Quantitative evaluation of tight gas reservoir classification based on analytic hierarchy process: A case study of Penglaizhen Formation gas reservoir in Xinchang Gas Field by ZHOU Feng,HUANG Shilin,LI Xiaoming,LIAO Kaigui,LI Yong

“…Ultimately, this study offers valuable insights and a methodological framework for the efficient development of similar gas reservoirs.…”
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Source Term Estimation for Puff Releases Using Machine Learning: A Case Study by John Bartzis, Spyros Andronopoulos, Ioannis Sakellaris

“…Puff movement is highly stochastic due to atmospheric turbulence, intensified by complex urban canopies. This complexity, combined with time limitations, makes advanced computational modeling impractical. …”
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Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation by Bernardo Cândido, Ushasree Mindala, Hamid Ebrahimy, Zhou Zhang, Robert Kallenbach

“…This integrated framework provides practical insights for precision agriculture and optimized pasture management, significantly advancing efficient and sustainable rangeland monitoring.…”
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Adaptive Congestion Detection and Traffic Control in Software-Defined Networks via Data-Driven Multi-Agent Reinforcement Learning by Kaoutar Boussaoud, Abdeslam En-Nouaary, Meryeme Ayache

“…Efficient congestion management in Software-Defined Networks (SDNs) remains a significant challenge due to dynamic traffic patterns and complex topologies. …”
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Physarum-inspired multi-parameter adaptive routing protocol for coal mine hybrid wireless mesh networks by Guangzhi Han, Haifeng Jiang, Liansheng Lu, Shanshan Ma, Shuo Xiao

“…Hybrid wireless mesh networks are suitable for complex environment communication in coal mine. Mesh clients with application service and routing function in hybrid wireless mesh networks can form a highly robust hybrid network with mesh routers. …”
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Harnessing Artificial Intelligence and Machine Learning for Identifying Quantitative Trait Loci (QTL) Associated with Seed Quality Traits in Crops by My Abdelmajid Kassem

“…Recent advances in artificial intelligence (AI) and machine learning (ML) provide powerful alternatives that enable more accurate trait prediction, robust marker-trait associations, and efficient feature selection. This review presents an integrated overview of AI/ML applications in QTL mapping and seed trait prediction, highlighting key methodologies such as LASSO regression, Random Forest, Gradient Boosting, ElasticNet, and deep learning techniques including convolutional neural networks (CNNs) and graph neural networks (GNNs). …”
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Morphological Analysis and Subtype Detection of Acute Myeloid Leukemia in High-Resolution Blood Smears Using ConvNeXT by Mubarak Taiwo Mustapha, Dilber Uzun Ozsahin

“…(1) Background: Acute Myeloid Leukemia (AML) is a complex hematologic malignancy where accurate subtype classification is crucial for targeted treatment and improved patient outcomes. …”
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THE RESULTS OF USE OF THE INITIAL MATERIAL DURING DURUM WINTER WHEAT BREEDING IN THE KUBAN CONDITIONS by A. A. Mudrova, A. S. Yanovsky

“…It has been shown a significant role of the varieties of durum spring wheat ‘Oviachic 65’ from Mexico and a mutant form of soft winter wheat ‘Krasnodarsky karlik 1’ with efficient genes of height reduction ‘rht’ for plant height reduction and for further increase of productivity and of stability to lodging. …”
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Missing Categorical Data in Sociological Surveys: An Experimental Evaluation of Imputation Techniques by Yaroslav Kostenko, Andrii Gorbachyk

“…K-Nearest Neighbors showed promise with smaller predictor sets, offering a computationally efficient alternative. The work emphasizes the importance of principled imputation and provides practical recommendations for sociologists regarding method selection, predictor set construction, and consideration of computational costs when addressing missing categorical data.…”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…Our findings indicate that the LSTM model effectively captures and predicts the complex relationships between key design parameters—efficiency, fill factor, and open-circuit voltage—and degradation-induced changes in PSCs. …”
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Constraints on multi-item working memory access: performance costs and retrieval dynamics by Chen Tiferet-Dweck, Chen Tiferet-Dweck, Abigail Keegan, Kerstin Unger, Kerstin Unger

“…Instead, we found that selecting two out of three items was slower and less accurate than selecting one, arguing against the idea that diminished inhibition underlies multi-item retrieval efficiency. …”
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Methylations with methanol via bioinspired catalytic C–O bond cleavage by Qing Huang, Yao Xiang, Yaqi Wu, Yuzhu Zheng, Rong-Zhen Liao, Youwei Xie

“…Abstract Nature has a delicate system for catalysis due to optimization through evolution, which often displays unparalleled efficiency and selectivity. “Learning from nature” is a popular and effective approach in designing alternative reactions and catalysts when traditional strategies fail. …”
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Curb Detection and Mapping via Robust Iterative Gaussian Process Regression by Di Wang, Si Chen, Zhenni Ma, Jiajia Shi, Fuchun Zhang

“…Curb detection and mapping are of great importance to ensure the safety and efficiency of intelligent vehicles. However, it remains challenging because shape estimation under noise and outliers is not well addressed in real traffic scenarios. …”
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Digital security risk identification and model construction of smart city based on deep learning by Zhilei Zhao

“…In order to deal with these problems, this paper designs a flexible three-layer architecture framework, and introduces a new intrusion detection feature selection method that combines flock optimization (CSO) and genetic algorithm (GA) to reduce the complexity of feature selection and enhance the detection and processing power of security vulnerabilities through deep neural networks (DNN). …”
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BiLSTM-Based Parallel CNN Models With Attention and Ensemble Mechanism for Twitter Sentiment Analysis by Anas W. Abulfaraj

“…However, the current approaches to analyzing word-of-mouth on social media face significant challenges like lack of feature integration, low sentiment analysis efficiency, low topic identification efficiency, issues with data scarcity, and the high costs of annotations. …”
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Research on Multi-objective Shielding Intelligent Optimization Method Based on Non-dominated Sorting Genetic Algorithm NSGA-Ⅲ by WANG Mengqi, ZHENG Zheng, MEI Qiliang, PENG Chao, GAO Jing, ZHOU Yan

“…The program’s functionality was tested and validated to improve the efficiency and effectiveness of shielding design for spent fuel transport ship. …”

A review article on the assessment of additive manufacturing by Teshager Awoke Yeshiwas, Atalay Bayable Tiruneh, Milashu Asnake Sisay

“…ML-integrated process optimization techniques are shown to enhance part performance and production efficiency. Additionally, this study compares AM with subtractive manufacturing (SM), focusing on material utilization, energy efficiency, and production flexibility. …”
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N6-methyladenine identification using deep learning and discriminative feature integration by Salman Khan, Islam Uddin, Sumaiya Noor, Salman A. AlQahtani, Nijad Ahmad

“…To optimize computational efficiency and eliminate irrelevant or noisy features, an unsupervised Principal Component Analysis (PCA) algorithm is employed, ensuring the selection of the most informative features. …”
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Effects of Leaf Trait Variability on PM Retention: A Systematic Review by Wenkai Xue, Yongjun Lin, Zhengqi Sun, Yuchong Long, Dele Chen, Shan Yin

“…Trichomes decrease the likelihood of particle resuspension and boosts the efficiency of PM retention. 5. Leaves with high rigidity and complex multi-faceted leaf shapes are typically presumed to exhibit higher PM retention efficiency for higher edge effects and increased interleaf turbulence. …”
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Sparse Feature-Weighted Double Laplacian Rank Constraint Non-Negative Matrix Factorization for Image Clustering by Hu Ma, Ziping Ma, Huirong Li, Jingyu Wang

“…Consequently, the SFLRNMTF approach becomes more robust in capturing data patterns and achieving high-quality clustering results in complex datasets. We also propose an efficient alternating iterative update algorithm to optimize the proposed model and provide a theoretical analysis of its performance. …”
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