Consider the master-slave game model of integrated energy system with step carbon trading and demand response by Yi Zhang, Zhezhou Zhang

“…In the context of deepening energy coupling and the high penetration of renewable energy, this paper proposes a master-slave game model incorporating comprehensive demand response and a stepped carbon trading mechanism. The goal is to optimize scheduling of demand response resources and fully leverage the flexibility of energy use within an integrated energy system while addressing conflicts of interest among multiple stakeholders, thereby enhancing trading revenue in Energy Markets while considering lower carbon emissions. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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An Adaptive Unscented Kalman Ilter Integrated Navigation Method Based on the Maximum Versoria Criterion for INS/GNSS Systems by Jiahao Zhang, Kaiqiang Feng, Jie Li, Chunxing Zhang, Xiaokai Wei

“…On this basis, fully considering the high-order moments of estimation errors, the maximum versoria criterion is introduced as the optimization criterion to construct a novel cost function, further effectively suppressing deviations caused by non-Gaussian disturbances and improving system navigation accuracy. …”
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Machine Learning-Driven Acoustic Feature Classification and Pronunciation Assessment for Mandarin Learners by Gulnur Arkin, Tangnur Abdukelim, Hankiz Yilahun, Askar Hamdulla

“…This study confirms the effectiveness of objective assessment methods based on formant analysis in speech acquisition research, provides a theoretical basis for algorithm optimization in speech evaluation systems, and holds significant application value for the development of Computer-Assisted Language Learning (CALL) systems and the improvement of multi-ethnic Mandarin speech recognition technology.…”
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Cross-modal adaptive reconstruction of open education resources by Tang Shengju, Feng Li, Zhan Wang, Xie Zhaoyuan

“…The dynamic knowledge graph improved recommendation accuracy by 35.5% while achieving low system latency (1.45 s average, 99% of responses ≤ 1.8 s). …”
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Deep Reinforcement Learning-Based Multi-Agent System with Advanced Actor–Critic Framework for Complex Environment by Zihao Cui, Kailian Deng, Hongtao Zhang, Zhongyi Zha, Sayed Jobaer

“…Our evaluation compares MA-PPO against other DRL algorithms, showing a 30.67% performance improvement over the baseline algorithm.…”
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Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

“…Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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Flood resilience assessment of region based on TOPSIS-BOA-RF integrated model by Guofeng Wen, Fayan Ji

“…Training samples are then input into the Butterfly Optimization Algorithm(BOA) to optimize the key parameters in the Random Forest(RF). …”
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Dynamic characteristics of a semi-active fractional-order inerter-based suspension with acceleration-velocity switch control by Yong Wang, Jiachen Li, Mingzhu Ji, Xiwen Qiao, Yang Wang

“…The optimized SA-FOIB suspension further improves the dynamic performance of the suspension dynamic deflection and wheel dynamic load, which the corresponding RMS values are smaller than the unoptimized SA-FOIB suspension, while deteriorates the vehicle body acceleration.…”
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Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control by Peng Ji, Fengrui Han, Yifan Zhao

“…First, a seven-degree-of-freedom (7-DOF) vehicle dynamics model is established and optimized with a layered control strategy. The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. …”
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A Full-Profile Measurement Method for an Inner Wall with Narrow-Aperture and Large-Cavity Parts Based on Line-Structured Light Rotary Scanning by Zhengwen Li, Changshuai Fang, Xiaodong Zhang

“…Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. …”
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition by Mashael Maashi, Huda G. Iskandar, Mohammed Rizwanullah

“…Finally, the attraction-repulsion optimization algorithm (AROA) adjusts the hyperparameter values of the CNN-BiGRU-A method optimally, resulting in more excellent classification performance. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…Abstract Forest fires are severe ecological disasters worldwide that cause extensive ecological destruction and economic losses while threatening biodiversity and human safety. …”
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Evaluation of Multi-Class Classification Performance Lung Cancer Through K-NN and SVM Approach by Muh. Indra Endriartono Saputra Troy, Sitti Rahmah Jabir, Siska Anraeni

“…Lung cancer is a lung disease caused by genetic changes in respiratory epithelial cells, resulting in uncontrolled cell proliferation. In an effort to improve diagnosis and treatment, this study proposes an approach for multiclass performance evaluation using K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms based on 2024 data. in this study KNN is implemented conventionally while SVM applies 2 kernel processes, namely Linear and Polynominal. …”
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Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets. by Qifeng Liu, Yong Han, Lu Shen, Jialei Du, Marzia Hoque Tania

“…The method integrates automatic tissue attenuation techniques, which enhance the image contrast by removing non-essential tissue components while preserving important tissues and bones. Additionally, we apply an improved Type-II fuzzy set algorithm to further optimize image sharpness. …”
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Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process by Yang Zhou, Xinmin Tang, Xuanming Ren

“…The experimental results show that the IMM algorithm with the improved model set, described in this paper, is more accurate than the IMM algorithm and prediction results of the current statistical model, as described in the literature. …”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…The dynamic reconfiguration of active distribution networks (ADNDR) essentially belongs to a complex high-dimensional mixed-integer nonlinear stochastic optimization problem. Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. …”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…This article presents a novel change detection approach that employs the hierarchical density-based clustering algorithm to improve the accuracy and robustness of change map generation. …”
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Traffic light detection and recognition based on deep learning for autonomous-rail rapid tram by XIONG Qunfang, LIN Jun, YUAN Xiwen, XU Yanghan, YUE Wei, LI Yuanzhengyu

“…This paper presents study efforts in this field through the application of a deep learning algorithm. Firstly, regions of interest (RoIs) for traffic lights were determined using high-precision map information to narrow the detection range and improve the detection speed. …”
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