Hybrid Techniques for Short Term Load Forecasting by Saroj Panda, Papia Ray, Surender Salkuti

“…The neural model consists of weights whose optimal values are determined using various optimization approaches. …”
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Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens by Vittorio Erba, Emanuele Troiani, Luca Biggio, Antoine Maillard, Lenka Zdeborová

“…We note that modern architectures naturally subsume the BSR model due to the skip connections. Building on recent methodological progress, we compute the Bayes-optimal generalization error for the model in the limit of long sequences of high-dimensional tokens and provide a message-passing algorithm that matches this performance. …”
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Hybrid modeling of adsorption process using mass transfer and machine learning techniques for concentration prediction by Jing Lv, Lei Wang

“…To improve model performance, hyperparameters were optimized using the bio-inspired Barnacles Mating Optimizer (BMO) algorithm. …”
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Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

“…In response to the rapid and accurate distribution network security situation awareness requirements, this paper proposes a distribution network security situation awareness method based the distribution network topology layered model. First, a hierarchical model of the distribution network topology under the premise of optimizing the location of the synchronous phasor measuring device is constructed. …”
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Detection of kidney bean leaf spot disease based on a hybrid deep learning model by Yiwei Wang, Qianyu Wang, Yue Su, Binghan Jing, Meichen Feng

“…Based on this dataset, a novel hybrid deep learning model framework is proposed, which integrates deep learning models (EfficientNet-B7, MobileNetV3, ResNet50, and VGG16) for feature extraction with machine learning algorithms (Logistic Regression, Random Forest, AdaBoost, and Stochastic Gradient Boosting) for classification. …”
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Accurate irrigation decision-making of winter wheat at the filling stage based on UAV hyperspectral inversion of leaf water content by Xuguang Sun, Baoyuan Zhang, Menglei Dai, Cuijiao Jing, Kai Ma, Boyi Tang, Kejiang Li, Hongkai Dang, Limin Gu, Wenchao Zhen, Xiaohe Gu

“…The SPA algorithm also improved the inversion efficiency of LWC. …”
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Mission Sequence Model and Deep Reinforcement Learning-Based Replanning Method for Multi-Satellite Observation by Peiyan Li, Peixing Cui, Huiquan Wang

“…Both phases are formulated as Markov Decision Processes (MDPs) and optimized using the PPO algorithm. Extensive simulations demonstrate that our method significantly outperforms state-of-the-art approaches, achieving a 15.27% higher request insertion revenue rate and a 3.05% improvement in overall mission revenue rate, while maintaining a 1.17% lower modification rate and achieving faster computational speeds. …”
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A novel hybrid model based on MPA-VMD, QRMGM and KDE for carbon price prediction by Dabin Zhang, Yufeng Ye, Yongmei Fang, Jing Zhou

“…The study employed a lightweight hybrid model to forecast carbon prices. Firstly, Marine Predators Algorithm Optimized Variational Mode Decomposition (MPA-VMD) was applied to decompose the original carbon price time series to obtain optimal parameters and subsequences. …”
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A Planar Feature-Preserving Texture Defragmentation Method for 3D Urban Building Models by Beining Liu, Wenxuan Liu, Zhen Lei, Fan Zhang, Xianfeng Huang, Tarek M. Awwad

“…In this paper, we propose a planar feature-preserving texture defragmentation method designed specifically for urban building models. Our approach leverages the multi-planar topology of buildings to optimize texture merging and reduce fragmentation. …”
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Dark Side of the Web: Dark Web Classification Based on TextCNN and Topic Modeling Weight by Gun-Yoon Shin, Younghoan Jang, Dong-Wook Kim, Sungjin Park, A-Ran Park, Younghwan Kim, Myung-Mook Han

“…For validation, we employed two datasets and compared the performance of the model with other text classification algorithms, where the proposed model demonstrated superior effectiveness in Dark Web classification.…”
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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…This paper presents an advanced hybrid approach that utilizes the Quantum Chimp Optimization Algorithm (QCOA) integrated with SqueezeNet to enhance the accuracy and efficiency of DR classification significantly. …”
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Spatiotemporal Analysis of Eco-Geological Environment Using the RAGA-PP Model in Zigui County, China by Xueling Wu, Jiaxin Lu, Chaojie Lv, Liuting Qin, Rongrui Liu, Yanjuan Zheng

“…It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. …”
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Prediction of China’s Sulfur Dioxide Emissions by Discrete Grey Model with Fractional Order Generation Operators by Wei Meng, Daoli Yang, Hui Huang

“…Based on fractional order operators, a discrete grey model with fractional operators is developed, which also makes use of genetic algorithms to optimize the modeling parameter r. …”
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Ship-DETR: A Transformer-Based Model for EfficientShip Detection in Complex Maritime Environments by Yi Wang, Xiang Li

“…First, we introduce the high-low frequency (HiLo) attention into the intra-scale feature interaction module to enhance the extraction of both high- and low-frequency features, reduce computational complexity, and improve detection performance. To strengthen the model&#x2019;s multi-scale fusion capability for ship features of different scales, we incorporate the bidirectional feature pyramid network (BiFPN) to optimize cross-scale feature fusion and add the <inline-formula> <tex-math notation="LaTeX">$S_{2}$ </tex-math></inline-formula> features to further enhance the representation of small-scale ship features. …”
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High-Frequency Cryptocurrency Price Forecasting Using Machine Learning Models: A Comparative Study by Fátima Rodrigues, Miguel Machado

“…We compare various machine learning models, including recurrent neural networks (RNNs), time series analysis (ARIMA), and conventional regression algorithms, using minute-step Bitcoin price data over a 30-day period to predict prices 60 min ahead. …”
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Development of a risk prediction model for secondary infection in severe/critical COVID-19 patients by Yinmei Zhang, Mingmei Lin, Zhenchao Wu, Zhongyu Han, Liyan Cui, Jiajia Zheng

“…The optimal model selected was further assessed, with model interpretability provided using SHapley Additive exPlanations (SHAP). …”
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Quality of life identification by unsupervised cluster analysis: A new approach to modelling the burden of endometriosis. by Alexandre Vallée, Maxence Arutkin, Pierre-François Ceccaldi, Jean-Marc Ayoubi

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A target detection model HR-YOLO for advanced driver assistance systems in foggy conditions by Yao Zhang, Na Jia

“…Abstract To improve the accuracy and real-time performance of detection algorithms in Advanced Driver Assistance Systems (ADAS) under foggy conditions, this paper introduces HR-YOLO, an improved YOLO-based model specifically designed for vehicle and pedestrian detection. …”
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Evaluation of Machine Learning Models for Estimating Grassland Pasture Yield Using Landsat-8 Imagery by Linming Huang, Fen Zhao, Guozheng Hu, Hasbagan Ganjurjav, Rihan Wu, Qingzhu Gao

“…The findings also highlighted the importance of predictor selection in optimizing model performance, except for the reflectance and vegetation indices characterizing vegetation canopy information, the inclusion of soil moisture information could appropriately improve the accuracy of model predictions, especially for grasslands with relatively low vegetation cover.…”
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Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System by Gopisetti Manikanta, Ashish Mani, Hemender Pal Singh, Devendra Kumar Chaturvedi

“…In order to solve this critical combinatorial optimization problem with voltage dependent load model, which requires an extensive search, Adaptive Quantum inspired Evolutionary Algorithm (AQiEA) is used. …”
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