Comparative Analysis of Offshore Wind Resources and Optimal Wind Speed Distribution Models in China and Europe by Yanan Chen, Ming Zhao, Zhengxian Liu, Jianlong Ma, Lei Yang

“…Offshore wind resources in China and Europe are systematically compared, focusing on wind speed characteristics and the selection of optimal wind speed probability distribution models. …”
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Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

“…The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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Optimizing Greenhouse Cucumber Fertigation Through Grafting: Improving Yield, Bioactive Compounds, and Antioxidant Activity by Đorđe Vojnović, Ivana Maksimović, Gabrijela Koprivica, Aleksandra Tepić Horecki, Anita Milić, Boris Adamović, Zdravko Šumić, Žarko Ilin

“…In contrast, grafting and the new fertigation methods generally reduced the phenolic content in the peel. …”
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An Optimized GWO-BPNN Model for Predicting Corrosion Fatigue Performance of Stay Cables in Coastal Environments by Liping Zhou, Guowen Yao

“…The optimized GWO-BPNN model significantly enhances prediction accuracy, stability, generalization, and convergence speed. …”
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Continuous approximation and GIS-enhanced design optimization of feeder bus networks along rail corridors. by Jiahe Liu, Rui Song

“…The objective is to minimize total generalized system cost with respect to the density of feeder bus routes and their service frequencies. …”
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Improved Phase Diversity Wavefront Sensing with a Deep Learning-Driven Hybrid Optimization Approach by Yangchen Wang, Ming Wen, Hongcai Ma

“…Simulation and experimental results indicate that the proposed method achieves an RMS wavefront error below 0.05λ within [−0.5λ, 0.5λ] and exhibits a certain level of generalization up to [−0.7λ, 0.7λ]. …”
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Analysis and optimization of electrospinning parameters for fabricating thermoplastic polyurethanes (TPU) nanofibers by response surface methodology by Lu Liu, Tian Luo, Xiaoju Kuang, Xiaoqian Wan, Xinhua Liang, Gaoming Jiang, Honglian Cong, Haijun He

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Optimizing Backbone Networks Through Hybrid–Modal Fusion: A New Strategy for Waste Classification by Houkui Zhou, Qifeng Ding, Chang Chen, Qinqin Liao, Qun Wang, Huimin Yu, Haoji Hu, Guangqun Zhang, Junguo Hu, Tao He

“…Traditional manual methods are time-consuming, labor-intensive, costly, and error-prone, resulting in reduced accuracy. Deep learning has revolutionized this field. …”
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Fusion of Recurrence Plots and Gramian Angular Fields with Bayesian Optimization for Enhanced Time-Series Classification by Maria Mariani, Prince Appiah, Osei Tweneboah

“…For multivariate tasks, the proposed fusion model achieves macro F1 scores of 91.55% on the UCI Human Activity Recognition dataset and 98.95% on the UCI Room Occupancy Estimation dataset, outperforming standard deep learning baselines. These results demonstrate the robustness and generalizability of our framework, establishing a new benchmark for image-based time-series classification through principled fusion and adaptive optimization.…”
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A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

“…In this paper, we propose a novel iterative optimized RBF-NN method for NSS prediction. Our proposed method leverages a resource allocation network (RAN) to dynamically determine the optimal number of neurons in the hidden layer, ensuring a balance between model complexity and prediction accuracy. …”
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A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

“…A loss function based on the value function was then constructed, and network parameters were updated iteratively by a batch gradient descent method. Results from simulations conducted in environments set up using Matlab showed that in the task training of train operation on long steep downhill with randomly generated entry speeds, cumulative rewards gradually converged over training runs, which verified the convergence and generalization of the proposed algorithm. …”
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Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin by Qinghou Hang, Hao Guo, Xiangchen Meng, Wei Wang, Ying Cao, Rui Liu, Philippe De Maeyer, Yunqian Wang

“…Furthermore, the temporal and spatial evolution of agricultural drought in the Yellow River Basin (YRB) was analyzed using VHIopt. The results indicate the following: (1) In the YRB, the optimal contribution of the VCI to the VHI is lower than that of the TCI. (2) The drought monitoring accuracy of VHIopt in forests, grasslands, croplands, and other vegetation types exceeds that of the original VHI (VHIori). …”
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Inoculant Formulation for <i>Bradyrhizobium</i> spp.: Optimizing CMC/Starch Blends for Improved Performance by Jaqueline Carvalho de Almeida, Vinício Oliosi Favero, Janaina Ribeiro Costa Rouws, Carla de Sant’Anna Freitas, Érica Barbosa de Sousa, Jéssica Feitoza da Rocha, Nainicelle Cibelle Sousa Chantre, Gustavo Ribeiro Xavier, Paulo Jansen de Oliveira, Norma Gouvêa Rumjanek

“…From four commercial starches and two carboxymethylcelluloses (CMC), we developed CMC/starch blends compatibilized or not with MgO at concentrations from 0.1% to 1.0% and subjected them to autoclaving for either 30 or 60 min. The resulting inoculants were stored for 168 days. Generally, blends compatibilized with 1.0% MgO exhibited a significant decrease in cell numbers, likely due to the observed pH values of approximately 10. …”
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A new method of task aggregation and optimization allocation for multiple groups collaborative task networks by WeiWei Du, XiaoWei Chen

“…Abstract As task diversity and inter-task relationship complexity grow, optimal formation power allocation is key to improving task execution efficiency. …”
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Cost–benefit analysis and design optimization of wind propulsion systems for a Tanker retrofit case by M. Reche-Vilanova, H.B. Bingham, M. Fluck, D. Morris, H.N. Psaraftis

“…A retrofit case study of an oil tanker evaluates two WPS classes—DynaRigs and Rotor Sails—across multiple operational and economic conditions. Results reveal that optimal configurations vary based on constraints: in an unconstrained scenario, larger, well-spaced installations minimize aerodynamic losses, whereas realistic constraints shift the preference towards smaller, distributed setups to mitigate cargo loss and air draft penalties. …”
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A GIS-based integrative approach for land use optimization in a semi-arid watershed by S.M. Tajbakhsh, H. Memarian, A. Kheyrkhah

“…Therefore, it is necessary for managers to control runoff using the strategies related to runoff harvesting, especially on steep slopes. Generally, it can be concluded that a combination of the techniques weighted goal programming, analytic hierarchy process and multi-objective land allocation is highly capable to optimize land use and land covers based on the conflicting objectives.…”
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…By using metaheuristic optimization, parameter adjustment became more effective, avoiding trapping in local minima and improving model generalization. …”
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Multi-objective optimization and characteristic analysis of contra-rotating fan double-row blades coupling by Xinyu ZHANG, Hua JIANG, Wuqi GONG

“…The sample set data is used to construct a neural network surrogate model, and the weights and thresholds of the neural network are optimized in combination with the genetic algorithm to improve the generalization ability of the surrogate model. …”
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Optimizing solar PV systems using fuzzy logic for Climate-Resilient Healthcare infrastructure in Kyrgyzstan by Nivine Guler, Zied Ben Hazem, Ali Gunes

“…Though photovoltaic (PV) modules are commonly used for renewable energy generation, conventional methods are generally based on fixed tilt angles or high mathematical modeling techniques. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…To fine-tune model parameters efficiently, the method incorporates the Chaotic Billiards Optimizer (CBO) alongside the Adam optimizer. In this framework, WT helps break down wind speed signals into different frequency bands, capturing both short-term changes and long-term behavior. …”
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