Support Vector Machine Berbasis Feature Selection Untuk Sentiment Analysis Kepuasan Pelanggan Terhadap Pelayanan Warung dan Restoran Kuliner Kota Tegal by Oman Somantri, Dyah Apriliani

“…Sentiment analysis is used to provide a solution related to this problem by applying the Support Vector Machine (SVM) algorithm model. The purpose of this research is to optimize the generated model by applying feature selection using Informatioan Gain (IG) and Chi Square algorithm on the best model produced by SVM on the classification of customer satisfaction level based on culinary restaurants at Tegal City so that there is an increasing accuracy from the model. …”
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Indoor Positioning System based on SSA-ELM Neural Network for Visible Light by JIA Kejun, NIU Zhen, YU Kai, ZHANG Zhicong, PENG Duo, CAO Minghua

“…【Objective】The Extreme Learning Machine (ELM) neural network algorithm in the traditional indoor Visible Light Positioning (VLP) system suffers from unstable convergence and a tendency to get stuck in local optimal states, resulting in decreased positioning accuracy. …”
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Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…We aim to optimize a deep MARL algorithm with minimal modifications to the well-known QMIX approach. …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…This study introduces a machine learning-based framework for predicting vegetation flow resistance, incorporating nine ML methods, including SVM, XGBoost, and BP. To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
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Research on Dynamic Storage Location Assignment of Picker-to-Parts Picking Systems under Traversing Routing Method by Xiangbin Xu, Chenhao Ren

“…Then, the adjustment gain model of dynamic storage location assignment is built, and a genetic algorithm is designed to find the final adjustment solution. …”
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Robust Planning for Hydrogen-Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage by Shufan Wang, Dong Yang, Linglu Zhang, Lingzhi Chenmei

“…This paper proposes an optimal planning model for the hydrogen-based integrated energy system (HIES) considering power to heat and hydrogen (P2HH) and seasonal hydrogen storage (SHS) to take full advantage of multienergy complementarity. …”
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Adaptive robust position control scheme for an electromagnetic levitation system with experimental verification. by Ziwei Wu, Kuangang Fan, Ping Yi

“…Firstly, a nonlinear model of the electromagnetic levitation ball system was established; Secondly, robust sliding mode control is combined with linear active disturbance rejection control, and an adaptive parameter tuning strategy is introduced for the PD module in LADRC; Meanwhile, an improved whale optimization algorithm was proposed to address the issue of excessive adjustable parameters in the controller; In addition, the stability and convergence of the control algorithm were proven using the Lyapunov equation; Finally, in order to verify the effectiveness of the control method, PID, LADRC, CS-LADRC, and I-LADRC were introduced for simulation analysis and experimental verification. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…However, the underlying machine learning strategy used to develop and refine the EGF algorithm has not yet been detailed. Here, we present how our EGF Model—trained on procedural outcomes from 199 fully anonymized retrospective patient datasets—identifies clinically significant sources of AF and how this machine learning–driven hyperparameter optimization underlies its clinical effectiveness. …”
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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs by Kaifeng Geng, Chunming Ye, Zhen hua Dai, Li Liu

“…This paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. …”
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A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder by Hoyeon Lee, Jaehong Yu

“…In modern industrial systems, establishing the optimal maintenance policy for rotating machinery is essential to improve productivity and prevent catastrophic accidents. …”
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Intelligent Trust Evaluation Method for Underwater Sensor Networks Based on Fuzzy Clustering and Dynamic Weight Allocation by Zhaohui WANG, Guangjie HAN, Jiaxin DU, Chuan LIN, Lei WANG

“…First, a hierarchical dynamic topology model of the USN was developed to enhance universality. …”
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Lithium-Ion Battery State of Health Estimation Based on Feature Reconstruction and Transformer-GRU Parallel Architecture by Bing Chen, Yongjun Zhang, Jinsong Wu, Hongyuan Yuan, Fang Guo

“…The results show that the RMSE of the state of health estimation by the proposed method is 0.0071, which is an improvement of 61.41% in the accuracy of its baseline model.…”
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Risk assessment of tunnel water inrush based on Delphi method and machine learning by Leizhi Dong, Qingsong Wang, Weiguo Zhang, Yongjun Zhang, Xiaoshuang Li, Fei Liu

“…Then, the Radial Basis Function (RBF) network, improved by the Locally Linear Embedding (LLE) algorithm and the Particle Swarm Optimization (PSO), is applied to predict the risk level. …”
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A Real-Time Signal Measurement System Using FPGA-Based Deep Learning Accelerators and Microwave Photonic by Longlong Zhang, Tong Zhou, Jie Yang, Yin Li, Zhiwen Zhang, Xiang Hu, Yuanxi Peng

“…The results show that the time of inference saves 28–31% for the DNN model and 71–73% for the LSTM + DNN model compared to running on graphic processing unit (GPU). …”
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Combating electricity fraud: Employing hybrid learning and computer vision for sustainable energy management by Jui-Sheng Chou, Nader Anwar Charaf, Dani Nugraha Limantono, Hoang-Minh Nguyen

“…Additionally, the study explores hybrid and ensemble AI models that combine the best-performing algorithms to improve prediction accuracy. …”
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MULTIDIMENSIONAL ANALYSIS OF PHYSICOCHEMICAL TRANSFORMATIONS AND SENSORY ATTRIBUTES OF GREEN AND ROASTED COFFEE by OTTO KETNEY, IULIAN CHIRILOV, OLGA DRĂGHICI

“…Utilizing a multi-objective optimization algorithm, Ethiopian coffee emerged as possessing the most optimal physicochemical characteristics. …”
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Application of 5G + edge computing technology in intelligent monitoring construction of electricity business office by Wei Cui, Junwei Li, Wei Ge, Bo Zhang, Tianwei Liu

“…This paper also proposes an edge scheduling algorithm based on game theory, which enables each edge device to choose the optimal data processing task according to its own utility function through a non-cooperative game model, realizing the optimization of the efficacy and accuracy of data processing. …”
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SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…Through cross-domain validation of the ALU and HIT-UAV datasets, the ablation experiments and comparative analysis fully validated the effectiveness of the algorithmic improvement, and its detection accuracy and robustness were significantly improved over the baseline model. …”
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A Multi-Strategy ALNS for the VRP with Flexible Time Windows and Delivery Locations by Xiaomei Zhang, Xinchen Dai, Ping Lou, Jianmin Hu

“…This VRP-CS is formally modeled as a bi-objective optimization problem, which is an NP-hard problem. …”
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Securing federated learning: a defense strategy against targeted data poisoning attack by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Tony Jan, Sarabjot Singh, Md. Ashraf Uddin

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