An adaptive hybrid framework for IIoT intrusion detection using neural networks and feature optimization using genetic algorithms by Mohammad Zubair Khan, Aijaz Ahmad Reshi, Shabana Shafi, Ibrahim Aljubayri

“…Additionally, Genetic Algorithms were employed to optimize feature selection, further refining the ANN’s input space to improve computational efficiency without sacrificing predictive power. …”
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CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…Conclusion The intelligent Continuous Kidney Replacement Therapy nursing feedback model improves prediction accuracy while reducing redundant information. …”
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Optimizing Stroke Classification with Pre-Trained Deep Learning Models by Serra Aksoy, Pinar Demircioglu, Ismail Bogrekci

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Parameter Extraction of Photovoltaic Cells and Panels Using a PID-Based Metaheuristic Algorithm by Aseel Bennagi, Obaida AlHousrya, Daniel T. Cotfas, Petru A. Cotfas

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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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Joint Optimization of Multienergy Virtual Power Plant Configuration and Operation Considering Electric Vehicle Access by Xianqiang Zeng, Chuangwei Xu, Tengfei Wei

“…Based on the gazelle algorithm and mixed integer linear programming (MILP), the capacity and output of the system energy equipment are jointly optimized, and the running curve of MEVPP in a typical quarter is analyzed. …”
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RUL Prediction Method for Lithium‐Ion Batteries Based on the SOA‐ELM Algorithm by Meng Xiangdong, Zhang Haifeng, Li Dexin, Dong Yunchang, Zhang Jiajun, Cao Xinyu, Li Gang

“…This paper proposes an advanced RUL prediction model that combines the seagull optimization algorithm (SOA) with the extreme learning machine (ELM) to enhance prediction accuracy. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Multi-objective optimization of daylighting performance and solar radiation for building geometry using a hybrid evolutionary algorithm by Shaoyang Lou, Xiaojun Luo, Zhonggou Chen, Zhiji Gao, Ruida Wang, Linjin Feng, Guoyi Zhang, Yanfei Zhang, Ye Zhao, Bei Li

“…A multi-objective evolutionary algorithm named Steady-State Island Evolutionary Algorithm (SSIEA) was applied to optimize the building geometry, ultimately yielding the Pareto front optimal solution. …”
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Rolling optimization method of virtual power plant demand response based on Bayesian Stackelberg game by Binxi Huang

“…Utilizing the forecast results of dynamic electricity demand, a demand response elastic matrix for virtual power plant is constructed through a rolling optimization model based on Stackelberg game. The two optimization objective functions, maximizing the supply-side income and minimizing the demand-side electricity purchase cost of virtual power plant, are transformed into maximizing the profit of power transaction for the virtual power plant. …”
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Multi-Energy Microgrid Data-Driven Distributionally Robust Optimization Dispatch Considering Uncertainty Correlation by LI Jiawei, SUN Qinghe, WANG Qiong, YE Yujian, HU Heng, ZHANG Xi

“…This transforms the distributionally robust model into a linear deterministic model，thereby enabling an efficient solution using optimization solvers. …”
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UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures by Ahmed Serag, Maram H. Abduljabbar, Yusuf S. Althobaiti, Farooq M. Almutairi, Shaker T. Alsharif, Rami M. Alzhrani, Marwa F. Ahmed, Atiah H. Almalki

“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning by A. Beena Godbin, S. Graceline Jasmine

“…To optimize the performance of machine learning models, the paper incorporates genetic algorithms for hyperparameter optimization. …”
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Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters by Wenmin Wang, Cuijie Diao, Wenqing He, Zhihong Jin, Zaili Yang

“…Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. …”
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Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network by Renpeng LIU, Bo HU, Hequn LI

“…The high-speed motion of low-earth orbit communication satellites results in a highly dynamic network topology, and the spatio-temporal distribution of resources in the satellite-terrestrial integrated network is non-uniform.When multiple users and services switch between satellites, a large number of handover requests are triggered, leading to intensified network resource competition.As a result, the limited satellite resources cannot meet all the handover requests, leading to a significant decrease in handover success rate.In view of the above problem, the multi-objective optimization based satellite handover method was proposed.It introduced the satellite coverage spatio-temporal graph and transforms the dynamic continuous topology into static discrete snapshots, accurately depicted the connections between satellite nodes and users at different times and locations.The multi-objective optimization model was established for satellite handover decisions, and anadaptive accelerated multi-objective evolutionary algorithm(AAMOEA) was proposed to optimized user data rate and network load simultaneously, ensured handover success rate and enhanced network service capability.It built a STIN communication simulation environment and tested the multi user handover performance in a multi satellite overlapping coverage scenario.The results demonstrated that the multi-objective optimization-based satellite handover method achieved an average handover success rate improvement of over 20% compared to benchmark algorithms.…”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…The wind power offset was decomposed by a Butterworth low-pass filter, and the low-frequency and high-frequency components were used as the reference power of lithium battery energy storage and flywheel energy storage, respectively. In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
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Improvement analysis of organic light emitting diode temperature control by integrating whale algorithm in PID control system. by Dayu Zhang, Cong Guan

“…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”
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Enhanced Design of a Hand Exoskeleton: Balancing Force Transmission and Actuation With Evolutionary Algorithms by Baris Akbas, Huseyin Taner Yuksel, Aleyna Soylemez, Mine Sarac, Fabio Stroppa

“…Our simulation results and statistical analyses revealed that using Big Bang-Big Crunch provides high and more consistent results in terms of optimality with lower convergence time. In addition, adding more objectives offers a variety of trade-off solutions to the designers, who might later set priorities for the objectives without repeating the process – at the cost of complicating the optimization algorithm and computational burden. …”
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Federated Reinforcement Learning in Stock Trading Execution: The FPPO Algorithm for Information Security by Haogang Feng, Yue Wang, Shida Zhong, Tao Yuan, Zhi Quan

“…The FPPO algorithm demonstrates significant improvements in model performance across various stocks, with average returns enhanced by 3% to 15%. …”
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