Capacity Optimization and Location of BESS-SC Hybrid System for Grid Inertia Support With High Wind Power Penetration by Shami Ahmad Assery, Nan Chen, Xiao-Ping Zhang

“…This paper firstly proposes a sizing strategy based on techno-economic analysis using the Genetic Algorithm (GA) optimization technique, which can minimize the cost of the BESS-SC hybrid system while maintaining the Rate of Change of Frequency (RoCoF) within an acceptable limit. …”
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Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment by Hui Li, Yunfei Ge, Yuzhou Duan, Xu Zhang

“…Building upon this, optimal timings for phase adjustments and the optimization bus trajectories are calculated using signal control and eco-driving speed guidance models. …”
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Electricity Carbon Coupled Market Modeling Method and Market Optimization Mechanism Based on Dynamic Carbon Emission Intensity by Tong ZHAO, Xuesong LI, Hao ZHOU, Yu DING, Bin YANG, Wentao WANG, Peng WANG

“…A Markov decision iterative optimal coordination algorithm (MDIOCA) is proposed to solve the model. …”
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Performance Optimization of Synchronous Reluctance Motor using Adaptive MTPA Curve Fitting with Anti-Windup Current Control by Alex V, Rammohan A

“…Conventional scalar control methods typically rely on precomputed lookup tables or iterative optimization algorithms, which introduce computational overhead and require significant memory resources. …”
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Lattice-Based Certificateless Proxy Re-Signature for IoT: A Computation-and-Storage Optimized Post-Quantum Scheme by Zhanzhen Wei, Gongjian Lan, Hong Zhao, Zhaobin Li, Zheng Ju

“…However, most existing proxy re-signature schemes, which are predominantly based on traditional public-key cryptosystems, face security vulnerabilities and certificate management bottlenecks. While identity-based schemes alleviate some issues, they introduce key escrow concerns. …”
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Bioinspired Mobility-Aware Clustering Optimization in Flying Ad Hoc Sensor Network for Internet of Things: BIMAC-FASNET by Abdu Salam, Qaisar Javaid, Masood Ahmad

“…First, the clustering problem in network is formulated to dynamic optimization problem. An algorithm is designed based on bee intelligence, applied to select optimal UAVs CH and balanced cluster. …”
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A hybrid prediction and multi-objective optimization framework for limestone calcined clay cement concrete mixture design by Xi Chen, Weiyi Chen, Zongao Li, Pu Zhang

“…Non-dominated Sorting Genetic Algorithm-II was employed for MOO, generating Pareto fronts to minimize cost and embodied carbon while meeting strength requirements. …”
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Random forest algorithm integrated with an initial basic feasible solution in buckling analysis of a two-dimensional functionally graded porous taper beam by Ravikiran Chinthalapudi, Jagadesh Kumar Jatavallabhula, Geetha Narayanan Kannaiyan, Bridjesh Pappula, Seshibe Makgato

“…To overcome these limitations, a hybrid analytical computational methodology is proposed that integrates the novel Initial Basic Feasible Solution approach with the Random Forest algorithm. The beam is modelled using hyperbolic shear deformation theory to account for transverse shear effects, while material properties vary along both the length and thickness following a power-law distribution. …”
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Broadcasting in Stars of Cliques and Path-Connected Cliques by Akash Ambashankar, Hovhannes A. Harutyunyan

“…Determining the broadcast time for a node in an arbitrary network is NP-complete. While polynomial-time algorithms exist for specific network topologies, the problem remains open for many others. …”
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Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…In this study, we propose an integrated framework that combines a Bayesian network (BN)-based landslide susceptibility map (LSM) with an improved A* algorithm for safe and efficient route planning. The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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Optimizing spatial normalization of multisubject inner ear MRI: comparison of different geometry-preserving co-registration approaches by Johannes Gerb, Valerie Kirsch, Emilie Kierig, Thomas Brandt, Marianne Dieterich, Rainer Boegle

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Robust Optimal Control for a Microbial Batch Culture Processes: Incorporating Free Terminal Time and Sensitivity Analysis by Yang Qi, Zheng Shijin, Xie Suzhen, Feng Enmin

“…Subsequently, we develop an improved particle swarm optimization algorithm to solve this equivalent problem. …”
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Optimization of diagnostics of retinopathy of prematurity stages based on the integration of clinical data using the Key to Diagnosis I software by O. A. Pererva, M. A. Kovalevskaya

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Multi-objective optimization of lithium-ion battery designs considering the dilemma between energy density and rate capability by Xiao-Ying Ma, Wen-Ke Zhang, Ying Yin, Kailong Liu, Xiao-Guang Yang

“…A physics-based pseudo-2D model, validated against experimental data, generates data to train the surrogate model, which is combined with the NSGA-II algorithm for rapid optimization. Three different objective calculation methods are compared to identify the maximum sum of energy densities, lowest polarization, and most balanced performance, respectively. …”
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Hybrid active-passive thermal management system for deep wells: Long-term stability and multi-objective optimization by Zongwei Yao, Haomin Li, Hongxu Xu, Hongfei Yang, Qiushi Bi, Tianshuang Xu

“…To address this challenge, this study proposes a hybrid active-passive thermal management system integrating vacuum insulation, phase change materials (PCMs), and an optimized curved flow channel. A multi-objective optimization framework combining Kriging surrogate modeling and NSGA-II algorithm is developed to maximize heat transfer coefficient (h) while minimizing pressure drop (P). …”
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Physics-informed modeling and process optimization of friction stir welding of AA7075-T6 with a zinc interlayer by Dejene Alemayehu Ifa, Dame Alemayehu Efa, Naol Dessalegn Dejene, Sololo Kebede Nemomsa

“…This study is the first to combine a zinc interlayer with machine learning (ML) based optimization in the FSW of AA7075-T6. Artificial Neural Networks (ANN), Support Vector Regression (SVR), Random Forest Regression (RFR), a Genetic Algorithm (GA) for optimization, and Response Surface Methodology (RSM) for statistical modeling were used to analyze a dataset of 60 observations. …”
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Personalized EEG-guided brain stimulation targeting in major depression via network controllability and multi-objective optimization by Aihua Wang, Jingnan Sun

“…A multi-objective optimization algorithm (NSGA-II) was used to select optimal node–frequency–amplitude combinations minimizing control energy while maximizing network efficiency gain and structural restoration. …”
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Optimization location routing problem (LRP) of humanitarian aid distribution in Sigi district using NSGA II methods by Serli Bombang, Bonivasius Prasetya Ichiarto, Humiras Hardi Purba

“…It utilizes the NSGA-II algorithm for multi-objective optimization and the Displaced Ideal Solution (DIS) method to select the best solution from the Pareto front.…”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…The results demonstrate that the proposed H-SAGA approach consistently achieves 5–10 percentage points higher profit increment ratios than other benchmark optimization algorithms (such as GA, SA, PSO, and ACO), alongside faster convergence and notable robustness against environmental and economic variability. …”
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