AdaGram in Python: An AI Framework for Multi-Sense Embedding in Text and Scientific Formulas by Arun Josephraj Arokiaraj, Samah Ibrahim, André Then, Bashar Ibrahim, Stephan Peter

“…The Adaptive Skip-gram (AdaGram) algorithm extends traditional word embeddings by learning multiple vector representations per word, enabling the capture of contextual meanings and polysemy. …”
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A Computationally Efficient Model Predictive Control Energy Management Strategy for Hybrid Vehicles Considering Driving Style by Yalian Yang, Yuqi Chen, Changdong Liu

“…The driving-style adaptive Pontryagin’s minimum principle for model predictive control (DSA-PMP-MPC) algorithm was designed as a real-time energy management strategy for Hybrid Electric Vehicles (HEVs). …”
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PCA-GWO-KELM Optimization Gait Recognition Indoor Fusion Localization Method by Xiaoyu Ji, Xiaoyue Xu, Suqing Yan, Jianming Xiao, Qiang Fu, Kamarul Hawari Bin Ghazali

“…Then, constructing PCA-GWO-KELM optimization gait recognition algorithms to obtain important features, the model parameters of the kernel-limit learning machine are optimized by the gray wolf optimization algorithm. …”
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An Energy-Efficient Battery Monitoring and Logging System for Agricultural Robotics with CAN Bus Integration by Soosaar Guido, Lillerand Tormi

“…A key innovation is its adaptive data acquisition algorithm, which adjusts polling frequency based on battery activity and temperature thresholds, significantly reducing power consumption without compromising responsiveness. …”
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Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion by Ying Chen, Yuanning Liu, Xiaodong Zhu, Huiling Chen, Fei He, Yutong Pang

“…The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples’ own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.…”
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Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction by Nan Zhou, Jin Hong, Bo Song, Shichao Wu, Yichen Wei, Tao Wang

“…The researchers used a genetic algorithm (GA), interval combination optimization (ICO), and competitive adaptive reweighted sampling (CARS) to filter feature variables from full-band spectral data. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel, Hetal Bhavsar

“…In our research, we propose a novel approach to address this challenge specifically tailored for Support Vector Machines (SVM), a well-established family of learning algorithms. …”
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Hyperspectral Estimation of Tea Leaf Chlorophyll Content Based on Stacking Models by Jinfeng Guo, Dong Cui, Jinxing Guo, Umut Hasan, Fengqi Lv, Zixing Li

“…In this study, derivative transformations were first applied to preprocess the tea hyperspectral data, followed by the use of the Stable Competitive Adaptive Reweighted Sampling (SCARS) algorithm for feature variable selection. …”
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Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology by Yurong Zhang, Wenliang Wu, Xianqing Zhou, Jun-Hu Cheng

“…The feature variables were extracted by a variable iterative space shrinkage approach (VISSA), competitive adaptive reweighted sampling (CARS), and a successive projections algorithm (SPA). …”
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State of Health Estimation for Lithium-Ion Batteries Using an Explainable XGBoost Model with Parameter Optimization by Zhenghao Xiao, Bo Jiang, Jiangong Zhu, Xuezhe Wei, Haifeng Dai

“…Then, a SOH estimation method based on the XGBoost algorithm is established, and the model’s hyper-parameters are tuned using the Bayesian optimization algorithm (BOA) to enhance the adaptiveness of the proposed estimation model. …”
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ZNN-Based Gait Optimization for Humanoid Robots with ALIP and Inequality Constraints by Yuanji Liu, Hao Jiang, Haiming Mou, Qingdu Li, Jianwei Zhang

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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…The model was further compared with the PSO algorithm, demonstrating its superiority with a 7.5% reduction in total maintenance cost and a 6.3% decrease in total downtime. …”
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A Genetic QoS-Aware Routing Protocol for the Smart Electricity Networks by Agustin Zaballos, David Vernet, Josep M. Selga

“…The resulting routing protocol, named genetic algorithm with TBR algorithm for Smart Grids (GATAS), is an adapted intelligent evolution of the TBR. …”
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Development of High Accuracy Classifier for the Speaker Recognition System by Raghad Tariq Al-Hassani, Dogu Cagdas Atilla, Çağatay Aydin

“…In order to enhance noise immunity, we proposed a single hidden layer feed-forward neural network (FFNN) tuned by an optimized particle swarm optimization (OPSO) algorithm. The proposed model is tested using 10-fold cross-validation over different levels of Adaptive White Gaussian Noise (AWGN) (0-50 dB). …”
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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…MethodsTo address these issues, Multi-Way Improved Whale Optimization Algorithm (MWIWOA) was proposed to optimize the SVM-based prediction model for the internal corrosion rate of long-distance submarine pipelines. …”
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Dual-coding Contrastive Learning Based on the ConvNeXt and ViT Models for Morphological Classification of Galaxies in COSMOS-Web by Shiwei Zhu, Guanwen Fang, Chichun Zhou, Jie Song, Zesen Lin, Yao Dai, Xu Kong

“…In our previous works, we proposed a machine learning framework named USmorph for efficiently classifying galaxy morphology. …”
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Pesticide Residue Detection in Broccoli Based on Hyperspectral Technology and Convolutional Neural Network by Dan WANG, Yuqing LUAN, Zuojun TAN, Wei WEI

“…Using broccoli as a sample, this article used hyperspectral technology combined with machine learning algorithms and deep learning algorithms to provide a simple, fast, low-cost, and non-destructive method for detecting pesticide residues in broccoli. …”
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A novel method based on the SCNGO‐ICEEMDAN and MCNN‐BiLSTM model for fault diagnosis of motor bearings for more electric aircraft by Dongsheng Yuan, Feng Liu, Zhonggang Yin, Yanqing Zhang, Yanping Zhang, Peien Luo

“…In this article, a Northern Goshawk algorithm using a fusion subtraction optimiser and Cauchy strategy (SCNGO) is proposed to optimise the number of white noise additions and amplitude weights in the improved full set empirical mode decomposition method based on adaptive noise (ICEEMDAN). …”
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Virtual Modelling Framework-Based Inverse Study for the Mechanical Metamaterials with Material Nonlinearity by Yuhang Tian, Yuan Feng, Wei Gao

“…By employing an extended support vector regression (X-SVR), a powerful machine learning algorithm model, this study explores the uncertainty and sensitivity analysis and inverse study of re-entrant honeycombs under quasi-static compressive loads. …”
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