Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…By leveraging the adaptability of fuzzy logic to adjust PSO parameters dynamically, the method optimizes the allocation and utilization of diverse energy resources within a grid-connected microgrid. …”
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Research on accuracy enhancement methods for highway slope deformation monitoring based on the BeiDou system. by Yuhong Luo, Geyu Chen

“…Furthermore, through multi-source data fusion optimization, the improved positioning accuracy reached a 71.16% enhancement, and deformation monitoring accuracy was improved by 66.84%. …”
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DynaFusion-SLAM: Multi-Sensor Fusion and Dynamic Optimization of Autonomous Navigation Algorithms for Pasture-Pushing Robot by Zhiwei Liu, Jiandong Fang, Yudong Zhao

“…At the same time, the introduction of multi-source mileage fusion can effectively avoid the phenomenon of large-scale offset or drift in the process of map construction. …”
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A Universal Method for Achieving Ultra‐Low Contact Resistances in Organic Electrochemical Transistors by Luis‐Abraham Lozano‐Hernández, Patrice Rannou, Yvan Bonnassieux, Sébastien Sanaur

“…Beyond device geometry, reaching optimal operation of organic electronic circuits requires the optimization of the physico‐chemical properties of the channel. …”
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An Improved Decline Curve Analysis Method via Ensemble Learning for Shale Gas Reservoirs by Yu Zhou, Zaixun Gu, Changyu He, Junwen Yang, Jian Xiong

“…The results show that the Improved DCA model achieved superior performance—with an mean absolute error (MAE) of 0.0660, an mean squared error (MSE) of 0.0272, and an <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> value of 0.9882—and exhibited greater stability across various samples and conditions. This method provides a reliable tool for long-term production forecasting and optimization without extensive geological or engineering information.…”
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Study on Vibration Characteristics and Transmission Path of Mountain Rack Trains Based on the OPTA Method by Liangzhao Qi, Xingqiao Deng, Liyuan Zeng, Chenglong Dong, Yixin Xu, Shisong Wang, Yucheng Liu

“…However, due to the multi-source vibration of gear teeth, wheels, rails, and suspensions, it is difficult to clearly define the vibration characteristics and vibration transmission path of the train, which has a serious impact on its vibration noise suppression and optimization. …”
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Optimization of Precious Metals Recovery from Electronic Waste by Chromobacterium violaceum Using Response Surface Methodology (RSM) by Wan Nur Fazlina Abdol Jani, Fatihah Suja’, Sharifah Iziuna Sayed Jamaludin, Nor Fadilah Mohamad, Noor Hidayu Abdul Rani

“…An effective recovery technology will be valuable in the future because the concentration of the precious metal contained in the source can be a key driver in recycling technology. …”
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Dynamic Performance Improvement of a Single-Phase VSI with Digital Implementation of an On-Line Optimal Trajectory Control Algorithm by Shah Zaman, Yan Zhang, Jinjun Liu, Danni Yang, Zhenchao Li

“…A single-phase voltage source inverter (VSI) still suffers from a long settling time and significant voltage overshoot/undershoot under the abrupt step-change of load current. …”
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Optimal Split Ratio in Double-Stator Permanent-Magnet Motors Considering Loss Limitations for Robot Joint Applications by Tianran He, Yang Shen, Wei Li, Dawei Liang

“…Additionally, an investigation into the electromagnetic characteristics of the optimized DSPM motor was conducted using the finite element method. …”
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Application of Taguchi Experimental Design in Optimization of Levulinic Acid Production from Cellulose Derived From Millet Stalk by Shehu Ibrahim, Abdullahi Sokoto Muhammad, Kabiru Jega Umar, Ibrahim Magami Muhammad

“…Cellulose is the primary component of lignocellulosic biomass and the main source of renewable materials in chemical industry. …”
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Optimal operation for hybrid AC and DC systems under typhoon disaster considering branch switching and frequency security by Changfeng Liao, Li He, Zhuangxi Tan, Bin Xie, Yong Li, Chaoyang Chen, Yijia Cao

“…To address this issue, this paper proposes an optimal operation method for hybrid AC/DC systems with voltage source converters (VSCs) during extreme events. …”
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Artificial neural network analysis of Jeffrey hybrid nanofluid with gyrotactic microorganisms for optimizing solar thermal collector efficiency by Anup Kumar, Bhupendra K. Sharma, Bandar Almohsen, Laura M. Pérez, Kamil Urbanowicz

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Optimization of Microwave-Assisted Extraction Saponins from Sapindus mukorossi Pericarps and an Evaluation of Their Inhibitory Activity on Xanthine Oxidase by Baoqin Deng, Zaizhi Liu, Zhengrong Zou

“…A microwave-assisted extraction (MAE) method was applied to separate saponins from Sapindus mukorossi pericarps. …”
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Multi-Time Scale Optimal Dispatch of Distribution Network with Pumped Storage Station Based on Model Predictive Control by Pengyu Pan, Zhen Wang, Gang Chen, Huabo Shi, Xiaoming Zha

“…To address this, a multi-time scale optimal dispatch method based on model predictive control is proposed, including a day-ahead stage and an intra-day rolling stage. …”
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GLTDNet: Cross-Domain Road Extraction Through Collaborative Optimization of Global-Local Feature Enhancement and Topological Decoupling by Jie Chen, Changxian He, Hao Wu, Jun Zhang, Siqiang Rao, Songshan Zhou, Jingru Zhu

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Optimization and Simulation of Flat Area Sites Based on Probability Matching and Transfer Intensity Using Remote Sensing Precipitation by Chen Yu, Huaiyong Shao, Xingchuan Yang, Gang Liu, Qi Xin, Jiaming Gu

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The Optimal Scheduling of Integrated Energy System Considering the Incentive and Punishment Mechanism of Electric and Thermal Carbon Emission Factors by Kaiyan Wang, Hengxiang He, Ningning Yang, Xiaowei Wang, Rong Jia

“…To comprehensively explore the potential for carbon reduction through source-load synergy and achieve low-carbon and high-efficiency operation of the system, an IES optimal scheduling method that incorporates a reward and punishment mechanism for dynamic electricity and thermal carbon emission factors is proposed. …”
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Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads by Keyong Hu, Qingqing Yang, Lei Lu, Yu Zhang, Shuifa Sun, Ben Wang

“…To further manage uncertainties, a distributionally robust optimization (DRO) approach is introduced. This method uses 1-norm and ∞-norm constraints to define an ambiguity set of probability distributions, thereby restricting the fluctuation range of probability distributions, mitigating the impact of deviations on optimization results, and achieving a balance between robustness and economic efficiency in the optimization process. …”
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Risk–Cost Equilibrium for Grid Reinforcement Under High Renewable Penetration: A Bi-Level Optimization Framework with GAN-Driven Scenario Learning by Feng Liang, Ying Mu, Dashun Guan, Dongliang Zhang, Wenliang Yin

“…Spatial congestion maps and scenario risk-density plots further illustrate the ability of adversarial learning to reveal latent structural bottlenecks not captured by conventional methods. This work offers a new methodological paradigm, in which optimization and generative AI co-evolve to produce robust, data-aware, and stress-responsive transmission infrastructure designs.…”
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Optimization Driven Variational Autoencoder GAN for Artifact Reduction in EEG Signals for Improved Neurological Disorder and Disability Assessment by Sikkandar Mohamed Yacin, Sabarunisha Begum S., Alassaf Ahmad, AlMohimeed Ibrahim, Alhussaini Khalid, Aleid Adham, Alhaidar Abdulrahman Khalid

“…This study introduces an innovative method for minimizing artifacts in electroencephalography (EEG) signals by integrating brainstorm optimization (BSO) with a variational autoencoder generative adversarial network (VAE-GAN), resulting in the BrOpt_VAGAN model. …”
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