Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm. by Jiayuan Wang

“…Secondly, considering the complexity and diversity of wind speed data characteristics, data decomposition technique, autoregressive moving average (ARIMA) model and cuckoo search algorithm are used to achieve data preprocessing, serial data modelling and hybrid prediction. …”
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A sentiment-driven three-stage approach for multi-scale carbon price prediction by Yongliang Liu, Chunling Tang, Aiying Zhou, Kai Yang, Huaiyu Yuan

“…This paper proposes a new hybrid model for carbon trading price forecasting. The model fuses complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) with extreme gradient boosting (XGBoost) and long short-term memory (LSTM) networks, and leverages SnowNLP to derive sentiment scores from news text and the Baidu Index. …”
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Target Detection and Image Enhancement for Underwater Environment: Research on Improving YOLOv7 by Yang Luo, Wen Feng

“…To further enhance the computational efficiency, a deep decomposition feature expression module is designed, which significantly reduces the computational complexity and the number of parameters of the model. …”
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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

“…The results demonstrate that: (1) the TCN-LSTM model achieves higher prediction accuracy compared to single models. (2) FIF is a more effective decomposition method with superior performance compared to EMD-based methods. (3) The proposed model exhibits the highest predictive capability, with MAE values of 0.0964, 0.1403, 1.9476, 2.0848, and 0.5029 for the five carbon markets, significantly outperforming comparison models. (4) The attention mechanism effectively captures the influence of multiple factors on carbon price, particularly within the short-term components.…”
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Gearbox fault diagnosis using data fusion based on self-organizing map neural network by Zhang Qiang, Gu Jieying, Liu Junming, Tian Ying, Zhang Shilei

“…This article aims to provide an efficient fault diagnosis method for gearbox. A self-organizing map–based fault model is developed to provide effective diagnosis of the faults of gearboxes using the gear signals extracted from gearboxes operating with zero and three different types of faults. …”
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Estimation of DOA for Noncircular Signals via Vandermonde Constrained Parallel Factor Analysis by Heyun Lin, Chaowei Yuan, Jianhe Du, Zhongwei Hu

“…Then, taking the Vandermonde structure of the array manifold matrix into account, the extended matrix can be turned into a tensor model which admits the Vandermonde constrained PARAFAC decomposition. …”
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Interval combined prediction of mine tunnel's air volume considering multiple influencing factors. by Zhen Wang, Erkan Topal, Liangshan Shao, Chen Yang

“…Finally, a sensitivity analysis was carried out to analyze the values of the preference coefficients in the model, and the final range of values was given. Experimental analysis using data from a coal mine in Inner Mongolia showed that the method could reduce Combined Weighted Mean Absolute Error(CWMAE) to a maximum of 5.0384, Combined Weighted Root of Mean Squares Error(CWRMSE) to 6.8889, and Combined Weighted Mean Absolute Percentage Error(CWMAPE) to 1.4756, which indicates that the method proposed in this study can effectively improve the prediction accuracy of the mine tunnel air volume.…”
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Global, regional and national burden of traumatic amputations from 1990 to 2021: a systematic analysis of the Global Burden of Disease study 2021 by Baixing Wei, Jie Zhang, Yuanpei Cheng, Han Wu

“…In-depth analyses and projections were performed using Age-Period-Cohort (APC) model analysis, decomposition analysis, and Autoregressive Integrated Moving Average (ARIMA) models.ResultThere was an increase in the number of traumatic amputations globally in 2021 compared to 1990. …”
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Unified Dynamic Dictionary and Projection Optimization With Full-Rank Representation for Hyperspectral Anomaly Detection by Hongran Li, Chao Wei, Yizhou Yang, Zhaoman Zhong, Ming Xu, Dongqing Yuan

“…Traditional reconstruction based methods model the background using a predefined static background dictionary and low-rank representation coefficients. …”
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Research on Health Condition Monitoring for Glass Panel of Hidden Frame Glass Curtain Wall Under Wind Load Using Fuzzy Comprehensive Evaluation by Letian Ding, Wei Cao, Zhiyang Cao, Yifan Wang, Rui Su, Ziqi Chen, Muhammad Maqsood, Niraj Khara, Mu Liming

“…The vibration signals of glass panel under different wind load conditions were processed by using the method of Hilbert vibration decomposition and envelope spectrum analysis, and the peak value and area of envelope spectrum were extracted to judge the vibration amplitude of glass panel, which was used as the evaluation index. …”
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The burden of intracerebral hemorrhage attributable to ambient particulate matter pollution in five Asian countries: a 32-year comparative analysis by Rui Yang, Xingke Wang, Panpan Hao

“…Abstract Objective To assess the impact of ambient particulate matter exposure on the burden of intracerebral hemorrhage (ICH) in the world, China, Indonesia, North Korea, Myanmar and Vietnam from 1990 to 2021 in different population, and to reveal regional heterogeneity and policy effects. Methods Based on the GBD 2021 data, we integrated the Joinpoint, Age-period-cohort model, Decomposition Analysis, Health Inequality Analysis and BAPC model chain achieved a complete cycle analysis including trend mutation detection, analysis of driving factors and long-term prediction. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Subsequently, time-domain, frequency-domain, and time–frequency domain features are extracted from the preprocessed data using FFT and wavelet packet decomposition, followed by feature screening for tool wear mapping via Pearson correlation and XGBoost feature importance analysis as model input. …”
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TOOL WEAR STATE MONITORING BASED ON WAVELET PACKET BP＿ADABOOST ALGORITHM by ZHU Xiang, XIE Feng

“…Aiming at the problems of less tool wear state data,low diagnostic efficiency,high maintenance cost and lack of effective diagnostic methods during CNC machine tool processing,A method of extracting features by wavelet packet analysis and kernel principal component analysis,and using BPAda Boost algorithm to diagnose tool wear state is proposed.The tool vibration signal and the cutting force signal are collected by installing an acceleration sensor on the machined workpiece of the numerical control machine tool and a force gauge on the workbench; Then the wavelet packet decomposition is performed on the signal to pass the signal through the low-pass filter and the high-pass filter of different dimensions,so that the conditional selection can be performed to form the energy value corresponding to the different frequency bands. …”
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Intelligent Fault Severity Detection of Rotating Machines Based on VMD-WVD and Parameter-Optimized DBN by Ning Jia, Yao Cheng, Youyuan Tian, Feiyu Yang

“…An intelligent fault severity detection method based on variational mode decomposition- (VMD-) Wigner-Ville distribution (WVD) and sparrow search algorithm- (SSA-) optimized deep belief network (DBN) is suggested to address the problem that typical fault diagnostic algorithms are inappropriate for extremely comparable vibration signals when the samples are insufficient. …”
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Multimodal medical image fusion combining saliency perception and generative adversarial network by Mohammed Albekairi, Mohamed vall O. Mohamed, Khaled Kaaniche, Ghulam Abbas, Meshari D. Alanazi, Turki M. Alanazi, Ahmed Emara

“…Compared to state-of-the-art methods, the framework achieves an 11.378% improvement in fusion accuracy and a 12.441% enhancement in precision. …”
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Vibration Tendency Prediction Approach for Hydropower Generator Fused with Multiscale Dominant Ingredient Chaotic Analysis, Adaptive Mutation Grey Wolf Optimizer, and KELM by Wenlong Fu, Kai Wang, Jiawen Tan, Kaixuan Shao

“…For this purpose, a novel hybrid approach combined with multiscale dominant ingredient chaotic analysis, kernel extreme learning machine (KELM), and adaptive mutation grey wolf optimizer (AMGWO) is proposed. Among the methods, variational mode decomposition (VMD), phase space reconstruction (PSR), and singular spectrum analysis (SSA) are suitably integrated into the proposed analysis strategy. …”
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Collaborative filtering based on GNN with attribute fusion and broad attention by MingXue Liu, Min Wang, Baolei Li, Qi Zhong

“…In recent years, graph neural networks (GNN) based CF models have effectively addressed the limitations of nonlinearity and higher-order feature interactions in traditional recommendation methods, such as matrix decomposition-based methods and factorization machine approaches, achieving excellent recommendation performance. …”
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Lightweight Brain Tumor Segmentation Through Wavelet-Guided Iterative Axial Factorization Attention by Yueyang Zhong, Shuyi Wang, Yuqing Miao, Tao Zhang, Haoliang Li

“…Conventional deep learning methods, such as convolutional neural networks and transformer-based models, frequently introduce significant computational overhead or fail to effectively represent multi-scale features. …”
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Effect of Polarization on the Correlation and Capacity of Indoor MIMO Channels by Hsun-Chang Lo, Ding-Bing Lin, Teng-Chieh Yang, Hsueh-Jyh Li

“…We also propose an analysis method for polarization channel capacity; this method includes the normalization of the received power and polarization effect for different polarization schemes. …”
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Analysis and Prediction of the Dynamic Antiplane Characteristics of an Elastic Wedge-Shaped Quarter-Space Containing a Circular Hole by Shen Liu, Jie Yang, Yue Liu, Qin Liu

“…The wedge-shaped medium is decomposed into two subregions along the virtual boundary using the virtual region decomposition method. The scattering wave field in subregion I is constructed by the mirror method, and the standing wave field in region II is constructed by the fractional Bessel function. …”
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