A Short-Term Load Forecasting Method Considering Multiple Factors Based on VAR and CEEMDAN-CNN-BILSTM by Bao Wang, Li Wang, Yanru Ma, Dengshan Hou, Wenwu Sun, Shenghu Li

“…Finally, the sine–cosine and Cauchy mutation sparrow search algorithm (SCSSA) is used to optimize the parameters of the combinative model to improve the forecasting accuracy. …”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

“…To tackle the challenge of designing an improved diabetes classification algorithm that is more accurate, random oversampling and hyper‐tuning parameter techniques have been used in this study. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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A Systematic Review and Comparative Analysis Approach to Boom Gate Access Using Plate Number Recognition by Asaju Christine Bukola, Pius Adewale Owolawi, Chuling Du, Etienne Van Wyk

“…By optimizing the capabilities of advanced YOLO algorithms, the proposed method seeks to improve the reliability and effectiveness of access control through precise and rapid plate number recognition. …”
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Travel Time Prediction of Urban Agglomeration Significance Channel: A Case Study on the Cross-Hangzhou Bay Channel by Wang Yu, Hu Xiaowei, Cui Shu, Rao Zonghao

“…The Yangtze River Delta is one of the most economically dynamic urban agglomerations in China, with the Hangzhou Bay Bridge and Jiashao Bridge serving as crucial sea-crossing transportation corridors. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. …”
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Features of single treasury account management in the context of budget funds liquidity management by N. S. Sergienko

“…Successful examples of integration of automated financial flow management systems, use of machine learning algorithms for forecasting and optimization of balances on single treasury account, as well as the interdepartmental interaction mechanisms to improve transparency and efficiency of budget management have been considered. …”
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Research on High Arch Dam Deformation Monitoring Model with Deep Capturing Related Features in Factor-time Dimensions by XUE Jianghan, ZHANG Pengtao, TIAN Jichen, LU Xiang, CHEN Jiankang, Guo Yinju

“…However, at the present stage, the dam prediction model based on machine learning mostly adopts the means of data preprocessing, using optimization algorithm, and using the model's characteristics to stack multiple models, lacking in in-depth consideration of the physical mechanism of dam deformation. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Faster RCNN and Yolov8 were used to compare the performance of object detection, and the loss function and accuracy curve before and after model improvement were compared. The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
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Deep learning-based detection and classification of acute lymphoblastic leukemia with explainable AI techniques by Debendra Muduli, Sourav Parija, Suhani Kumari, Asmaul Hassan, Harendra S. Jangwan, Abu Taha Zamani, Sk. Mohammed Gouse, Banshidhar Majhi, Nikhat Parveen

“…Additionally, we evaluated the performance of these models using different optimization techniques, including Adadelta, SGD, RMSprop, and Adam, to determine the most effective optimization strategy for improving classifica-tion accuracy. …”
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Proteomics mapping of cord blood identifies haptoglobin "switch-on" pattern as biomarker of early-onset neonatal sepsis in preterm newborns. by Catalin S Buhimschi, Vineet Bhandari, Antonette T Dulay, Unzila A Nayeri, Sonya S Abdel-Razeq, Christian M Pettker, Stephen Thung, Guomao Zhao, Yiping W Han, Matthew Bizzarro, Irina A Buhimschi

“…This was then subjected to 2(nd)-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. …”
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AHA: Design and Evaluation of Compute-Intensive Hardware Accelerators for AMD-Xilinx Zynq SoCs Using HLS IP Flow by David Berrazueta-Mena, Byron Navas

“…We outline criteria for selecting algorithms to improve speed and resource efficiency in HLS design. …”
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Development of a machine learning model for predicting renal damage in children with closed spinal dysraphism by Yu He, Wan-liang Guo, Ming-chang Zhang

“…The Shapley additive explanations (SHAP) algorithm and Local Interpretable Model-Agnostic Explanations (LIME) were used to interpret the optimal model. …”
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Parameterization of user functions in digital signal processing for obtaining angular superresolution by A. A. Shchukin, A. E. Pavlov

“…Objectives. One of the most important tasks in the development of goniometric systems is improving resolution in terms of angular coordinates. …”
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Efficient and Motion Correction-Free Myocardial Perfusion Segmentation in Small MRI Data Using Deep Transfer Learning From Cine Images: A Promising Framework for Clinical Implement... by German Garcia-Jara, Angel Jimenez-Molina, Esteban Reyes, Nicolas Tapia-Rivas, Cristobal Ramos-Gomez, Jose De Grazia, Matias Sepulveda

“…This methodology includes normalization and cropping of cine images using a Region-of-Interest detector based on a Markovian, graph-based visual saliency algorithm improved by a sequence of morphological operations. …”
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Zonal Estimation of the Earliest Winter Wheat Identification Time in Shandong Province Considering Phenological and Environmental Factors by Jiaqi Chen, Xin Du, Chen Wang, Cheng Cai, Guanru Fang, Ziming Wang, Mengyu Liu, Huanxue Zhang

“…Other zones reached optimal timing between late December and late January, all with OA above 95%. …”
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Current project of management guidelines of the patients with nosocomial pneumonia in adults by Maria A. Karnaushkina, Andrey G. Maliavin, Leonid I. Dvoretckiy, Sergey V. Yakovlev, Sergey L. Babak, Sergey V. Fedosenko, Margarita P. Suvorova, Natalia F. Razgulyeva, Albina B. Arutyunova

“…The quick introduction of management guideline algorithm of the patients with nosocomial pneumonia and the precise indication of the dose regime into clinical practice will allow doctors to decrease the death rate and improve the quality of medical service.…”
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Subjective Air Traffic Complexity Analysis Based on Weak Supervised Learning by Weining ZHANG, Weijun PAN, Changqi YANG, Xinping ZHU, Jianan YIN, Jinghan DU

“…Compared with the K-means algorithm based on Euclidean distance, metric learning improves the optimal silhouette coefficient and Davidson-Boldin index by 31.80% and 12.97%, respectively. …”
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A Machine Learning Approach to Analyze Manpower Sleep Disorder by Reza Amiri

“…Moreover, a combination of machine learning and metaheuristic algorithms such as eXtreme Gradient Boosting and particle swarm optimization are used to make an accurate predictive model. …”
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Underwater Target 3D Reconstruction via Integrated Laser Triangulation and Multispectral Photometric Stereo by Yang Yang, Yimei Liu, Eric Rigall, Yifan Yin, Shu Zhang, Junyu Dong

“…At the same time, we propose to optimize the laser place calibration and laser line separation processes, further improving the reconstruction performance of underwater laser triangulation and multispectral photometric stereo. …”
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