi

“…When sequences can only undergo substitutions, optimal reconstructions can be efficiently computed using well-known algorithms. …”
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Computing the Mean-Variance-Sustainability Nondominated Surface by ev-MOGA by A. Garcia-Bernabeu, J. V. Salcedo, A. Hilario, D. Pla-Santamaria, Juan M. Herrero

“…For this purpose, new computational methods for optimizing this complex multiobjective problem are needed. …”
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Leveraging explainable artificial intelligence for early detection and mitigation of cyber threat in large-scale network environments by G. Nalinipriya, S. Rama Sree, K. Radhika, E. Laxmi Lydia, Faten Khalid Karim, Mohamad Khairi Ishak, Samih M. Mostafa

“…Initially, the normalization is performed using Min-max normalization to standardize the data. The Mayfly Optimization Algorithm (MOA) is then utilized for feature selection, effectively mitigating computational complexity. …”
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Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications by Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique

“…Neuromorphic Continual Learning (NCL) appears as an emerging solution, by leveraging the principles of Spiking Neural Networks (SNNs) and their inherent advantages (e.g., sparse spike-driven operations and bio-plausible learning rules) for improving energy efficiency and performance, thereby enabling efficient CL algorithms (e.g., unsupervised learning approach) executed in dynamically-changed environments with resource-constrained computing systems. …”
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Application of Signal Processing Tools for Fault Diagnosis in Induction Motors-A Review-Part II by J. J. Faiz, A. M. Takbash, E. Mazaheri-Tehrani

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Towards solving NLP tasks with optimal transport loss by Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria

“…Incorporating such information in the computations of the probability divergence can facilitate the model’s learning dynamics.In this work, we study an under-explored loss function in NLP — Wasserstein Optimal Transport (OT) — which takes label coordinates into account and thus allows the learning algorithm to incorporate inter-label relations. …”
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Research on the Capability Maturity Evaluation of Intelligent Manufacturing Based on Firefly Algorithm, Sparrow Search Algorithm, and BP Neural Network by Li Shi, Xuehong Ding, Min Li, Yuan Liu

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Dynamic optimization of solar DG and shunt capacitor placement to mitigate the impact of EV charging stations on power distribution network by T. Yuvaraj, M. Thirumalai, T.D. Suresh, Sudhakar Babu Thanikanti, Mohammad Khishe

“…Simulation results confirm the superior performance of QRSMA in improving voltage profiles, reducing power losses, and achieving better computational efficiency compared to conventional optimization algorithms. …”
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Internet traffic data recovery via a low-rank spatio-temporal regularized optimization approach without d-th order T-SVD by Yuxuan Duan, Chen Ling, Jinjie Liu, Xinmin Yang

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Hybrid lion and exponential PSO-based metaheuristic clustering approach for efficient dynamic data stream management by M. Ananthi, K. Valarmathi, A. Ramathilagam, R. Praveen

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IPO: An Improved Parrot Optimizer for Global Optimization and Multilayer Perceptron Classification Problems by Fang Li, Congteng Dai, Abdelazim G. Hussien, Rong Zheng

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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…Experimental findings indicate that the P-BTLBO algorithm surpasses conventional optimization methods, including TLBO and PSO, regarding classification accuracy, feature subset size, and computational efficiency. …”
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An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…In this work, we propose a computational fluid dynamics (CFD), machine learning (ML), and an artificial intelligence (AI) based computational framework for hemodynamics simulation of couple-stressed hybrid nano-integrated blood flow through parallel plates under external squeezing. …”
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COMPARATIVE ANALYSIS OF COLORING ALGORITHMS FOR ORDINARY WEIGHTED GRAPH by Andrey Sergeyevich Merzlenko, Valery Grigoryevich Kobak

“…All algorithms are considered with examples. To evaluate the algorithm efficiency, a computational experiment on several hundred of randomly generated graphs is set up. …”
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