An interpretable integrated machine learning framework for genomic selection by Jinbu Wang, Jia Zhang, Wenjie Hao, Wencheng Zong, Mang Liang, Fuping Zhao, Longchao Zhang, Lixian Wang, Huijiang Gao, Ligang Wang

“…Moreover, we introduced the NuSVR model, which achieved the highest accuracy among nine compared algorithms. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…In response to the complex and easily interfered characteristics of near-infrared spectral signals, an innovative BP neural network algorithm is introduced to construct a prediction model. …”
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Data-driven approach to mid-latitude coherent scatter radar data classification by Berngardt Oleg

“…Based on 2021 data, a solution of the problem of automatic data classification is presented without their labeling by an expert and without postulating the number of classes. The algorithm automatically labels the data, determines the optimal number of signal classes observed by the radars, and trains a two-layer classifying neural network of an extremely simple structure. …”
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An Integrated Approach to Scheduling B-CAVs in Container Terminals considering Battery Management by Shuo Wang, Jiliang Luo, Weimin Wu, Dahai Zhang, Tao Zhang

“…Furthermore, a congestion-free path plan-based improved genetic algorithm is presented to obtain a near-optimal plan for dispatching B-CAVs to perform transporting and charging operations. …”
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Notice of Violation of IEEE Publication Principles: Dynamic Embedding and Scheduling of Service Function Chains for Future SDN/NFV-Enabled Networks by Haotong Cao, Hongbo Zhu, Longxiang Yang

“…Subsequently, to remove the NP-hardness of the MILP model, a dynamic VNF embedding and scheduling algorithm is proposed. …”
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Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…Further, an adaptive coati optimization algorithm is used to adjust the hyperparameters of the classification models. …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…However, several challenges persist, such as the complexity of multimodal data integration, limitations in model generalization capabilities, and the need for real-time prediction and dynamic adjustments, all of which necessitate continuous technological innovations, algorithm optimization, and interdisciplinary collaborations. …”
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Credit approval classification through a WASD neuronet by Mourtas Spyridon D.

“…In light of this, a new weights and structure determination (WASD) neuronet has been developed to address the two issues of credit approval mentioned above, as well as to manage its particular features. We improve the learning process of the WASD algorithm with a novel activation function for optimal adaptation to the credit approval model, motivated by the finding that WASD neuronets perform better than traditional back-propagation neuronets in terms of slow training speed and trapping in a local minima. …”
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Research on Heat Dissipation Effect of Radiator Structure of Disc Brake for High-speed Train by Xin WANG, Guoquan WANG, Yong CHEN

“…In order to improve the safety of the braking process of high-speed train, the brake disc heat dissipation structure needs to be optimized. …”
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Research on autonomous obstacle avoidance of mountainous tractors based on semantic neural network and laser SLAM. by Ningjie Chang, Xianghai Yan, Bingxin Chen, Yiwei Wu, Liyou Xu

“…The accuracy and consistency of obstacle avoidance map construction are poor in complex and changeable dynamic environment. In order to improve the driving safety of mountain tractors in complex mountain environment, an autonomous obstacle avoidance method for mountain tractors based on semantic neural network and laser SLAM was studied. …”
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The Next Frontier in Brain Monitoring: A Comprehensive Look at In-Ear EEG Electrodes and Their Applications by Alexandra Stefania Mihai (Ungureanu), Oana Geman, Roxana Toderean, Lucas Miron, Sara SharghiLavan

“…Recent studies have demonstrated that in-ear EEG can record signals qualitatively comparable to scalp EEG, with an optimized signal-to-noise ratio and improved electrode stability. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…Existing methods, including post-processing optimization, specific model based improvements, and body part feature based methods, have limitations such as inaccurate handling of heavily occluded positive samples, high computational complexity, and susceptible to background noise. …”
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Research on economic dispatching strategy for active distribution network considering high penetration of renewable energy source by ZHANG Yu, YUAN Bo, HUANG Shicheng, SHI Jinyue, AN Yichen

“…The effectiveness of the proposed strategy and the superiority of similar algorithms are validated through using an improved IEEE 33-node test system.…”
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Vehicle-to-Vehicle Communication Channel Estimator Based on Gate Recurrent Unit by Jun-Han Wang, He He, Kosuke Tamura, Shun Kojima, Jaesang Cha, Chang-Jun Ahn

“…To alleviate such issues, this study proposes a channel estimation method by combining the sparrow search algorithm (SSA) and gated recurrent unit (GRU). In addition, this paper adds the attention mechanism to GRU to improve the robustness of the model. …”
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Study on Color Detection of Korla Fragrant Pears by Near-Infrared Spectroscopy Combined with PLSR by Yifan Xia, Yang Liu, Hong Zhang, Jikai Che, Qing Liang

“…The optimal detection models were determined. The results indicated that pre-processing and characteristic extraction improved the accuracy of the PLSR model. …”
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Short-term forecast of wind power based on the division of wind speed fluctuation characteristics by QIAO Titang, XIE Lirong, YE Jiahao, GAO Yang, DAI Bing

“…The dynamic time warping algorithm is used to mine the fluctuating wind similar data in the historical data, and a training sample data set is constructed combining with the corresponding historical wind power; a hunger game search algorithm is used to optimize the hyperparameters of the gated recurrent unit neural network, and a combined prediction model for three fluctuation stages is established. …”
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Dynamic-budget superpixel active learning for semantic segmentation by Yuemin Wang, Ian Stavness

“…A static budget could result in over- or under-labeling images as the number of high-impact regions in each image can vary.MethodsIn this paper, we present a novel dynamic-budget superpixel querying strategy that can query the optimal numbers of high-uncertainty superpixels in an image to improve the querying efficiency of regional active learning algorithms designed for semantic segmentation.ResultsFor two distinct datasets, we show that by allowing a dynamic budget for each image, the active learning algorithm is more effective compared to static-budget querying at the same low total labeling budget. …”
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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…Preprocessing methods like K-means clustering, Fuzzy C-Means, and PCA, along with ensemble approaches, further improved model accuracy. Lastly, the study underscores that high-quality, well-labeled datasets, stakeholder involvement, and comprehensive evaluation metrics such as F1 score and precision are crucial for optimizing ML and DL models, making them more effective for real-world applications in sustainable agriculture.…”
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Re-Estimating GEDI Ground Elevation Using Deep Learning: Impacts on Canopy Height and Aboveground Biomass by Rei Mitsuhashi, Yoshito Sawada, Ken Tsutsui, Hidetake Hirayama, Tadashi Imai, Taishi Sumita, Koji Kajiwara, Yoshiaki Honda

“…The broader application of this method may improve global carbon cycle understanding and climate models.…”
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Deep Reinforcement Learning-Based Impact Angle-Constrained Adaptive Guidance Law by Zhe Hu, Wenjun Yi, Liang Xiao

“…We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. …”
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