Control of steering wheel idle jitter based on optimization of engine suspension system with verifications using multi-sensor measurement by Shuilong He, Binqiang Chen, Zhansi Jiang, Yanxue Wang, Fuyun Liu

“…A multi-sensor-based measurement strategy was utilized to evaluate the idle jitter severity of the steering wheel. In order to improve the indicators of the decoupling degree, the vibration transmissibility, and the resonant frequency distributions of the engine suspension system, an optimization model of engine suspension system was established. …”
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Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems by Wanru Tang, Haoze Qin, Shuang Kang

“…Abstract As a swarm intelligence algorithm, Dung beetle optimizer (DBO) was inspired by the behavior pattern of dung beetles for survival. …”
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Ground-Truth-Free 3D Seismic Denoising Based on Diffusion Models: Achieving Effective Constraints Through Embedded Self-Supervised Noise Modeling by Zhonghan Zhang, Guihe Qin, Yanhua Liang, Minghui Sun, Yingqing Wang, Jiaru Song

“…Furthermore, the algorithm integrates the noise distribution estimation network into the diffusion model to further guide and refine the sampling process, thereby optimizing computational complexity and improving detail representation. …”
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Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production by Chengcai He, Jiaxing Deng, Jingchun Wu, Beicheng Qin, Jinxiang Chen, Yan Li, Qiangsheng Huang

“…When actual qualification rates exceed 88.1%, the model’s regression fit also surpasses 88.1%, indicating strong alignment between predicted and actual performance. (2) Compared with other algorithmic models, the proposed approach achieves a predictive accuracy of over 94.7%. …”
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Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm approach for global maximum power point tracking in PV systems under different shading conditions by Nivine Guler, Zied Ben Hazem, Ali Gunes, Firas Saidi

“…The ANFIS is ideal in modeling the nonlinearity and uncertain nature of PV systems; the Genetic Algorithm (GA) then dynamically determines the optimal Proportional–Integral–Derivative (PID) controller parameters by minimizing the error between the actual power output and the maximum power output calculated in ANFIS. …”
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Enhanced thyroid nodule detection and diagnosis: a mobile-optimized DeepLabV3+ approach for clinical deployments by Changan Yang, Muhammad Awais Ashraf, Mudassar Riaz, Pascal Umwanzavugaye, Kavimbi Chipusu, Hongyuan Huang, Yueqin Xu

“…The obtained segmentation results suggest promising directions for future research, especially in the early detection of thyroid nodules. Deploying this algorithm on mobile devices offers a practical solution for early diagnosis and is likely to improve patient outcomes.…”
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Hybrid fuzzy logic–PI control with metaheuristic optimization for enhanced performance of high-penetration grid-connected PV systems by Mohamed Ahmed Ebrahim Mohamed, Sayed A. Ward, Mohamed F. El-Gohary, M. A. Mohamed

“…To optimize the FLC-PI control scheme, several artificial intelligence (AI)-based metaheuristic optimization techniques (MOTs) are employed to simultaneously tune all control parameters—namely Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and the Arithmetic Optimization Algorithm (AOA)—are employed. …”
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Calculation method of line loss rate of substation areas considering tidal current variation with photovoltaic power generation access by Shengbo Sun, Chao Cheng, Shujun Ji, Wei Cui, Wei Ge, Shifang Hao

“…The proposed method employs an improved K-medoids clustering algorithm for substation area classification, optimized by an enhanced Cuckoo algorithm to minimize classification errors. …”
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Research on Joint Stiffness Identification and Error Compensation of the Serial Six DOF Robot by Ping Rui, Guifang Qiao, Xiulan Wen, Ying Zhang, Dongxia Wang

“…Secondly，in order to improve the identification accuracy and efficiency of joint stiffness parameters, the BP neural network is applied to fit the stiffness error model to optimize the initial population fitness of genetic algorithm. …”
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RESEARCH ON KEYWORD MINING OF ACADEMIC LIBRARY SUBJECT SERVICE by Fan Zhang

“…Empirical research has shown that the subject service model based on keyword mining can effectively improve the level of subject service in libraries, providing users with more accurate and comprehensive information resource services. …”
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Clustering analysis of Yue opera character tone trends based on quantum particle swarm optimization for fuzzy C-means. by Yuhang Zhang, Xiaofeng Wu, Jiawei Xu, Zihao Ning, Xiao Han

“…We designed a detection algorithm using trend data to validate our clustering method, thereby enhancing the accuracy of the analysis of tonal ranges and potential models. …”
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Study on the Lightweighting Strategy of Target Detection Model with Deep Learning by Junli Hu

“…Aiming at the high miss detection and false detection rate of traditional SSD (single shot multibox detector) target detection algorithm in target detection, this paper proposes a lightweight detection algorithm for deep learning target detection model in order to improve the detection accuracy. …”
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A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals by Priyaranjan Kumar, Prabhat Kumar Upadhyay

“…Abstract In order to detect epileptic spikes, this paper suggests a deep learning architecture that blends 1D residual convolutional neural networks (1D-ResCNN) with a hybrid optimization strategy. The Layer-wise Adaptive Moments (LAMB) and AdamW algorithms have been used in the model’s optimization to improve efficiency and accelerate convergence while extracting features from time and frequency domain EEG data. …”
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A Fusion Model for Predicting the Vibration Trends of Hydropower Units by Dong Liu, Youchun Pi, Zhengyang Tang, Hongpeng Hua, Xiaopeng Wang

“…The fusion model first employed a waveform matching extension method based on parameter ergodic optimization to extend the original signal. …”
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Optimizing Electric Cold-Chain Vehicle Scheduling for Sustainable Urban Logistics: A Novel Framework Balancing Freshness and Vehicle Charging by Zhenkun Gan, Peiwu Dong, Zhengtang Fu, Yanbing Ju, Yajun Shen

“…Subsequently, we develop a mixed-integer programming model to optimize freshness preservation. Additionally, we design a state-of-the-art algorithm based on an improved genetic algorithm to solve the scheduling model effectively. …”
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Power Adaptation for Optimizing Secrecy Energy Efficiency in NOMA-Enabled Underlay Cognitive Radio Networks and DNN-Based Evaluation by P. P. Hema, A. V. Babu

“…The combination of Non-orthogonal multiple access (NOMA) and cognitive radio (CR) has become a reliable solution for improving spectrum efficiency in wireless networks. …”
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Transmission Error Prediction of RV Reducer based on SSA-BP by Houzhen Sun, Hongbing Yuan, Bin Yu

“…In response to this situation， an optimized BP neural network quality prediction model based on the Sparrow Search Algorithm （SSA） is established. …”
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Research on scenario recognition for THz channels based on mRMR-GA by HAO Xinyu, LIAO Xi, WANG Yang, LIN Feng, LUO Jiao, ZHANG Jie

“…To address the challenges of excessive feature parameter redundancy and insufficient scene correlation in terahertz (THz) channel scenario recognition, a recognition algorithm integrating the minimal redundancy maximal relevance (mRMR) criterion with genetic algorithm (GA) optimization was constructed based on feature selection theory and evolutionary computation principles. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…In this paper, the bilevel programming model of the public transport network considering factors such as the per capita occupancy area and travel cost of different groups was established, to alleviate the urban transportation equity and optimize the urban public transport network under fairness constraints. …”
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Interpretable machine learning for predicting optimal surgical timing in polytrauma patients with TBI and fractures to reduce postoperative infection risk by Xing Han, Jia-Hui Zhang, Xin Zhao, Xi-Guang Sang

“…SHAP and LIME algorithms were utilized for model interpretation, elucidating the importance and predictive thresholds of the variables. …”
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