The Use of General Inverse Problem Platform (GRIPP) as a Robust Backtracking Solution by Nikolas Gomes Silveira de Souza, Jader Lugon, Alexandre Macedo Fernandes, Ramiro Joaquim de Jesus Neves, Antônio José da Silva Neto

“…This study addresses the challenge of identifying pollutant sources in aquatic coastal environments using inverse problem techniques hampered by particularities in hydrodynamic and Lagrangian models. An approach is presented employing the General Inverse Problem Platform (GRIPP) coupled with a General Simulated Annealing (GenSA) algorithm for robust backtracking. …”
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Three-dimensional image-guided navigation technique for femoral artery puncture by Yunmeng Zhang, Shenglin Liu, Qiang Zhang, Qingmin Feng

“…An improved ICP method is implemented to optimize surface point cloud alignment, providing higher efficiency and accuracy compared to conventional approaches. …”
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Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction. by Kang Xu, Bin Pan, MingXin Zhang, Xuan Zhang, XiaoYu Hou, JingXian Yu, ZhiZhu Lu, Xiao Zeng, QingQing Jia

“…Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to accurately model the spatial relationships in complex road networks; and (3) end-to-end training, which often results in unclear optimization directions for model parameters, thereby limiting improvements in predictive performance. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…In treatment planning, AI could improve approaches by optimizing surgical resection, radiotherapy regimen, and chemotherapy protocols. …”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
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Factors influencing the effectiveness of SM-VCE method in solving 3D surface deformation by Xupeng Liu, Guangyu Xu, Mingkai Chen, Tengxu Zhang

“…The latter type applies to earthquakes that do not cause surface ruptures and have extensive blind faults. Currently, most research focuses on improving the above types of methods. …”
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User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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Research on Dynamic Storage Location Assignment of Picker-to-Parts Picking Systems under Traversing Routing Method by Xiangbin Xu, Chenhao Ren

“…Then, the adjustment gain model of dynamic storage location assignment is built, and a genetic algorithm is designed to find the final adjustment solution. …”
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Robust Planning for Hydrogen-Based Multienergy System Considering P2HH and Seasonal Hydrogen Storage by Shufan Wang, Dong Yang, Linglu Zhang, Lingzhi Chenmei

“…This paper proposes an optimal planning model for the hydrogen-based integrated energy system (HIES) considering power to heat and hydrogen (P2HH) and seasonal hydrogen storage (SHS) to take full advantage of multienergy complementarity. …”
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Real-time prediction of HFNC treatment failure in acute hypoxemic respiratory failure using machine learning by Xiaojie Li, Chunliang Jiang, Qingyan Xie, Huiquan Wang, Jiameng Xu, Guanjun Liu, Panpan Chang, Guang Zhang

“…The soft-voting ensemble algorithm achieved an optimal predictive performance with an AUC of 0.839 (95% CI 0.786–0.889) for the all-features model, while logistic regression using common features achieved an AUC of 0.767 (95% CI 0.704–0.825), outperforming ROX and mROX indices. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

“…Also, the most applied machine learning algorithms are Linear Regression (LR), Random Forest (RF), and Gradient Boosting Trees (GBT) whereas the most applied deep learning algorithms are Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM). …”
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Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
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Hyperspectral Detection of Pesticide Residues in Black Vegetable Based on Multi-Classifier Entropy Weight Method by Rongchang Jiang, Guoqiang Zhuang, Shijie Xie, Yang Wang, Guoqi Zhang, Dandan Qu, Wanzhi Wen

“…The entropy weight method was then used to optimize model weights, developing the multi-classifier entropy weighted method algorithm to improve detection accuracy and robustness. …”
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A Lightweight YOLO-Based Architecture for Apple Detection on Embedded Systems by Juan Carlos Olguín-Rojas, Juan Irving Vasquez, Gilberto de Jesús López-Canteñs, Juan Carlos Herrera-Lozada, Canek Mota-Delfin

“…In Mexico, the manual detection of damaged apples has led to inconsistencies in product quality, a problem that can be addressed by integrating vision systems with machine learning algorithms. The YOLO (You Only Look Once) neural network has significantly improved fruit detection through image processing and has automated several related tasks. …”
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A Reputation Value-Based Task-Sharing Strategy in Opportunistic Complex Social Networks by Jia Wu, Fangfang Gou, Wangping Xiong, Xian Zhou

“…The two submodels apply an improved particle swarm algorithm and a Lagrange multiplier, respectively. …”
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Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms by Wenhao Ren, Zuowei Zhong

“…Firstly, this model optimizes the Path Aggregation Network (PAN) by introducing lateral skips and weighted feature fusion mechanisms, improving the multi-scale fusion capability of bare concrete crack features. …”
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A novel LSTPA methodology for managing energy in electrical/thermal microgrids through CHP, battery resources, thermal storage, and demand-side strategies by Elmira Akhavan Maroofi, Mahmoud Samiei Moghaddam, Azita Azarfar, Reza Davarzani, Mojtaba Vahedi

“…Abstract This paper presents a stochastic optimization model for integrated energy management in electrical and thermal microgrids, addressing uncertainties in renewable energy resources. …”
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Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things by Rui SHE, Ningchi ZHANG, Yanru WANG, Dandan GUO, Wenjie MA, Hui LIU, Jie ZHANG

“…The closed expressions of spectrum access probability and throughput are derived; in order to further increase the accuracy of the classification results, an improved K-means algorithm is proposed. The alternate iterative algorithm is implemented to jointly optimize the detection time, node power and the number of user clusters such that the system throughput can be maximized eventually. …”
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Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…These additions help achieve an initial reduction in model size while preserving detection accuracy. Furthermore, we optimize the model by removing redundant parameters using the DepGraph pruning algorithm, which facilitates its application on edge devices. …”
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