Diagnosis Method for High-Speed Train Axle Box Bearing Slight Faults Based on Improved SAE and Temperature-Vibration Fusion by XU Xiao, SONG Dongli, WANG Zifan

“…［Method］ First, an AE (auto encoder) driven bearing temperature feature extraction method is designed to obtain the abnormal bearing temperature features, and EMD (empirical modal decomposition) method is used to process the vibration signal，so as to obtain the statistical features of the effective vibration IMF (intrinsic modal function). Then, by optimizing the dimensionality reduction algorithm based on SAE (stacked auto encoder), an effective fusion method of temperature-vibration features is proposed to achieve nonlinear fusion and dimensionality reduction of temperature and vibration features. …”
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Evolutionary Cost Analysis and Computational Intelligence for Energy Efficiency in Internet of Things-Enabled Smart Cities: Multi-Sensor Data Fusion and Resilience to Link and Devi... by Khalid A. Darabkh, Muna Al-Akhras

“…Thorough simulations and comparative analysis reveal the protocol’s superior performance across key performance metrics, namely, network lifespan, energy consumption, throughput, and average delay. When compared to the most recent and relevant protocols, including the Particle Swarm Optimization-based energy-efficient clustering protocol (PSO-EEC), linearly decreasing inertia weight PSO (LDIWPSO), Optimized Fuzzy Clustering Algorithm (OFCA), and Novel PSO-based Protocol (NPSOP), our approach achieves very promising results. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm by Zhiqing Zhang, Zicheng He, Yuguo Wang, Feng Jiang, Weihuang Zhong, Bin Zhang, Yanshuai Ye, Zibin Yin, Dongli Tan

“…This aims to further improve the utilization and efficiency of SCR. In this study, a fuzzy gray relational analysis coupled with random forest (RF) and back propagation artificial neural network (BP-ANN) model was developed. …”
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Vehicle scheduling optimization for demand responsive transit with flexible stops by SHEN Zikang, JIN Wenzhou, ZHENG Yajing

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Progress and perspectives on genomic selection models for crop breeding by Dongfeng Zhang, Feng Yang, Jinlong Li, Zhongqiang Liu, Yanyun Han, Qiusi Zhang, Shouhui Pan, Xiangyu Zhao, Kaiyi Wang

“…A series of algorithms have been proposed to improve the prediction accuracy of genomic selection. …”
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Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…To address these challenges, this paper presents an innovative tool wear prediction method that integrates a nonlinear mean function and a multi-kernel function-optimized GPR model combined with an LSTM-enhanced particle filter algorithm. …”
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Frequency Control Method for Distributed Energy Systems Based on Nash Equilibrium Quantum Particle Swarm Optimization by YI Kang, LUO Wenguang, WANG Tao, CHEN Yufeng

“…The optimization capability of NEQPSO proved clearly superior to that of particle swarm algorithm (PSO) and genetic algorithm (GA). …”
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Enhancing molecular property prediction with quantized GNN models by Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije

“…This paper presents a systematic approach to molecular networks by integrating GNN models with the DoReFa-Net quantization algorithm. …”
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DESIGN AND PERFORMANCE ANALYSIS OF A DOUBLE LAYER VIBRATION ISOLATOR SUITABLE FOR AMMUNITION ROAD TRANSPORTATION by 张皓宇, 韩保红, 程兆刚, 曹洪娜, 刘俊延

“…On this basis, the corresponding optimization rules are set, and the NSGA-II optimization algorithm is used to optimize the system parameters, and the optimal parameters of the double-layer vibration isolator are obtained. …”
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Robust adaptive control with dung beetle optimization algorithm and disturbance observer for load displacement tracking of shock absorber damper test bench. by Xiangfei Tao, Kailei Liu, Dong Han, Jing Yang, Hongbin Qiang

“…The dung beetle optimization algorithm is specifically designed to iteratively optimize the control parameters of the robust adaptive controller. …”
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Research on rock burst prediction based on an integrated model by Junming Zhang, Qiyuan Xia, Hai Wu, Sailei Wei, Zhen Hu, Bing Du, Yuejing Yang, Huaixing Xiong

“…Additionally, the sparrow search algorithm (SSA) is employed to optimize hyperparameters, further improving the model’s performance. …”
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Enhanced OCR Recognition for Madurese Text Documents: A Genetic Algorithm Approach with Tesseract 5.5 by Muhammad Nazir Arifin, Muhammad Umar Mansyur, Ali Rahman, Nindian Puspa Dewi, Fauzan Prasetyo Eka Putra

“…Further optimization through language model selection, particularly using the Occitan (OCI) model, yielded 100% accuracy in specific test cases. …”
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Research on cooperative control strategy for high efficiency and energy saving in virtually coupled train sets based on two-layer optimization by JIANG Sidun, FENG Jianghua, ZHANG Zhengfang, SHI Ke, LUO Qinyang

“…This key information serves as intermediate transfer variables within this two-layer model. The lower layer concentrates on energy-saving optimization, establishing an objective function for energy saving and utilizing a multi-objective particle swarm algorithm to optimize cruising curves. …”
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Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic by Bin Yang, Bin Song, Yadegar Abdi

“…Squeeze Net carefully learns complex data patterns to produce reliable predictions, while FCOA focuses on improving the prediction framework. This study has culminated in the creation of a comprehensive forecasting model for electricity demand. …”
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A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration by Lijing Qin, Zhao Zhou, Huan Liu, Zhengang Yan, Yongqiang Dai

“…To solve this model, a deep reinforcement learning-based seagull optimization algorithm (DRL-SOA) is proposed, which integrates deep reinforcement learning with the seagull optimization algorithm (SOA) for adaptive optimization. …”
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Leveraging Game Theory to Design Incentive-Compatible Time-Varying electricity pricing with Demand-Side management by Magda I. El-Afifi, Bishoy E. Sedhom, Abdelfattah A. Eladl, Padmanaban Sanjeevikumar, Samaa Fawzy

“…This study investigates a novel approach to improve energy efficiency through a Demand Response (DR) program with a Game Theory (GT)-based Time-of-Use (ToU) pricing model. …”
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Optimization Design of Node Placement Manipulators Based on Working Area and Response Speed by Huang Zhiqiang, Duan Yuxing, Song Xiaowei, Wang Jie, Fu Mingwei, Sun Haoxiang, Li Gang

“…As the key equipment of data acquisition in oil and gas exploration, the node can be replaced by a mechanical arm because of its long-term continuous work and high efficiency, but the structure rigidity is weak and the motion ability is poor, so the structure optimization and lightweight design are carried out to improve the structure rigidity and motion ability. …”
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Optimizing the Joint Replenishment and Channel Coordination Problem under Supply Chain Environment Using a Simple and Effective Differential Evolution Algorithm by Lin Wang, Hui Qu, Shan Liu, Can Chen

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Fusion of Visible and Infrared Images Using a Reinforcement Learning System Based on Fuzzy Logic and Convolution Optimized with Wild Horse Algorithm by Mahvash Zarimeidani, Amir Amirabadi, Nasrin Amiri, Iman Ahanian, Siavash Es’haghi

“…This hybrid reinforcement learning system was optimized using algorithms including wild horse optimization (WHO), genetic algorithm (GA), and particle swarm optimization (PSO) to improve specific fusion metrics such as image correlation, similarity coefficient, image entropy, and signal-to-noise ratio. …”
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