Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…Improved some C3 modules of the backbone network, and integrated CA coordination attention mechanism into the C3 module, which improved the recognition accuracy and detection speed of the model while reducing the number of model parameters. Finally, optimized the path aggregation network of the model to enhance the feature fusion ability of the network.ResultsThe experimental results showed that the improved Our⁃YOLOv5s model had a mAP of 98.4% and a detection speed of 64 s-1 in the dataset, which was 2.4% and 6 s-1 higher than the original model, respectively.ConclusionThe model can meet the real⁃time detection requirements of marine fish.…”
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Inversion Model for Total Nitrogen in Rhizosphere Soil of Silage Corn Based on UAV Multispectral Imagery by Hongyan Yang, Jixuan Yan, Guang Li, Weiwei Ma, Xiangdong Yao, Jie Li, Qihong Da, Xuchun Li, Kejing Cheng

“…The optimal period for TN inversion was determined. The SVM-RFE algorithm outperformed the models built without feature selection in terms of accuracy. …”
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Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

“…Consequently, SNet inherits TNet’s capabilities and further refines them during optimization. For comparison, we combine three interpolation algorithms with three super-resolution algorithms and select the one with the best performance. …”
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Prediction of permeability and effective porosity values using ANN in Maleh field by Mohammed Essa Nassani, Ali Alaji

“…The ANN was tested on independent data and demonstrated exceptional performance, achieving 96% accuracy for effective porosity and 98% for permeability predictions in sandstone formations. This efficient algorithm eliminates the need for core sample analysis, reducing costs and time while improving prediction reliability, making it a valuable tool for subsurface characterization and resource exploration.…”
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Mission Sequence Model and Deep Reinforcement Learning-Based Replanning Method for Multi-Satellite Observation by Peiyan Li, Peixing Cui, Huiquan Wang

“…Both phases are formulated as Markov Decision Processes (MDPs) and optimized using the PPO algorithm. Extensive simulations demonstrate that our method significantly outperforms state-of-the-art approaches, achieving a 15.27% higher request insertion revenue rate and a 3.05% improvement in overall mission revenue rate, while maintaining a 1.17% lower modification rate and achieving faster computational speeds. …”
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Onboard Decision-making System of Unmanned Mine Truck by WANG Jia, HUANG Jiade, LIU Zhicong, HUANG Peng, LYU Liang

“…This paper adopts the quadratic programming algorithm based on the shortest time and the optimal energy consumption to solve the speed planning, and adopts the hybrid A-star and curve fitting algorithm based on special scenarios to solve the local path planning, so that the operation efficiency can be improved by 10%~20% in the loading and unloading parking scenario. …”
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LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…A Focal-EIoU loss function is also integrated to optimize the model’s training process. Experimental results show that compared to YOLOv8, the LCDDN-YOLO model reduces the number of parameters by 12.9% and the floating-point operations (FLOPs) by 9.9%, while precision, mAP@50, and recall improve by 4.6%, 6.5%, and 7.8%, respectively, reaching 89.5%, 85.4%, and 80.2%. …”
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Traffic light detection and recognition based on deep learning for autonomous-rail rapid tram by XIONG Qunfang, LIN Jun, YUAN Xiwen, XU Yanghan, YUE Wei, LI Yuanzhengyu

“…These abnormal image data were saved and utilized for further training and optimizing the model. Experimental results reveals that the proposed approach effectively detected and recognized ART traffic lights, achieving an average detection precision of 84.76% on designated roads during the daytime while exhibiting good real-time performance.…”
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Protein structural domain-disease association prediction based on heterogeneous networks by Jingpu Zhang, Lianping Deng, Lei Deng

“…Small proteins are often found to be composed of only a single domain, while most large proteins consist of multiple domains for achieving various composite cellular functions. …”
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Design of Restrictive Conditions for Simultaneous Loading and Unloading of Goods with Different Temperature Regimes in Vehicle Routing Problem by Kleprlík Jaroslav, Brázdová Markéta

“…Considering the proposed conditions in these algorithms will increase the utilization of the vehicle payload, and load space while complying with the established mandatory rules for the transport of foodstuffs. …”
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The interpretable machine learning model for depression associated with heavy metals via EMR mining method by Site Xu, Mu Sun

“…The highest-performing model, an eXtreme Gradient Boosting (XGB) algorithm optimized with GA, identified depression using 16 heavy metal indicators (AUC: 0.686; 95% CI: 0.68–0.69; accuracy: 97.1%). …”
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An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…In order to improve the training learning rate, Adam optimizer combining momentum algorithm and RMSprop algorithm is used to dynamically adjust the learning rate; the combination of the two algorithms makes the loss function converge to the lowest point faster. …”
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DECISION SUPPORT SYSTEM IN PLANNING INVESTMENT PROJECTS by Viktor Kosenko

“…The following results were obtained: it is shown that the efficiency of the investment process is related to the assessment and selection of the most attractive investment projects from a number of alternatives, which will provide the maximum profit in the future; the strategic tasks of investing in the development of organizations and enterprises are singled out; the main finances that can be involved in carrying out an investment project are considered; the concepts of an investment project, a subject and an object of the investment activity were defined; the above concepts were formalized using the theory of sets and the system approach; the basic conditions under which the project should be implemented are formulated; the generalized diagram of the investment project implementation is developed. While developing the method of selecting the optimal variant of the investment project, the types of source information about the project and the organization which will use the finances are involved are determined. …”
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Research into prediction and influential factors of circuit breaker closing time using BFGS-NN by Longcheng Dai, Jiaying Yu, Zhihui Huang, Hui Ni, Yifan Zhang, Junting Dou

“…On-site operational data were analyzed to build a circuit breaker action time database. The BFGS algorithm trained on these data generated a closing time prediction model, achieving rapid convergence and optimal fit during learning. …”
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HiCoACR: A reconfiguration decision-making model for reconfigurable security protocol based on hierarchically collaborative ant colony by Zhuo Yi, Ying Liao, Xuehui Du, Xin Lu, Lifeng Cao

“…The Explorer controls directions of protocol reconfiguration and generates abstract scheduling sub-goals which are conveyed from the Worker. While the Worker schedules most suitable cryptogram resources for each sub-goal received and produces the optimal reconfiguration solution which is verified and re-optimized by a Lévy process–based stochastic gradient descent algorithm. …”
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Task allocation and path planning for multi-robot systems in intelligent warehousing by CHU Jing, TIAN Yiqiu, YUE Qi, HUANG Yong

“…Additionally, a two-layer path planning strategy is proposed: the outer layer conducts global path planning based on the Floyd algorithm, while the inner layer resolves various collision issues through traffic rule constraints, achieving local optimal path planning. …”
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Growth Curve Models and Clustering Techniques for Studying New Sugarcane Hybrids by Carlos David Carretillo Moctezuma, María Guzmán Martínez, Flaviano Godínez-Jaimes, José C. García-Preciado, Ramón Reyes Carreto, José Terrones Salgado, Edgar Pérez Arriaga

“…According to the Connectivity and Dunn indexes, the DBSCAN algorithm provides the best clustering structure for materials in the plant cycle, while for the ratoon cycle, the k-means algorithm offers the best clustering structure. …”
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A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

“… This study aims to evaluate and compare five algorithms in diabetes detection, namely Flower Pollination Neural Network (FPNN), Particle Swarm Optimization Neural Network (PSONN), Bat Artificial Neural Network (BANN), Stochastic Gradient Descent (SGD), and Quadratic Interpolation Flower Pollination Neural Network (QIFPNN). …”
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YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…This effectively reduces the difficulty and cost of deployment on mobile terminals while significantly improving algorithm accuracy, meeting real-time requirements, and providing a more efficient and feasible technical solution for relevant applications. …”
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Pig Aggression Tracking and Analysis Application Based on A RPMeMOTR Method by Shuqin Tu, Haoxuan Ou, Aqing Yang, Yun Liang, Jiaying Du, Yuefei Cao, Ruilin He, Fang Yuan

“…The management of pig aggression in group-housed environments is crucial for ensuring animal welfare and optimizing production efficiency in the global agricultural industry. …”
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