Modeling sunflower yield and soil water–salt dynamics with combined fertilizers and irrigation in saline soils using APSIM and deep learning by Qingfeng Miao, Dandan Yu, Haibin Shi, Zhuangzhuang Feng, Weiying Feng, Zhen Li, José Manuel Gonçalves, Isabel Maria Duarte, Yuxin Li

“…Abstract Understanding the interactions between crop growth and abiotic stressors (water, salt, and nitrogen) is crucial for optimizing fertilizer use, improving plant stress resistance, and promoting agricultural productivity and environmental sustainability. …”
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Transformer Fault Diagnosis Utilizing Feature Extraction and Ensemble Learning Model by Gonglin Xu, Mei Zhang, Wanli Chen, Zhihui Wang

“…Furthermore, optimization with IAOS algorithm increases the diagnostic accuracy of LightGBM model to 93.42%, an additional gain of 6.58%.…”
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Transformer based models with hierarchical graph representations for enhanced climate forecasting by T. Bhargava Ramu, Raviteja Kocherla, G. N. V. G. Sirisha, V. Lakshmi Chetana, P. Vidya Sagar, R. Balamurali, Nanditha Boddu

“…To improve computational efficiency and feature selection, we introduce a hybrid optimization approach (HWOA-TTA) that combines the Whale Optimization Algorithm (WOA) and Tiki-Taka Algorithm (TTA). …”
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Optimal Design of Multiband Microstrip Antennas by Self-Renewing Fitness Estimation of Particle Swarm Optimization Algorithm by Xiaohong Fan, Yubo Tian, Yi Zhao

“…In order to reduce the time of designing microstrip antenna, this paper proposes a self-renewing fitness estimation of particle swarm optimization algorithm (SFEPSO) to improve the design efficiency. …”
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Operation Optimization Strategy of Commercial Combined Electric Heating System Based on Particle Swarm Optimization Algorithm by WANG Qing, LI Congcong, WANG Pingxin, WU Qingqing, CAI Xiaoyu

“… In order to improve the energy efficiency of the electric heating system, a particle swarm optimization (PSO, Particle Swarm Optimization)-based operation optimization strategy for the direct storage combined electric heating system is proposed.A mathematical model of influencing factors inside and outside the walls of electric heating buildings is established, and the simulink toolbox in matlab is used to build the overall system under the premise of determining the quantity of electric heating.Combining demand response ideas, the objective function is to establish the minimum heating and electricity cost of the user, and different sub-modules are selected to form the control module to achieve simulation verification, and the inverse cosine method is used to update the improved particle swarm algorithm to update the learning factor to solve the set objective function.Finally, through a calculation example of electricity consumption data of an enterprise in Jinan, Shandong, comparing energy consumption and economy can be obtained: the total energy consumption throughout the day is lower than the actual energy consumption, and the electricity bill is reduced by 17.16% compared with the unoptimized time.…”
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The necessity of the Black Sea region transport structure improvement by L.V. Nazarova

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PERFORMANCE OPTIMIZATION OF TRANSMISSION GEAR BASED ON OPTIMAL MODIFICATION DESIGN by HAN Wei, REN ZhiQun

“…At the same time,it can be proved that this method can effectively improve the meshing condition of gears and is an effective means to optimize the meshing performance of gears.…”
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Optimized Model Torque Prediction Control Strategy for BLDCM Torque Error and Speed Error Reduction System by Ye Yuan, Cheng Liu, Siyu Chen, Zhenxiong Zhou

“…This paper presents an improved whale optimization algorithm (IWOA) for optimizing the model predictive torque control (MPTC) of brushless DC motor (BLDCM) to further reduce the problems of strong torque pulsation and high ripple caused by the special structure of BLDCM. …”
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Multi-Objective Optimization of Daylighting–Thermal Performance in Cold-Region University Library Atriums: A Parametric Design Approach by Yunong Gao, Shuting Zhao, Yong Huang, Hui Pan

“…In this paper, we take the library project in the cold region as a practical case, use the measured data to support the simulation experiment, combine the parametric platform and multi-objective coupling optimization algorithm to carry out digital modeling, and explore the dynamic relationship between the atrium light, heat environment, and the value of energy consumption under the influence of a variety of parameters. …”
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An Adaptive Obstacle Avoidance Model for Autonomous Robots Based on Dual-Coupling Grouped Aggregation and Transformer Optimization by Yuhu Tang, Ying Bai, Qiang Chen

“…The Harris hawk optimization (HHO) algorithm is used for hyperparameter tuning, further improving model performance. …”
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Cable Force Optimization in Cable-Stayed Bridges Using Gaussian Process Regression and an Enhanced Whale Optimization Algorithm by Bing Tu, Pengtao Zhang, Shunyao Cai, Chongyuan Jiao

“…This study proposes an integrated framework combining Gaussian process regression (GPR) with an enhanced whale optimization algorithm improved by the Salp Swarm Algorithm (EWOSSA). …”
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Machine Learning Model for Hepatitis C Diagnosis Customized to Each Patient by Leran Chen, Ping Ji, Yongsheng Ma

“…A general-purpose machine learning algorithm depends on a large amount of data and requires abundant computing power support, relies on the average level to describe the model performance, and cannot achieve optimal results on a specific problem. …”
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Towards a digital twin: Digitization and model-based optimization of the innovative high-gradient magnetic separatorMendeley Data by Marko Tesanovic, Torben Bardel, Robin Karl, Sonja Berensmeier

“…Furthermore, process efficiency is often not fully realized due to the reliance on fixed operational recipes.This study presents a digital twin framework for a pilot-scale HGMS system, integrating real-time monitoring, automated control, advanced mechanistic models, and multi-objective optimization using Bayesian algorithms. …”
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Optimized Controller Design Using Hybrid Real-Time Model Identification with LSTM-Based Adaptive Control by Yeon-Jeong Park, Joon-Ho Cho

“…Our approach integrates an optimally adaptive Proportional–Integral–Derivative (PID) controller design algorithm that estimates the coefficients of the SOPTD model in the Smith Predictor control structure and adjusts the PID controller parameters dynamically. …”
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A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…The proposed model employs an improved Squirrel Search Algorithm-based Feature Selection (ISSA-FS) to identify the most relevant features from medical data. …”
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Evaluating energy efficiency in Turkish electric distribution using network DEA and GA models by Serpil Aydin, Talat Şenel

“…For 2015, only Boğaziçi EDC is efficient among the twenty-one distribution companies evaluated in detail. The NDEA model with sub-processes provided more realistic efficiency scores than traditional DEA. …”
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An optimized spatial target trajectory prediction model for multi-sensor data fusion in air traffic management by Jian Dong, Yuan Xu, Rigeng Wu, Chengwang Xiao

“…This paper proposes an innovative network model based on the improved snow ablation optimizer algorithm. …”
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A highly generalized federated learning algorithm for brain tumor segmentation by Jun Wen, Xiusheng Li, Xin Ye, Xiaoli Li, Hang Mao

“…To address these issues, this paper proposes a client-side brain tumor image segmentation model utilizing Virtual Adversarial Training (VAT) integrated into a 3D U-Net to improve model performance under conditions of limited datasets, effectively addressing data scarcity and imbalance within the federated learning environment by optimizing the use of brain tumor image data held by each client. …”
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GCB‐YOLO: A Lightweight Algorithm for Wind Turbine Blade Defect Detection by Zhiming Zhang, Chaoyi Dong, Ze Wei, Xiaoyan Chen, Weidong Zan, Yao Xue

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Study on the Impact of Input Parameters on Seawater Dissolved Oxygen Prediction Models by Wenqing Li, Jing Lv, Yuhang Wang, Xiangfeng Kong

“…Future research will develop a parameter adaptive selection algorithm, conduct the dynamic monitoring of multi-scale environmental factors, and achieve the intelligent optimization and verification of model parameters.…”
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