Decentralized Nonstationary Fuzzy Neural Network with Meta-Learning-Net by Zhen Zhang, Meiling Yu, Hui Jia

“…To address this limitation, we propose a Decentralized NFNN (DNFNN) that overcomes the obstacles in the backward update process and enhances the efficiency of large-scale optimization. Additionally, we demonstrate improved computational efficiency and establish the linear convergence of the proposed decentralized algorithm. …”
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Grid Integration of PV Systems With Advanced Control and Machine Learning Strategies by Venkata Reddy Kota, Bapayya Naidu Kommula, Asif Afzal, Mohammad Asif, Liew Tze Hui

“…The primary objective is to optimize voltage output from PV system while concurrently maximizing power using a novel Modified Zeta-Cuk converter, coupled with Hybrid Maximum Power Point Tracking (MPPT) algorithm combining Incremental Conductance and Bat Optimization Algorithm (InC-BOA). …”
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NSGA-II-based load resource management for frequency and voltage support by Yaxin Wang, Zhihang Zhu, Zhihong Yu, Zigan Wang

“…Compared to the conventional optimal load control or using LRM alone, the improved NSGA-II-based LRM demonstrates superior performance. …”
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Physics-Informed Decoupled Calibration for Fourier Ptychographic Microscopy by Mingdi Liu, Junzhao Liang, Yanxiong Wu, Zicong Luo, Rui Xie, Jiaxiong Luo, Lisong Yan

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Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

“…Optimization using GTO resulted in a 6.71% improvement in kerf deviation prediction accuracy compared to experimental values, while ZOA achieved a 2.37% improvement. …”
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Techno-economic analysis and energy management strategies for micro gas turbines: A state-of-the-art review by A.H. Samitha Weerakoon, Mohsen Assadi

“…The review critically examines the techno-economic analysis of Micro Gas Turbines, focusing on four major areas: integration with photovoltaic systems, configurations like cogeneration and trigeneration, optimization techniques, and hydrogen utilization. The review reveals that while standalone Micro Gas Turbines face economic challenges, their integration with photovoltaic and battery bank systems significantly improves cost-effectiveness, achieving a cost of electricity as low as $0.263/kWh. …”
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A Diagnostic and Performance System for Soccer: Technical Design and Development by Alberto Gascón, Álvaro Marco, David Buldain, Javier Alfaro-Santafé, Jose Victor Alfaro-Santafé, Antonio Gómez-Bernal, Roberto Casas

“…Results indicate high accuracy rates for detecting ball-striking events and CoDs, with improvements in algorithm performance achieved through adaptive thresholds and ensemble neural network models. …”
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A study on life assessment of metro cowcatcher based on multi-axis vibration environment reconstruction by ZHENG Yuhao, WU Xingwen, LIU Yang, CHI Maoru, LIANG Shulin

“…Then, the modal damping ratio was optimized by the genetic algorithm, improving the consistency between the simulation and measured response results, and proving the correctness of the modeling method. …”
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Research on Wind Power Grid Integration Power Fluctuation Smoothing Control Strategy Based on Energy Storage Battery Health Prediction by Bin Cheng, Jiahui Wu, Guancheng Lv, Zhongbo Li

“…The experimental results show that the GA-SVR algorithm can accurately predict the health of the energy storage system, and the MPC-based control strategy derived from health predictions can improve grid power stability while adaptively adjusting energy storage output according to different health levels.…”
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A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
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Sparse support path generation for multi-axis curved layer fused filament fabrication by Tak Yu Lau, Dong He, Yamin Li, Yihe Wang, Danjie Bi, Lulu Huang, Pengcheng Hu, Kai Tang

“…Firstly, the overhang regions are detected by identifying the overhang points given a multi-axis nozzle path. Then, an optimization framework for the support guide curve is proposed to minimize its total length while ensuring that overhang filaments can be stably supported. …”
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Microservice Workflow Scheduling with a Resource Configuration Model Under Deadline and Reliability Constraints by Wenzheng Li, Xiaoping Li, Long Chen, Mingjing Wang

“…Additionally, we propose a reliability microservice workflow scheduling algorithm (RMWS), which incorporates heuristic leasing and deployment strategies to ensure reliability while reducing cloud resource leasing cost. …”
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Exploring the Impact of Artificial Intelligence on Healthcare Management: A Combined Systematic Review and Machine-Learning Approach by Vito Santamato, Caterina Tricase, Nicola Faccilongo, Massimo Iacoviello, Agostino Marengo

“…The scientific novelty of the study lies in its integrated approach, combining systematic review and predictive algorithms to provide a comprehensive understanding of AI’s role in improving healthcare management across different contexts. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…Furthermore, the metaheuristic Cat Swarm Optimization (CSO) algorithm is employed to fine-tune the hyperparameters of both the CSO-2D-CNN and the attention-based XGBoost classifier. …”
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Online English teaching resource recommendation method design based on LightGCNCSCM by Jing Tang

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STARMAP: Spaceborne Target Acquisition Radar With Meta-RL Assisted Placement by Alireza Famili, Shihua Sun, Tolga Atalay, Angelos Stavrou

“…To address this, we have developed an advanced meta-reinforcement learning (meta-RL) algorithm, enhancing a double deep Q-network (DDQN) to optimize receiver placement. …”
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Energy-efficient artificial fish swarm-based clustering protocol for enhancing network lifetime in underwater wireless sensor networks by Puneet Kaur, Kiranbir Kaur, Kuldeep Singh, Kiran Saleem, Ateeq Ur Rehman, Rupesh Gupta, Seada Hussen Adem

“…EAFSCCIP leverages the collective behavior of artificial fish within a Bees algorithm framework, using a combination of heuristic and metaheuristic approaches for optimal cluster-head (CH) selection in each round. …”
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RLEAFS: Reinforcement Learning-Based Energy Aware Forwarding Strategy for NDN-Based IoT Networks by Naeem Ali Askar, Adib Habbal

“…To address these challenges, we propose Reinforcement Learning-based Energy-Aware Forwarding Strategy (RLEAFS), a novel strategy for NDN-based IoT communications that leverages reinforcement learning to optimize forwarding decisions. Our Strategy integrates Q learning algorithm into path selection procedure, focusing on minimizing energy consumption and extending network lifetime while maintaining efficient data delivery. …”
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Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Muhammad Sabo Yahaya, Ahmad Sobri B. Hashim, Abdullateef Oluwagbemiga Balogun, Aminu Aminu Muazu, Fatima Sabo Usman, Dahiru Adamu Aliyu, Abdullahi Uwaisu Muhammad

“…Pairwise testing, a combinatorial testing methodology, optimizes test case generation by minimizing redundancy while maintaining defect detection effectiveness. …”
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Pre-disaster evacuation transport network design under uncertain demand and connectivity reliability: a novel bi-level programming model by Junxiang Xu, Divya Jayakumar Nair, S. Travis Waller

“…For the solution of this model, an Improved Genetic Algorithm combined with Non-dominated Sorting Genetic Algorithm II(IGA-NSGA-II) is designed. …”
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