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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Experimental determination and theoretical calculation for CO2 liquid-solid phase equilibrium in PLNG by Zihe LI, Jianlu ZHU, Qing MIAO, Feng YAN, Xin OUYANG, Chaofei NIE, Hui HAN, Yuxing LI

“…The calculations demonstrated improved accuracy in CO2 solid solubility derived from the established model that was optimized using the genetic algorithm. …”
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Integrated Operational Planning of Battery Storage Systems for Improved Efficiency in Residential Community Energy Management Using Multistage Stochastic Dual Dynamic Programming:... by Pattanun Chanpiwat, Fabricio Oliveira, Steven A. Gabriel

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Cooperative sensing method considering malicious nodes in cognitive radio networks by Xiao-gang QI, Sheng-yu ZHENG, Li-fang LIU, Hui-fang WANG

“…Based on a more practical cognitive radio network with malicious users,the spectrum sharing network model based on the cooperative spectrum sensing was studied that the secondary user can dynamically adjust its transmit power based on cooperative sensing results.To avoid significant reduction in performance of spectrum sensing system caused by malicious nodes,it is aimed to study how to improve the performance of cooperative sensing.By introducing the convex optimization problem,the secondary network throughput is maximized under the certain detection probability conditions and the corresponding power constraints.Simulation results show that whether or not there are malicious nodes,the algorithm is efficient in calculating optimal sensing time and the optimal transmit powers,and the secondary network throughput is increased when the maximum interference power limits and the maximum transmit power restrictions are decreased.…”
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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The priors are constructed using cosine similarity, mean, and intensity, where intensity is computed using the improved Papoulis–Gerchberg algorithm. The image is reconstructed using the probabilistic maximum a posteriori estimate. …”
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Research and Design of an Active Light Source System for UAVs Based on Light Intensity Matching Model by Rui Ming, Tao Wu, Zhiyan Zhou, Haibo Luo, Shahbaz Gul Hassan

“…By collecting and comparing visible light images of different color light sources under various intensities and constructing the light intensity matching model using the comprehensive peak signal-to-noise ratio parameter, the model is optimized to ensure the best vision tracking performance under different lighting conditions. …”
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Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping by Oluwatobi Emmanuel Dare, Kennedy Okokpujie, Emmanuel Adetiba, Olabode Idowu-Bismark, Abdultaofeek Abayomi, Raymond Jules Kala, Emmanuel Owolabi, Udeme Christopher Ukpong

“…Xgboost, SVM, and kriging variogram models were explored to generate ground truth datasets for the CGAN model training, and the best algorithm was employed. …”
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Machine learning-based risk prediction model for pertussis in children: a multicenter retrospective study by Juan Xie, Run-wei Ma, Yu-jing Feng, Yuan Qiao, Hong-yan Zhu, Xing-ping Tao, Wen-juan Chen, Cong-yun Liu, Tan Li, Kai Liu, Li-ming Cheng

“…The application of this model can help optimize the early identification and management of high-risk patients and improve clinical decision-making. …”
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A target detection model HR-YOLO for advanced driver assistance systems in foggy conditions by Yao Zhang, Na Jia

“…Abstract To improve the accuracy and real-time performance of detection algorithms in Advanced Driver Assistance Systems (ADAS) under foggy conditions, this paper introduces HR-YOLO, an improved YOLO-based model specifically designed for vehicle and pedestrian detection. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
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Enhancing Flexibility of Virtual Power Plants Considering Reconfiguration of District Heating Network by Peinan Fan, Yixun Xue, Haotian Zhao, Xinyue Chang, Jia Su, Ke Wang, Hongbin Sun

“…Case studies based on an actual CHP-VPP certify the validity of the proposed model and algorithm.…”
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Accelerating automatic model finding with layer replications case study of MobileNetV2. by Kritpawit Soongswang, Chantana Chantrapornchai

“…For a given network, various layers can be replicated, and effective replication can yield better accuracy. Our proposed algorithm identifies the optimal layer replication configuration for the model. …”
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A model study of teaching method reform of computer laboratory course integrating internet of things technology. by Xiao Zhou, Ledan Qian, Haider Aziz, Marvin White

“…In particular, face capture services improve student concentration to create an efficient classroom atmosphere by using face recognition algorithms that support end devices. …”
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Storage life evaluation of photodetector based on multi-parameter performance degradation and competitive failure by ZHANG Yeping, YANG Tongbo, LI Ziwei

“…This method comprehensively considered whether the key performance parameters of the sample have deteriorated or improved trend. Firstly, the optimal degradation model with a single parameter was selected by performance degradation modeling, so that the pseudo-life of the sample with increasing degradation trend was calculated according to the failure threshold, and the pseudo-life was regarded as the right-censored data for the sample with decreasing degradation trend. …”
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Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-Dimensional Tokens by Vittorio Erba, Emanuele Troiani, Luca Biggio, Antoine Maillard, Lenka Zdeborová

“…We note that modern architectures naturally subsume the BSR model due to the skip connections. Building on recent methodological progress, we compute the Bayes-optimal generalization error for the model in the limit of long sequences of high-dimensional tokens and provide a message-passing algorithm that matches this performance. …”
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Evolutionary fuzzy learning for Chinese medicine liver syndrome differentiation by Jia-Yu Yan, Peng-Wei Zhang, Wei-Guo Sheng, Jun-Ping Shi, Wei Ni, Li Li, Yu-Jun Zheng

“…To determine the most appropriate fuzzy membership functions of the fuzzy learning machines, an evolutionary algorithm was employed to optimize the types and parameters of the fuzzy functions simultaneously. …”
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School-level prediction and management of myopia in children and adolescents by Shengsong Xu, Linling Li, Yingting Zhu, Zhenbang Ruan, Yiwen Qu, Zhuandi Zhou, Yin Hu, Zhidong Li, Fei Hou, Xiaohua Zhuo, Yunxia Leng, Xuelin Huang, Yamei Lu, Zhirong Wang, Shuifeng Deng, Yehong Zhuo, Guoming Zhang, Min Fu, Xiao Yang

“…The interactions between age and other variables were revealed by the algorithms, and hence the final prediction models were established based on age segmentation. …”
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Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

“…In response to the rapid and accurate distribution network security situation awareness requirements, this paper proposes a distribution network security situation awareness method based the distribution network topology layered model. First, a hierarchical model of the distribution network topology under the premise of optimizing the location of the synchronous phasor measuring device is constructed. …”
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Construction of Industrial Economic Management Decision Model Based on Three Parameter Interval Grey Numbers by Pao-Ching Lin, Tzu-Jung Wu, Jui-Chan Huang

“…This model characterizes the uncertainty of decision information by introducing three parameter interval grey numbers, and innovatively adopts grey relational clustering decision-making method, combined with genetic algorithm to dynamically optimize key parameters. …”
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Detection of kidney bean leaf spot disease based on a hybrid deep learning model by Yiwei Wang, Qianyu Wang, Yue Su, Binghan Jing, Meichen Feng

“…Based on this dataset, a novel hybrid deep learning model framework is proposed, which integrates deep learning models (EfficientNet-B7, MobileNetV3, ResNet50, and VGG16) for feature extraction with machine learning algorithms (Logistic Regression, Random Forest, AdaBoost, and Stochastic Gradient Boosting) for classification. …”
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