Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
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Optimized Dual-Battery System with Intelligent Auto-Switching for Reliable Soil Nutrient Monitoring in Remote IoT Applications by Doan Perdana, Pascal Lorenz, Bagus Aditya

“…The proposed system integrates Lithium-Sulphur (Li-S) and Lithium-Ion (Li-Ion) batteries with advanced switching algorithms—specifically, the Dynamic Load Balancing–Power Allocation Optimisation (DLB–PAO) and Dynamic Load Balancing–Genetic Algorithm (DLB–GA)—tailored to maximise sensor operational longevity. …”
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Optimize multi-objective transformation rules of water-sediment regulation for cascade reservoirs in the Lower Yellow River of China by Kunhui Hong, Aixing Ma, Wei Zhang, Mingxiong Cao

“…An innovative method (ESS-NSGA-II) is proposed, combining Efficient Search Space (ESS) with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to optimize cascade reservoirs operation. …”
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Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas by Yue Hu, Xin Cao, Hongyi Chen, Daoying Geng, Kun Lv

“…We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) biomarkers to discriminate high-grade (HGGs) and low-grade gliomas (LGGs) in the frontal lobe. …”
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Experimental study on solution possibilities of multiextremal optimization problems through heuristic methods by Rudolf A. Neydorf, Ivan V. Chernogorov, Orkhan Takhir Yarakhmedov, Victor V. Polyakh

“…Therefore, three best known and developed search engine optimization techniques are studied: particle swarm method, evolutionary genetic approach, and ant colony algorithm. …”
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Designing High‐Performance, Manufacturing‐Friendly Rotor Blades for Micro Wind Turbines via Cambered Plate Airfoil Optimization by Moritz Burmester, Abdullah Khisraw, Peter Dalhoff

“…Aerodynamic performance was analyzed using XFOIL, with evaluations conducted at Reynolds numbers of 30,000, 40,000, and 50,000 to ensure robust performance across realistic operating scenarios. The iterative optimization employed both single‐objective and (genetic) multi‐objective algorithms, targeting both aerodynamic efficiency and manufacturability. …”
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Squat Motion of a Humanoid Robot Using Three-Particle Model Predictive Control and Whole-Body Control by Hongxiang Chen, Xiuli Zhang, Mingguo Zhao

“…TP-MPC is utilized to optimize the rough planning’s reference trajectory, while WBC is employed to follow the optimized trajectory. …”
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The open-closed mod-minimizer algorithm by Ragnar Groot Koerkamp, Daniel Liu, Giulio Ermanno Pibiri

“…Abstract Sampling algorithms that deterministically select a subset of $$k$$ k -mers are an important building block in bioinformatics applications. …”
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An Effective Genetic Algorithm for Mixed Precision by Wanyu Zhang, Yu Shang, Min Tsao, Yiwei Li, Xiaoyu Song

“…Addressing this trade-off is essential for optimizing performance while ensuring numerical accuracy. …”
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Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms by Claudio Cicconetti

“…While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. …”
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PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…It can be concluded that while predictive models produce satisfactory results, the Bat Algorithm (BA) demonstrates a higher level of precision and realism in its outcomes.…”
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A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…Additionally, the hybrid approach enables early predictions of approximately 17 cycles and late predictions of only 2%, while other learning algorithms, such as linear regression, do not make early predictions but 100% of their predictions are late. …”
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Novel Application of Quantum Computing for Routing and Spectrum Assignment in Flexi-Grid Optical Networks by Oumayma Bouchmal, Bruno Cimoli, Ripalta Stabile, Juan Jose Vegas Olmos, Carlos Hernandez, Ricardo Martinez, Ramon Casellas, Idelfonso Tafur Monroy

“…By formulating the problem as a Quadratic Unconstrained Binary Optimization (QUBO) model, we employ the Quantum Approximate Optimization Algorithm (QAOA) to effectively solve it. …”
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The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. …”
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A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Hence, a novel hybrid model is provided, incorporating singular value decomposition (SVD) in conjunction with kernel-based ridge regression (SKRidge), multivariate variational mode decomposition (MVMD), and the light gradient boosting machine (LGBM) as a feature selection method, along with the Runge–Kutta optimization (RUN) algorithm for parameter optimization. …”
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Aerodynamic Optimization of Morphing Airfoil by PCA and Optimization-Guided Data Augmentation by Ao Guo, Jing Wang, Miao Zhang, Han Wang

“…A Multi-Island Genetic Algorithm (MIGA) efficiently explores the reduced design space, while iterative retraining of the surrogate model enhances prediction accuracy, particularly in high-performance regions. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
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Sliding Mode Thrust Control Strategy for Electromagnetic Energy-Feeding Shock Absorbers Based on an Improved Gray Wolf Optimizer by Wenqiang Zhang, Jiayu Lu, Wenqing Ge, Xiaoxuan Xie, Cao Tan, Huichao Zhang

“…Meanwhile, a position update strategy from the particle swarm optimization (PSO) algorithm is integrated into the gray wolf optimizer (GWO) to improve the global search ability and the balance of local exploitation. …”
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Efficient Frequency Management for Hybrid AC/DC Power Systems Based on an Optimized Fuzzy Cascaded PI−PD Controller by Awadh Ba Wazir, Sultan Alghamdi, Abdulraheem Alobaidi, Abdullah Ali Alhussainy, Ahmad H. Milyani

“…The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. …”
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