Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…Compared to the conventional LSTM neural network model, the average absolute errors during the early and later stages are reduced by 1.290 m3/d and 0.213 × 104 m3/d, respectively. …”
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A Comparison of Methods for Determining the Number of Factors to Retain in Exploratory Factor Analysis for Categorical Indicator Variables by Holmes Finch

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Evaluation of a fully automated 2-dimensional imaging system for real-time cattle lameness detection using machine learning by N. Siachos, B.E. Griffiths, J.P. Wilson, C. Bedford, A. Anagnostopoulos, J.M. Neary, R.F. Smith, G. Oikonomou

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A Centralized–Distributed Joint Routing Algorithm for LEO Satellite Constellations Based on Multi-Agent Reinforcement Learning by Licheng Xia, Baojun Lin, Shuai Zhao, Yanchun Zhao

“…Compared to traditional centralized algorithms, MARL-JR achieves faster link-state awareness and adaptation; compared to distributed algorithms, it delivers superior initial performance due to optimized pre-training. Experimental results demonstrate that MARL-JR outperforms both Q-Routing (QR) and DR-BM algorithms in average delay, packet loss rate, and load-balancing efficiency.…”
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A Framework for Risk Evolution Path Forecasting Model of Maritime Traffic Accidents Based on Link Prediction by Shaoyong Liu, Jian Deng, Cheng Xie

“…The performance of these indices was compared, and the optimal indicator was selected. This indicator was then integrated into the risk evolution network model to assess the interdependence between risk factors and accident types, ultimately identifying the most probable evolution paths from various risk factors to specific accident outcomes. …”
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Measurement of intelligent computing via Levenberg Marquardt algorithm (LMA) for accurate prediction of fluid forces in a transient non-Newtonian thermal flow by Atif Asghar, Rashid Mahmood, Afraz Hussain Majeed, Ahmed S. Hendy, Mohamed R. Ali

“…To get around these issues, CFD simulations have been joined with Artificial Neural Networks (ANN). An optimally configured artificial neural network (ANN) is given the training and validation data sets produced by computational fluid dynamics (CFD). …”
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A Multimodal Machine Learning Model in Pneumonia Patients Hospital Length of Stay Prediction by Anna Annunziata, Salvatore Cappabianca, Salvatore Capuozzo, Nicola Coppola, Camilla Di Somma, Ludovico Docimo, Giuseppe Fiorentino, Michela Gravina, Lidia Marassi, Stefano Marrone, Domenico Parmeggiani, Giorgio Emanuele Polistina, Alfonso Reginelli, Caterina Sagnelli, Carlo Sansone

“…Specifically, our approach uses the following: (i) feature extraction from chest CT scans via a convolutional neural network (CNN), (ii) their integration with clinically relevant tabular data from patient exams, refined through a feature selection system to retain only significant predictors. …”
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Realization of Integrated Regional Ecological Management Based on Ecosystem Service Supply and Demand Flow Networks: An Example from a Dominant Mineral Resources Development Area by Sheng Xiao, Yanling Zhao, Hui Li, Hairong Deng, Hao Xu, Yimin Xing, Dan Li

“…This study developed a framework that links ecosystem service flows (ESFs) and ecological security patterns (ESP) based on multi-source ecological monitoring data, constructed an ES supply-demand flow network through the flow properties, and determined the sequence and optimization strategies for mine rehabilitation to achieve integrated regional management. …”
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Evaluation and Optimization of Traditional Mountain Village Spatial Environment Performance Using Genetic and XGBoost Algorithms in the Early Design Stage—A Case Study in the Cold... by Zhixin Xu, Xiaoming Li, Bo Sun, Yueming Wen, Peipei Tang

“…It then employed the Wallacei_X plugin, which uses the NSGA-II algorithm for multi-objective genetic optimization (MOGO) to optimize five energy consumption and comfort objectives. …”
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Characteristics and favorable area optimization of ultra-deep high-pressure basement reservoirs: A case study of Kun 2 block in Kunteyi gas reservoir, Qaidam Basin by CAO Hui, ZHANG Guoqing, XU Li, LI Zhexiang, WANG Haicheng, ZHAO Changyang, FEI Ying

“…The fractures exhibited a network-like development and were distributed in NE-SW trending bands in the plane view. …”
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Capacity and Coverage Dimensioning for 5G Standalone Mixed-Cell Architecture: An Impact of Using Existing 4G Infrastructure by Naba Raj Khatiwoda, Babu Ram Dawadi, Sashidhar Ram Joshi

“…The comparative analysis of metaheuristic algorithms shows that the proposed network is efficient in providing an average data rate of 50 Mbps, can meet the coverage requirements of at least 98%, and meets quality-of-service requirements. …”
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Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

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Research on Small-Target Detection of Flax Pests and Diseases in Natural Environment by Integrating Similarity-Aware Activation Module and Bidirectional Feature Pyramid Network Mod... by Manxi Zhong, Yue Li, Yuhong Gao

“…Secondly, in terms of model architecture, a Bidirectional Feature Pyramid Network (BiFPN) module is introduced to replace the original feature extraction network. …”
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Emergency Resource Dispatch Scheme for Ice Disasters Based on Pre-Disaster Prediction and Dynamic Scheduling by Runyi Pi, Yuxuan Liu, Nuoxi Huang, Jianyu Lian, Xin Chen, Chao Yang

“…First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing of resource scheduling and reducing scheduling costs. …”
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Framework for extracting multi-objective operation rules for cascade reservoirs based on causal features and physical mechanisms by Donglin Gu, Baowei Yan, Jianbo Chang, Yixuan Zou, Dongxu Yang, Mingbo Sun, Xiaoyu Diao

“…Based on this framework, a Bidirectional Long Short-Term Memory network enhanced with Multi-Head Self-Attention Mechanism and Bayesian Optimization (BO-MHSAM-BiLSTM) is developed for extracting operation rules. …”
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Psychological and pharmacological interventions for posttraumatic stress disorder and comorbid mental health problems following complex traumatic events: Systematic review and comp... by Peter A Coventry, Nick Meader, Hollie Melton, Melanie Temple, Holly Dale, Kath Wright, Marylène Cloitre, Thanos Karatzias, Jonathan Bisson, Neil P Roberts, Jennifer V E Brown, Corrado Barbui, Rachel Churchill, Karina Lovell, Dean McMillan, Simon Gilbody

“…We performed a systematic review and component network meta-analysis to assess the effectiveness of psychological and pharmacological interventions for managing mental health problems in people exposed to complex traumatic events.…”
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Landslide Forecasting Model Based on PCA and Improved CS-RBF by WANG Lianxia, LI Limin, FANG Zihao, REN Ruibin, FU Zhentao, CUI Chengtao

“…Taking the landslide monitoring points in Shanyang County, Shaanxi Province as an example, this study proposes a landslide probability forecasting model based on principal component analysis (PCA) and cuckoo search (CS) optimized radial basis function (RBF) neural network. …”
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A Scalable Data-Driven Surrogate Model for 3D Dynamic Wind Farm Wake Prediction Using Physics-Inspired Neural Networks and Wind Box Decomposition by Qiuyu Lu, Yuqi Cao, Pingping Xie, Ying Chen, Yingming Lin

“…Existing data-driven surrogate models based on neural networks often struggle with the high dimensionality of the flow field and scalability to large wind farms. …”
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EEG-Based Sleep Stage Classification via Neural Architecture Search by Gangwei Kong, Chang Li, Hu Peng, Zhihui Han, Heyuan Qiao

“…At this stage, most automatic staging neural networks are designed by human experts, and this process is time-consuming and laborious. …”
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Forecasting Peak Hours for Energy Consumption in Regional Power Systems by S. R. Saitov, N. D. Chichirova, A. A. Filimonova, N. B. Karnitsky

“…Timely forecasting of peak hours will make it possible, on the one hand, to reduce consumer costs for payments for electric power, and on the other hand, to smooth out the daily schedule of electric load of the power system, thereby optimizing the operation of generating equipment of stations and networks of the system operator. …”
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