A two-stage robust optimization model for emergency service facilities location-allocation problem under demand uncertainty and sustainable development by Hongyan Li, Dongmei Yu, Yiming Zhang, Yifei Yuan

“…Abstract Under the backdrop of frequent emergencies, the rational layout of emergency service facilities (ESF) and the effective allocation of emergency supplies have emerged as crucial in determining the timeliness of post-disaster response. By adequately accounting for potential uncertainties and carrying out comprehensive pre-planning, the robustness of location-allocation decisions can be significantly improved. …”
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A lithium-ion batteries SOH estimation method based on extracting new features during the constant voltage charging stage and improving BPNN. by Yanhua Xian, Mingyang Li, Jiayin Huang

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Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

“…The performance of the GLEO-coupled with the RFR model was compared with the standard Equilibrium Optimizer (EO) and other state-of-the-art algorithms in physical and physiological function estimation using biological signals.ResultsExperimental results showed that selected features and tuned hyperparameters demonstrated a significant improvement in root mean square error (RMSE), coefficient of determination (R2) and slope with values improving from 0.1330 to 0.1174, 0.7228 to 0.7853 and 0.6946 to 0.7414, respectively for the test dataset. …”
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Inversion of snow geophysical parameters using the VHR PAZ X-band dual polarimetric SAR data: first known experiments in the Himalayan region by Hemant Singh, Divyesh Varade

“…In this study, we proposed an improved algorithm for SD inversion, instead of relying on a single in-situ snow density value, we incorporated a range of snow densities (0.15 to 0.27 g/cm3), optimizing the axial ratio between 1.13 and 1.17. …”
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On the Performance of Downlink Channel Estimation‐Based Cell‐Free Massive MIMO Systems Under Correlated Rician Fading Channels by Jiarui Li, Yao Zhang, Fengjiao Gan, Na Liu, Longxiang Yang, Hongbo Zhu

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Re-Supplying Autonomous Mobile Parcel Lockers in Last-Mile Distribution by Sajjad Hedayati, Mostafa Setak, Tom Van Woensel, Emrah Demir

“…The CSA algorithm incorporates the K-means clustering method with specialized operators rooted in an extensive neighborhood search, aiming to improve the effectiveness of solution discovery. …”
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Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

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The Robust Steiner Team Orienteering Problem with Decreasing Priorities under budgeted uncertainty by Lucas Assunção, Andréa Cynthia Santos

“…Post-disaster relief operations have gained attention over the past decade, focusing on enhancing resilience in labor and social environments. …”
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Spatial Downscaling of TRMM Precipitation Data Using an Optimal Subset Regression Model with NDVI and Terrain Factors in the Yarlung Zangbo River Basin, China by Jinping Liu, Wanchang Zhang, Ning Nie

“…After downscaling, the bias between TRMM 3B43 and rain gauge data decreased considerably from 0.397 to 0.109, the root-mean-square error decreased from 235.16 to 124.60 mm, and the r2 increased from 0.54 to 0.61, indicating significant improvement in the spatial resolution and accuracy of the TRMM 3B43 data. …”
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Secure THz Communication in 6G: A Two-Stage DRL Approach for IRS-Assisted NOMA by Muhammad Shahwar, Manzoor Ahmed, Touseef Hussain, Muhammad Sheraz, Wali Ullah Khan, Teong Chee Chuah

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The Impact of the Natural Grass-Growing Model on the Development of Korla Fragrant Pear Fruit, as Well as Its Influence on Post-Harvest Sugar Metabolism and the Expression of Key E... by Mingyang Yu, Lanfei Wang, Yan Chen, Weifan Fan, Hao Wang, Kailu Guo, Shutian Tao, Xin Gong, Jianping Bao

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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…Aiming to reduce the maximum electric field strength of the reactor, this paper proposes a hybrid surrogate model that combines Radial Basis Function Neural Network (RBFNN) and the Kriging model to optimize the configuration of grading rings. First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
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Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…Compared to a baseline model from the literature, O-LGB achieved significant improvements in predictive performance. For compressive strength, it reduced the Mean Absolute Error (MAE) by 87.69% and the Root Mean Squared Error (RMSE) by 71.93%. …”
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FEATURES OF DIAGNOSTIC AND THERAPEUTIC TACTICS FOR BLUNT ABDOMINAL TRAUMA WITH DAMAGE TO THE PANCREAS by A. B. Singayevsky, S. G. Scherbak, B. V. Sigua, N. M. Vrublevsky, A. V. Nikiforenko, A. A. Kurkov, A. K. Dyukov

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Surface Reconstruction Planning with High-Quality Satellite Stereo Pairs Searching by Jinwen Li, Guangli Ren, Youmei Pan, Jing Sun, Peng Wang, Fanjiang Xu, Zhaohui Liu

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可穿戴设备在卒中风险预测及卒中后管理中的应用进展 Research Progress on the Application of Wearable Devices in Stroke Risk Prediction and Post-Stroke Management... by 吴雅婷1，魏宸铭1，桑振华1，陈乐1，梁怡凡1，武剑1，2，3 (WU Yating1, WEI Chenming1, SANG Zhenhua1, CHEN Le1, LIANG Yifan1, WU Jian1,2,3)

“…Wearable devices, with their real-time capabilities and portability features, present new solutions for stroke risk prediction and post-stroke management. By integrating with health management platforms and artificial intelligence algorithms, wearable devices can significantly enhance the accuracy of risk assessment, optimize rehabilitation treatment plans, and thus improve the patients’ outcomes. …”
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Construction and application of a digital twin model for multi-objectiveoptimization of intelligent tape conveyor system by Wei CHEN, Jingzhao LI, Qing SHI, Jichao LIU, Huashun LI

“…Moreover, forecast values of sweep force at the current moment help formulate the dispatch plan for the cleaning mechanism in the next moment, thus ensuring precise control of the physical model. The Improved Whale Optimization Algorithm (IWOA) is employed to optimize parameters in this blueprint, facilitating real-time scheduling by rapidly converging to the global optimum. …”
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Improving TerraClimate hydroclimatic data accuracy with XGBoost for regions with sparse gauge networks: A case study of the Meknes plateau and the Middle Atlas Causse, Morocco by Hammoud Yassine, Allali Youssef, Saadane Abderrahim

“…Applying the XGBoost algorithm significantly improves the raw TerraClimate data, reducing the average Mean Absolute Error (MAE) across all parameters from 3.08 to 0.29, and the average Root Mean Square Error (RMSE) from 4.84 to 0.46, and increasing the average Nash-Sutcliffe Efficiency (NSE) from 0.82 to 0.99. …”
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A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools by Saad Javed Cheema, Masoud Karbasi, Gurjit S. Randhawa, Suqi Liu, Travis J. Esau, Kuljeet Singh Grewal, Farhat Abbas, Qamar Uz Zaman, Aitazaz A. Farooque

“…A machine learning approach using XGBoost, optimized with the Chaos Game algorithm (CGO-XGBoost), was employed to predict Kc. …”
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Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations: A case study of grocery demand during Covid-19 outbreaks by Nader AL Theeb, Hazem Smadi, Naser Al-qaydeh

“…Furthermore, using BO algorithm for hyperparameters tuning improved the forecasting accuracy. …”
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