Model Predictive Control of Nonlinear System Based on GA-RBP Neural Network and Improved Gradient Descent Method by Youming Wang, Didi Qing

“…The incorporation of GA into RBP can reduce the possibility of the BP neural network falling into a local optimum instead of reaching global optimization. In the online optimizing stage, a multistep-ahead GA-RBP neural network predictor and an improved gradient descent method (IGDM) are proposed to efficiently solve the online optimization problem of nonlinear MPC by minimizing a modified quadratic criterion. …”
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Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

“…Response surface methodology (RSM) is used for predictive modeling, while enhanced hill climbing (EHC), non-dominated sorting genetic algorithm II (NSGA-II), and the multi-objective generalized normal distribution optimizer (MOGNDO) are applied for multi-objective optimization. …”
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Research and Optimization of White Blood Cell Classification Methods Based on Deep Learning and Fourier Ptychographic Microscopy by Mingjing Li, Junshuai Wang, Shu Fang, Le Yang, Xinyang Liu, Haijiao Yun, Xiaoli Wang, Qingyu Du, Ziqing Han

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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…This suggested framework leverages an attention-based convolutional neural network (CNN) and a genetic algorithm (GA) to enhance detection accuracy while optimizing the hyperparameters of the proposed model. …”
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Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…MOO, particularly nondominated sorting genetic algorithm III, effectively balances conflicting network objectives, offering a 15% improvement in overall network performance compared with single-objective approaches. …”
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Developing a novel approach for passive damped LCL filter and controller parameter design using PSO algorithm in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

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Min3GISG: A Synergistic Feature Selection Framework for Industrial Control System Security with the Integrating Genetic Algorithm and Filter Methods by Saiprasad Potharaju, Swapnali N. Tambe, G. Madhukar Rao, M. V. V. Prasad Kantipudi, Kalyan Devappa Bamane, Mininath Bendre

“…This study aims to enhance ICS security by improving attack detection through an optimized feature selection framework that balances dimensionality reduction and classification accuracy. …”
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Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
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Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs by Anwar Ahmad, Lindita Bande, Waleed Ahmed, Kheira Tabet Aoul, Mukesh Jha

“…This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. …”
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Modern approaches to the diagnosis and treatment of cardiac sarcoidosis: results of a cohort study by S. V. Mairina, D. V. Ryzhkova, L. B. Mitrofanova, A. V. Ryzhkov, P. M. Murtazalieva, O. M. Moiseeva

“…Contrast-enhanced cardiac magnetic resonance imaging (MRI) was performed in 10 patients, while endomyocardial biopsy in 7 patients. All patients underwent 18F-fluorodeoxyglucose positron emission tomography (PET).Results. …”
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HiGMA-DADCN: Hirudinaria granulosa multitropic algorithm optimised double attention enabled deep convolutional neural network for psoriasis classification by Soumya C S, Jayanna H S

“…The HiGMA algorithm plays a crucial role in identifying and extracting the most relevant regions of affected skin through optimal segmentation. …”
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Deceptive Cyber-Resilience in PV Grids: Digital Twin-Assisted Optimization Against Cyber-Physical Attacks by Bo Li, Xin Jin, Tingjie Ba, Tingzhe Pan, En Wang, Zhiming Gu

“…A non-dominated sorting genetic algorithm (NSGA-III) is employed to achieve Pareto-optimal solutions, ensuring high system resilience while minimizing computational burdens. …”
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Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping by Lalit Pathak, Badri Baral, Kamana Joshi, Dipak Raj Basnet, Danilo Godone

“…Sixteen factors, encompassing topography, hydrology, geology, and anthropogenic activities, were analyzed alongside a landslide inventory of 159 occurrences compiled from satellite imagery, the literature, and field surveys. A genetic algorithm (GA) was employed to determine the optimal set of conditioning factors, while Maximum Entropy (Maxent) modeling produced landslide susceptibility maps (LSM) at spatial resolutions ranging between 12.5 and 200 m. …”
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An integration of ensemble deep learning with hybrid optimization approaches for effective underwater object detection and classification model by G. Abirami, S. Nagadevi, J. D. Dorathi Jayaseeli, T. Prabhakara Rao, R S M Lakshmi Patibandla, Rajanikanth Aluvalu, K Srihari

“…In this manuscript, an Underwater Object Detection and Classification Utilizing the Ensemble Deep Learning Approach and Hybrid Optimization Algorithms (UODC-EDLHOA) technique is developed. …”
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A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. …”
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Hybrid Automata-Based Control Framework for Real-Time Optimization in Space-Based Solar Power Transmission by Patil Ankita, Ranjan Mritunjay, Deore Kalyani, Sonje Pranjal, Patil Kiran, Patil Rutuja

“…The system enhances stability in systems through the employment of machine learning predictions as inputs to automata-based reasoner-driven decision rules, ensuring real-time response. The system improves SBSP reliability, minimizes power loss, and forms a foundation for the development of autonomous SBSP infrastructure, which can be utilized to respond to different environmental challenges while providing energy transmission efficiency optimization.…”
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Enhancing Hybrid Flow Shop Scheduling Problem with a Hybrid Metaheuristic and Machine Learning Approach for Dynamic Parameter Tuning by Ahmed Abdulmunem Hussein

“…Specifically, we propose a hybrid algorithm by combining Ant Colony Optimization (ACO) and Iterated Local Search (ILS) to form ACOILS. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…This work demonstrates the potential of hybrid optimization techniques in bioinformatics for better gene selection and cancer diagnosis. • Hybrid ACO-ALO approach combines strengths of both algorithms for better feature selection. • Enhances classifier performance while reducing computational complexity. • Outperforms traditional methods on leukemia prediction datasets.…”
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Optimization of Adaptive Observation Strategies for Multi-AUVs in Complex Marine Environments Using Deep Reinforcement Learning by Jingjing Zhang, Weidong Zhou, Xiong Deng, Shuo Yang, Chunwang Yang, Hongliang Yin

“…Traditional algorithms struggle with the strong coupling between environmental information and observation modeling, making it challenging to derive optimal strategies. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Key Points Radiomics is a growing field that can still be optimized. Feature selection method impacts radiomics models’ performance more than ML algorithms. …”
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