Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The GVSAO algorithm is a sophisticated optimization technique that fine-tunes the hyperparameters of CNNs. …”
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Enhancing crane and gate OCR efficiency at container terminal using a hybrid genetic algorithm and neural network model: case study of tangier med port by Hamza Garmouch, Otman Abdoun

“…GA-based optimization allows for adaptive learning, parameterization, and real-time adaptation, significantly improving OCR accuracy, reducing error rates, and optimizing system uptime. …”
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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

“…The findings advance the understanding of aerodynamic optimization in low Reynolds number environments, paving the way for more efficient and cost‐effective rotor designs.…”
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Cost-Effective Multitask Active Learning in Wearable Sensor Systems by Asiful Arefeen, Hassan Ghasemzadeh

“…When employed alongside rank-based query selection, our proposed CSS algorithm demonstrates up to 9% improvement in accuracy over traditional querying approaches for a 2000-query budget.…”
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White Shark Optimization for Solving Workshop Layout Optimization Problem by Bin Guo, Yuanfei Wei, Qifang Luo, Yongquan Zhou

“…This paper establishes a mathematical model for the workshop layout problem, aiming to minimize logistics transportation costs and maximize non–logistics relationships. Using a real–world case study, the White Shark Optimizer (WSO) algorithm is applied to solve the model. …”
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Enhancing Compressive Strength Prediction in Recycled Aggregate Concrete through Robust Hybrid Machine Learning Approaches by Samuel Keown, Dylan O’Dwyer

“…This investigation explores the integration of LSSVR with two innovative optimizers, namely the Giant Trevally Optimizer (GTO) and the Dingo Optimization Algorithm (DOA). …”
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Advanced removal of butylparaben from aqueous solutions using magnetic molybdenum disulfide nanocomposite modified with chitosan/beta-cyclodextrin and parametric evaluation through... by Saeed Hosseinpour, Alieh Rezagholizade-shirvan, Mohammad Golaki, Amir Mohammadi, Amir Sheikhmohammadi, Zahra Atafar

“…The predictive stability of PR emerges through these different dataset applications. The L-BFGS algorithm established the optimal control factors as pH = 6.64 and initial concentration = 1.00 mg/L and contact time = 60 min and adsorbent dosage = 0.8 g/L which dramatically improved the removal efficiency due to the collaborative properties of the nanocomposite. …”
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Designing a new tomato leaf disease classification framework using ran-based adaptive fuzzy c-means with heuristic algorithm model by Kanti Rongali Divya, Rao Gottapu Sasibhushana, Aruna Singam

“…So, the parameters of AFCM are tuned by utilizing the new improved algorithm named Dingo Optimization Algorithm (DOA) to improve the clustering accuracy. …”
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A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…Second, the Cauchy-Gaussian Genetic-Arithmetic Optimizer (CG-GAO) addresses the challenge of high-dimensional data by combining a genetic algorithm (GA) and an arithmetic optimization algorithm (AOA), enhancing exploration and preventing premature convergence. …”
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Thermoeconomic optimization of a hybrid power and cooling facility using waste heat recovery from a marine diesel engine by Mohamed Bechir Ben Hamida, Waqid Al-Mussawi, Mohamed Shaban, Mohammad Marefati

“…Ultimately, 2-archive multi-objective cuckoo search algorithm-based optimization (MOCS2arc algorithm) establishes the optimized conceptual design. …”
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Comprehensive Fault Location on Transmission Lines Considering Variation in Line Parameters and Saturation in Current Transformers by Duy C. Huynh, Loc D. Ho

“…Precise and rapid fault location on transmission lines is a cornerstone for enhancing the reliability and cost-efficiency of power systems. This paper proposes an innovative approach to a fault location by solving an optimization problem. …”
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Intelligent design of high-performance fluids for thermal management: integrating response surface methodology, weighted Tchebycheff method, and strength Pareto evolutionary algori... by Mohamed Bechir Ben Hamida, Ali Basem, Neeraj Varshney, Loghman Mostafa

“…Abstract Optimizing nanofluid thermophysical properties (TPPs) is essential for advancing heat transfer applications; however, most studies focus on two-objective optimization, limiting their real-world applicability. …”
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GPTOR: Gridded GA and PSO-based task offloading and ordering in IoT-edge-cloud computing by Arezou Mahmoudi, Leili Farzinvash, Javid Taheri

“…In this study, we propose an improved genetic algorithm for joint task offloading and ordering to distribute tasks across the IoT, edge, and cloud layers. …”
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Pricing principles in the field of ready–made meal delivery: analysis of influence factors by K. V. Martynov

“…The study describes the most popular pricing principles: cost–based, competitor–oriented, as well as dynamic algorithms taking into account seasonal demand. …”
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Research on Offshore Vessel Trajectory Prediction Based on PSO-CNN-RGRU-Attention by Wei Liu, Yu Cao

“…This study utilizes real Automatic Identification System (AIS) data and applies the PSO algorithm to optimize the model and determine the optimal parameters, using a sliding window method for input and output prediction. …”
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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction by Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas

“…A genetic algorithm-based hyperparameter optimization method reduces the computational load on edge nodes by efficiently exploring different configurations and using only the most promising ones for edge nodes’ cross-validation. …”
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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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Opportunities of machine learning algorithms for education by Olga Ovtšarenko

“…By predicting trends, identifying patterns, and optimizing resource allocation, machine learning can improve the efficiency of e-learning and provide students with tailored recommendations for acquiring relevant knowledge and skills. …”
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Monitoring of Glacier Area Changes in the Ili River Basin during 1992–2020 Based on Google Earth Engine by Qinqin Zhang, Zihui Zhang, Xiaofei Wang, Zhonglin Xu, Yao Wang

“…Utilizing the Landsat data series, we employed the random forest (RF) classification algorithm within the GEE platform to extract glacier areas, optimizing a multidimensional feature set using the Jeffries–Matusita (JM) distance method, and applied visual interpretation for data refinement. …”
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Cost Index Predictions for Construction Engineering Based on LSTM Neural Networks by Jiacheng Dong, Yuan Chen, Gang Guan

“…This research extended current algorithm tools that can be used to forecast cost indexes and evaluated the optimization mechanism of the algorithm in order to improve the efficiency and accuracy of prediction, which have not been explored in current research knowledge.…”
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