ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11 by Zhe Zhang, Zhongyang Zhang, Gang Li, Chenxi Xia

“…Aiming at the problems of insufficient vehicle detection accuracy, high misdetection and omission rate, and heavy model computational burden caused by complex lighting conditions, target occlusion, and other factors in urban traffic scenarios, this paper proposes an improved lightweight detection network, ZZ-YOLO. Firstly, the current mainstream target detection algorithms lack components to improve the network’s focus on the edges of the objects, which can indirectly lead to unclear classification and localization. …”
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Optimized Electric Vehicles Wireless Charging: Applicative Models for Supporting Decision Makers by Cristian Giovanni Colombo, Ryosuke Ota, Michela Longo

“…The work proposes an optimization algorithm for each context and identifies outputs for 3 different car models with different heights above the ground (0.10 m, 0.20 m and 0.30 m). …”
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Integrated Approach to Optimizing Selection and Placement of Water Pipeline Condition Monitoring Technologies by Diego Calderon, Mohammad Najafi

“…This article introduces a unified framework and methods for optimally selecting condition monitoring technologies while locating their deployment at the most vulnerable pipe segments. …”
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Genetic Neuro-Fuzzy Approach towards Routing in Industrial IoT by Olena Semenova, Natalia Kryvinska, Andriy Semenov, Volodymyr Martyniuk, Olha Voitsekhovska

“…A rules base was developed. To improve the rule base of the ANFIS, a genetic algorithm was proposed. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…In order to address the issues of low accuracy and poor interpretability in existing HFMD incidence prediction models, in this paper, we propose an interpretable prediction model, namely, ARIMA–LSTM–XGBoost, which integrates multiple meteorological factors with Autoregressive integrated moving average model (ARIMA), Long short-term memory (LSTM), Extreme gradient boosting (XGBoost), Grey wolf optimizer (GWO), Genetic algorithm (GA) and Shapley additive explanations (SHAP). …”
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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…The Wilcoxon test results indicated that there was no significant difference between ABC_DEE and GABC, but ABC_DEE significantly outperformed the other algorithms. When <italic>D</italic>=20, ABC_DEE was superior to the comparison algorithms on at least 47 functions and inferior on at most 26 functions. …”
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DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification by Musa Adamu Wakili, Harisu Abdullahi Shehu, Mahdi Abdollahi, Badamasi Imam Ya'u, Md Haidar Sharif, Huseyin Kusetogullari

“…DenseNet effectively extracts hierarchical features, while FPA optimizes the selection of the most discriminative features, improving classification accuracy and reducing computational overhead. …”
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Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm by Fang Ye, Fei Che, Lipeng Gao

“…In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. …”
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Self-tuning trajectory tracking control for concrete pouring construction robots based on PID-NFTSMC and CPO algorithm. by Siwen Fan, Wanli Li, Rui Xie

“…Additionally, the study employed the crested porcupine optimizer (CPO) algorithm to automatically optimize PID control gains and NFTSMC sliding surface parameters, ensuring adaptability across varying conditions. …”
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Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah, Seifeddine Bouallegue, Ridha Bouallegue

“…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”
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Optimizing Natural Image Quality Evaluators for Quality Measurement in CT Scan Denoising by Rudy Gunawan, Yvonne Tran, Jinchuan Zheng, Hung Nguyen, Rifai Chai

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Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…The optimized VToMe-BiGRU algorithm combines the Transformer model and the BiGRU network, which effectively captures the critical features in the electric drive system data, thus improving the fault prediction performance. …”
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An experimental optimization environment for developing an intracycle pitch control in cross flow turbines by Stefan Hoerner, Roberto Leidhold, Shokoofeh Abbaszadeh, Karla Ruiz-Hussmann, Timo Bennecke, Zhao Zhao, Paul Joedecke, Christian-Thoralf Weber, Pierre-Luc Delafin, Cyrille Bonamy, Yves Delannoy

“… Cross-flow tidal turbines have not reached the efficiency of horizontal-axis turbines. Among various improvement approaches found in the literature, the intracycle pitch control is one of the most promising ones. …”
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Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals by Tian Han, Bo-Suk Yang, Won-Ho Choi, Jae-Sik Kim

“…GA is used to select the most significant features from the whole feature database and optimize the ANN structure parameter. …”
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K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers by Herayati Herayati, Andronias Siregar, Hariyanto Hariyanto

“…Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality. …”
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What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

“…Many studies have employed field calibration to improve sensor agreement with co-located reference monitors. …”
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Bearing remaining useful life prediction based on optimized VMD and BiLSTM-CBAM. by Wei Liu, Sen Liu

“…To address the issue of low accuracy in existing remaining useful life (RUL) prediction algorithms for rolling bearings, this paper proposes a novel RUL prediction method based on the Beluga Whale Optimization (BWO) algorithm, Variational Mode Decomposition (VMD), an improved Convolutional Block Attention Module (CBAM*), and a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…The empirical insights, drawn from the real-life case study of this research, indicate the challenges and complexities that arise in the path of achieving zero defect product and sustainability improvement. The extended view on effective root causes of product quality and the focus on improving TBL sustainability criteria in this research as well as its analytical approach offer practitioners valuable insights for improving their ZDM approaches in a more comprehensive way. …”
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Time and Covariance Threshold Triggered Optimal Uncooperative Rendezvous Using Angles-Only Navigation by Yue You, Hua Wang, Christophe Paccolat, Volker Gass, Jean-Philippe Thiran, Jiu Ren Li

“…In the context of Yamanaka-Ankersen orbital relative motion equations, the square root unscented Kalman filter (SRUKF) AON algorithm is developed to compute the relative state estimations from a low-volume/mass, power saving, and low-cost optical/infrared camera’s observations. …”
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