Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory. by Qi Dai, Xiao-Yan Liu, Fang-Yi Sun, Fang-Rong Ren

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A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort study by Xingjian Xiao, Xiaohan Yi, Zumin Shi, Zongyuan Ge, Hualing Song, Hailei Zhao, Tiantian Liang, Xinming Yang, Suxian Liu, Bo Sun, Xianglong Xu

“…We employed nine machine learning algorithms to construct predictive models for gastric ulcers over the next seven years (2011–2018, with 1482 samples) and the next three years (2014–2018, with 2659 samples). …”
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Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and meta-analysis by Jimmy Londono, Shohreh Ghasemi, Altaf Hussain Shah, Amir Fahimipour, Niloofar Ghadimi, Sara Hashemi, Zohaib Khurshid, Mahmood Dashti

“…This meta-analysis included 21 of 577 articles initially collected on the accuracy of ML algorithms for detecting and predicting anatomical landmarks. …”
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Neoantigen vaccines: advancing personalized cancer immunotherapy by Alaa A. A. Aljabali, Yassmen Hamzat, Alaa Alqudah, Lorca Alzoubi

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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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One-point Method for Speed Strategy Optimization Based on Slope Simplification and Speed Limit Prediction by XING Jian, HAN Bing

Subjects: “…speed limit prediction…”
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Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. …”
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Penaeus vannamei aquaculture water quality prediction based on the improved back propagation neural network by DING Jinting, ZANG Zelin, HUANG Min

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Integrating Artificial Intelligence in dermatology: progress, challenges and perspectives by Ionela Manole, George-Sorin Tiplica

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GRU-LSTM model based on the SSA for short-term traffic flow prediction by Changxi Ma, Xiaoyu Huang, Yongpeng Zhao, Tao Wang, Bo Du

Subjects: “…traffic flow prediction…”
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Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and Genetic Algorithm (GA) by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Before training, 32 different ANN configurations were evaluated by varying learning algorithms, adaptation functions, and transfer functions. …”
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A Novel Grey Prediction Model: A Hybrid Approach Based on Extension of the Fractional Order Discrete Grey Power Model with the Polynomial-Driven and PSO-GWO Algorithm by Baohua Yang, Xiangyu Zeng, Jinshuai Zhao

“…Background: This study addresses the challenge of predicting data sequences characterized by a mix of partial linearity and partial nonlinearity. …”
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Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer by Kaimin Hu, Yinan Wu, Yajing Huang, Meiqi Zhou, Yanyan Wang, Xingru Huang

“…Our classifier achieved a predicting accuracy of 81.25%, and 88.7% slides labeled as endocrine resistant were predicted as the mesenchymal-phenotype, while 75.6% slides labeled as sensitive were predicted as the epithelial-phenotype. …”
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Investigation of an Optimized Linear Regression Model with Nonlinear Error Compensation for Tool Wear Prediction by Lihua Shen, Baorui Du, He Fan, Hailong Yang

Subjects: “…tool wear prediction…”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

Subjects: “…deformation prediction model…”
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Artificial intelligence-based forecasting models for integrated energy system management planning: An exploration of the prospects for South Africa by Senthil Krishnamurthy, Oludamilare Bode Adewuyi, Emmanuel Luwaca, Mukovhe Ratshitanga, Prathaban Moodley

Subjects: “…Artificial intelligence-based predictive analytics…”
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Algorithmic Techniques for GPU Scheduling: A Comprehensive Survey by Robert Chab, Fei Li, Sanjeev Setia

“…In this survey, we provide a comprehensive classification of GPU task scheduling approaches, categorized by their underlying algorithmic techniques and evaluation metrics. We examine traditional methods—including greedy algorithms, dynamic programming, and mathematical programming—alongside advanced machine learning techniques integrated into scheduling policies. …”
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Decision Tree Methodology (C4.5) for Predicting Students' Reading Interest in the Library SMK Negeri 1 Kota Cirebon by Muhammad Erwanto, Kosim Kosim, Nur Bambang Riyanto, Sukmo Banyu Jogo

“…This study uses data mining techniques with the C4.5 algorithm to predict student reading interest. This research produces rules to help SMK N 1 Cirebon City predict student reading interest in the school library. …”
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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

“…In order to more accurately estimate the SOC, this paper proposes a prediction method that combines an immune genetic algorithm, gated recurrent unit, and multi-head attention mechanism (MHA), using battery experimental data from the University of Maryland as the dataset. …”
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Enhancing Agricultural Futures Return Prediction: Insights from Rolling VMD, Economic Factors, and Mixed Ensembles by Yiling Ye, Xiaowen Zhuang, Cai Yi, Dinggao Liu, Zhenpeng Tang

Subjects: “…agricultural futures return prediction…”
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