Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…By designing a texture-aware data prior algorithm, a high-quality training dataset with geological rationality is generated. …”
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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

“…The k-fold cross-validation technique is utilized in every algorithm to mitigate the overfitting problem during the training of models. …”
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18F-FDG dose reduction using deep learning-based PET reconstruction by Ryuji Akita, Komei Takauchi, Mana Ishibashi, Shota Kondo, Shogo Ono, Kazushi Yokomachi, Yusuke Ochi, Masao Kiguchi, Hidenori Mitani, Yuko Nakamura, Kazuo Awai

“…Compared to the recommended dose in the European Association of Nuclear Medicine (EANM) guidelines for 90 s per bed position (4.7 MBq/kg), this represents a dose reduction of 36%. Further optimization of DLR algorithms is required to maintain comparable diagnostic accuracy in patients weighing 75 kg or more.…”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…Empirical evidence demonstrates that this framework not only accurately captures the diverse characteristics of different data components but also significantly outperforms traditional benchmark models in predictive accuracy. By optimizing the GRU model with the grey wolf optimizer (GWO) algorithm, the framework enhances both prediction stability and adaptability, while the nonlinear integration approach effectively mitigates error accumulation. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Compared to RNNs and their variants, the LTCA–TCN algorithm yields superior prediction results while maintaining a simpler structure and requiring fewer computational resources. …”
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Low-carbon economic dispatch based on improved ISODATA scenario reduction for wind power in IES by Yuangen HUANG, Xingyu LIU, Tianran LI, Zhenya JI, Wei XU

“…A low-carbon, economic dispatch method for IES using an enhanced wind power scenario reduction algorithm is introduced in this paper. It employs an improved iterative self-organizing data analysis technique algorithm (ISODATA) for clustering historical wind power scenarios, addressing the limitations of traditional clustering algorithms in determining cluster centers and analyzing inherent data features. …”
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Calculation method of line loss rate of substation areas considering tidal current variation with photovoltaic power generation access by Shengbo Sun, Chao Cheng, Shujun Ji, Wei Cui, Wei Ge, Shifang Hao

“…The proposed method employs an improved K-medoids clustering algorithm for substation area classification, optimized by an enhanced Cuckoo algorithm to minimize classification errors. …”
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Machine Learning to Assess Relatedness: The Advantage of Using Firm-Level Data by Giambattista Albora, Andrea Zaccaria

“…We also discuss the effect of using parameter optimization and community detection algorithms to identify clusters of related companies and products, finding that a partition into a higher number of blocks decreases the computational time while maintaining a prediction performance well above the network-based benchmarks.…”
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Consider the master-slave game model of integrated energy system with step carbon trading and demand response by Yi Zhang, Zhezhou Zhang

“…In the context of deepening energy coupling and the high penetration of renewable energy, this paper proposes a master-slave game model incorporating comprehensive demand response and a stepped carbon trading mechanism. The goal is to optimize scheduling of demand response resources and fully leverage the flexibility of energy use within an integrated energy system while addressing conflicts of interest among multiple stakeholders, thereby enhancing trading revenue in Energy Markets while considering lower carbon emissions. …”
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A Robust Tomato Counting Framework for Greenhouse Inspection Robots Using YOLOv8 and Inter-Frame Prediction by Wanli Zheng, Guanglin Dai, Miao Hu, Pengbo Wang

“…Accurate tomato yield estimation and ripeness monitoring are critical for optimizing greenhouse management. While manual counting remains labor-intensive and error-prone, this study introduces a novel vision-based framework for automated tomato counting in standardized greenhouse environments. …”
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Big Data-Driven 3D Visualization Analysis System for Promoting Regional-Scale Digital Geological Exploration by Yiping Tian, Jiongqi Wu, Genshen Chen, Gang Liu, Xialin Zhang

“…Experimental validation shows the improved CMMN algorithm reduces cloud task completion time by 2.37% while increasing resource utilization by 0.652% compared with conventional methods. …”
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Rail surface identification and adhesion control based on dynamic adhesion characteristics by Wen Liu, Hongfeng Qi, Jingchun Huang, Yiyuan Chen, Sheng He, Haoxiang Feng

“…Therefore, to achieve stable tracking of the optimal adhesion state while adopting the feedback dynamic adhesion characteristic model, this study utilizes a machine learning algorithm to perform classification training on discrete points of the simulated adhesion characteristic model under various rail conditions. …”
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Blind source separation and unmanned aerial vehicle classification using CNN with hybrid cross-channel and spatial attention module by Jiangong Ni, Zhigang Zhou

“…The experimental results indicate that the mean absolute error (MAE) of the original algorithm was 14.58%, while the MAE of the improved FastICA decreased by 10.31%, dropping to 4.27%. …”
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Fibre-orientation-driven defect probability mapping for machining-induced delamination and burr minimisation in carbon fibre-reinforced polymer (CFRP) composites by Norbert Geier

“…Then, recursive convolution yielded a matrix whose minima identified the optimal hole position. First, edge trimming experiments were conducted to determine the arguments (critical fibre cutting angle and its range) of the developed algorithm. …”
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Energy and Reserve Scheduling of Distribution Network in Presence of Electric Vehicle Aggregators: A Decentralized Approach by Atena Tazikeh Lemeski, Reza Ebrahimi, Alireza Zakariazadeh, Keyvan Firuzi

“…The results indicate that ignoring network conditions and constraints leads to impractical decisions whereas consideration of DSO requirements by the distributed algorithm will deliver a profitable schedule for AGGs while protecting their privacy and fulfilling DSO’s economical and technical objectives.…”
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The Path Planning Problem of Robotic Delivery in Multi-Floor Hotel Environments by Linghui Han, Junzhe Ding, Songtao Liu, Meng Meng

“…To solve this NP-hard problem, an Adaptive Large Neighborhood Search (ALNS) algorithm is proposed. The effectiveness of the algorithm is validated through comparative experiments with Gurobi, demonstrating its ability to handle complex three-dimensional delivery scenarios. …”
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Incremental Reinforcement Learning for Portfolio Optimisation by Refiloe Shabe, Andries Engelbrecht, Kian Anderson

“…To address this, an incremental recurrent PPO is developed, leveraging incremental learning to adapt to concept drift triggered by the pandemic. This enhanced algorithm not only learns from ongoing market data but also consistently identifies optimal portfolios despite significant market volatility, offering a robust tool for real-time financial decision-making.…”
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Research on Status Assessment and Operation and Maintenance of Electric Vehicle DC Charging Stations Based on XGboost by Hualiang Fang, Jiaqi Liao, Shuo Huang, Maojie Zhang

“…To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. …”
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An Analog Sensor Signal Processing Method Susceptible to Anthropogenic Noise Based on Improved Adaptive Singular Spectrum Analysis by Zhengyang Gao, Shuangchao Ge, Jie Li, Wentao Huang, Kaiqiang Feng, Chenming Zhang, Chunxing Zhang, Jiaxin Sun

“…The singular spectrum decomposition (SSA) algorithm, while widely used, faces challenges such as the difficulty of determining the number of decomposition layers, requiring iterative adjustments that reduce precision and increase processing time. …”
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Komparasi Kinerja Algoritma Blocking Pada Proses Indexing Untuk Deteksi Duplikasi by M. Miftakul Amin, Yevi Dwitayanti

“…While the Soundex and Cosine Similarity algorithms provide the most optimal results, which are 8 candidate record pairs. …”
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