Integrating fast iterative filtering and ensemble neural network structure with attention mechanism for carbon price forecasting by Wang Zhong, Wang Yue, Wang Haoran, Tang Nan, Wang Shuyue

“…However, due to the non-linear and non-stationary nature of carbon price, traditional models often struggle to achieve high prediction accuracy. To address this challenge, this study proposes a novel integrated prediction framework designed to enhance forecast accuracy. …”
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Rapid Identification and Quality Evaluation of Medicinal Centipedes in China Using Near-Infrared Spectroscopy Integrated with Support Vector Machine Algorithm by Sihe Kang, Haiying Deng, Long Chen, Xiaoxuan Zeng, Yimei Liu, Keli Chen

“…When the model was validated with the calibration and prediction sets, the prediction accuracy was 100% and 81.82%, respectively; it can meet the requirement for rapid and preliminary identification. …”
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An Improved MG Model for Turbulent Mixing Parameterization in the Northwestern South China Sea by Minghao Hu, Lingling Xie, Mingming Li, Quanan Zheng, Feihong Zeng, Xiaotong Chen

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Forecasting Chinese Wind Power Installed Capacity Using a Novel Grey Model with Parameters Combination Optimization by Xiaoshuang Luo, Bo Zeng, Hui Li, Wenhao Zhou

“…To this end, a novel grey prediction model with parameters combination optimization is proposed in this paper. …”
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Anticipating Stock Market of the Renowned Companies: A Knowledge Graph Approach by Yang Liu, Qingguo Zeng, Joaquín Ordieres Meré, Huanrui Yang

“…Accordingly, research on stock prediction is becoming a popular direction in academia and industry. …”
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Application of Improved Deep Learning Method in Intelligent Power System by HuiJie Liu, Yang Liu, ChengWen Xu

“…The method uses the convolutional neural network to establish the energy prediction calculation model, uses CNN adaptive data features to mine characteristics, quantifies power uncertainty, uses drop regularization to optimize the deep network structure, uses the deep forest to learn the extracted data features, and builds a prediction model, in order to achieve accurate prediction of power load and solve the problem that the accuracy of existing forecasting methods decreases due to random fluctuations of power. …”
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Forecasting the Number of the Wounded after an Earthquake Disaster Based on the Continuous Interval Grey Discrete Verhulst Model by Jun Zhang, Tongyuan Wang, Jianpeng Chang, Yan Gou

“…Earthquake disaster causes serious casualties, so the prediction of casualties is conducive to the reasonable and efficient allocation of emergency relief materials, which plays a significant role in emergency rescue. …”
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Analysis and Forecast of a Tornadic Thunderstorm Using Multiple Doppler Radar Data, 3DVAR, and ARPS Model by Edward Natenberg, Jidong Gao, Ming Xue, Frederick H. Carr

“…A three-dimensional variational (3DVAR) assimilation technique developed for a convective-scale NWP model—advanced regional prediction system (ARPS)—is used to analyze the 8 May 2003, Moore/Midwest City, Oklahoma tornadic supercell thunderstorm. …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…Predicting the time series energy consumption data of manufacturing processes can optimize energy management efficiency and reduce maintenance costs for enterprises. …”
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Northern Hemisphere Climatology and Interannual Variability of Storm Tracks in NCEP’s CFS Model by Timothy Paul Eichler, Francisco Alvarez, Jon Gottschalck

“…We generate storm tracks from the National Center for Environmental Prediction (NCEP) Climate Forecast System (CFS) model for the northern hemisphere (NH) and compare them to storm tracks generated from NCEP’s reanalysis I data, the European Centre for Medium Range Prediction (ECMWF) ERA40 data, and CFS reanalysis data. …”
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An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network by Wei He

“…Inventory control is a key factor for reducing supply chain cost and increasing customer satisfaction. However, prediction of inventory level is a challenging task for managers. …”
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A Memory-Based Hysteresis Model in Piezoelectric Actuators by Guilin Zhang, Chengjin Zhang, Jason Gu

“…It shows that the proposed model prediction method is better than other two methods.…”
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Deep Neural Network Model Forecasting for Financial and Economic Market by Fan Chen

“…Second, the model also designs an optimization function based on the stability constraints of the prediction sequence, so that the model has better robustness. …”
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The Impact of Assimilating Atmospheric Infrared Sounder Observation on the Forecast of Typhoon Tracks by Chien-Ben Chou, Huei-Ping Huang

“…The parameter-sweeping framework is potentially useful for improving operational typhoon prediction.…”
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Short‐term load forecasting at electric vehicle charging sites using a multivariate multi‐step long short‐term memory: A case study from Finland by Tim Unterluggauer, Kalle Rauma, Pertti Järventausta, Christian Rehtanz

“…Abstract This study assesses the performance of a multivariate multi‐step charging load prediction approach based on the long short‐term memory (LSTM) and commercial charging data. …”
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SOCIAL AND PEDAGOGICAL FORECASTING IN THE PROCESS OF CHILDREN’S SOCIALIZATION by Antonina L. Leutina

“…The aim of the present research is to provide an analysis of prevalence of predictive thinking in modern theoretic pedagogy as well as elaboration of methodological schemes of implementation of social and pedagogic prediction in pedagogic activity, the primary function of which is successful socialization of children. …”
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Research on Small Sample Nonlinear Cointegration Test and Modeling Based on the LS-SVM Optimized by PSO by Jungang Du

“…And the NECM has better performance. The prediction effect can effectively predict small sample nonlinear systems. …”
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Field Measurement and Study on Overburden Fracture and Surface Subsidence Law of Solid Filling Mining under Buildings by Zhiyong Fu, Lujie Zhou, Kai Yu, Wanzhen Li, Hu Chen

“…In order to predict the surface subsidence scientifically in solid filling mining, it is necessary to establish a complete subsidence prediction model and parameter system according to the evolution law of overburden structure and strata movement characteristics. …”
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Economic Development Forecast of China’s General Aviation Industry by Hongqing Liao, Zhigeng Fang, Chuanhui Wang, Xiaqing Liu

“…Based on the dynamic deduction of the functional analysis factor of system impact evolution, the flight time of general aviation production operation is selected to predict the development trend of the system. Based on the current period information of the general aviation industry, the grey Bayesian network inference prediction model is used to predict the current and future trends, so as to predict the economic development trend of the general aviation industry in China. …”
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A recommender system with multi-objective hybrid Harris Hawk optimization for feature selection and disease diagnosis by Madhusree Kuanr, Puspanjali Mohapatra

“…This study proposes a health recommender system to analyze health risk and disease prediction by identifying the most responsible disease-causing factors using a hybrid Genetic–Harris Hawk optimization multi-objective feature selection approach. …”
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