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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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Here, we propose a hybrid quantum-classical algorithm, called local subspace variational quantum compilation (LSVQC), for compiling the time-evolution operator of quantum many-body systems. …”
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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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Designing diverse and high-performance proteins with a large language model in the loop. by Carlos A Gomez-Uribe, Japheth Gado, Meiirbek Islamov

“…We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse and adaptive sequence sampling (BADASS) to design sequences. …”
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Leveraging machine learning to evaluate the effect of raw materials on the compressive strength of ultra-high-performance concrete by Mohamed Abdellatief, G. Murali, Saurav Dixit

“…The impact of 12 influential features on CS was evaluated to optimize the performance of the proposed models. Among the algorithms, XGB outperformed the others with an R² of 90.1 % and a lower RMSE of 11.52 MPa, surpassing RF (88.7 %), GB (89.2 %), and GPR (86.1 %). …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…The approach addresses key limitations in UBEM while offering a robust tool for policymakers and urban planners to optimize energy consumption and reduce carbon emissions. …”
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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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Adverse events in the neonatal intensive care unit identified by triggers by Fabiana Bragança Albanese, Deise de Souza Ventura, Deise de Souza Ventura, Maurício Wesley Perroud, Maurício Wesley Perroud, Rafael Nogueira de Souza, Mariana Vieira Morau, Marília Berlofa Visacri, Marília Berlofa Visacri, Patricia Moriel, Patricia Moriel

“…AE severity was assessed using the Neonatal Adverse Event Severity Scale (NAESS) and the World Health Organization (WHO) classification, while ADR causality was evaluated using the WHO criteria and the algorithm proposed by Du et at. …”
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In situ fully vectorial tomography and pupil function retrieval of tightly focused fields by Xin Liu, Shijie Tu, Yiwen Hu, Yifan Peng, Yubing Han, Cuifang Kuang, Xu Liu, Xiang Hao

“…When combined with our decoding algorithm, this strategy mitigates the imperfections in the detection path. …”
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Balancing resource utilization and slice dissatisfaction through dynamic soft slicing for 6G wireless networks by Zeinab Sasan, Siavash Khorsandi

“…The problem is formulated as a Mixed Integer Linear Programming (MILP) model, aiming to maximize network utilization while minimizing slice dissatisfaction. Given the NP-hard nature of the problem, we propose the Heuristic Resource Allocation for Soft Slicing (HRASS) algorithm, which achieves near-optimal performance with significantly reduced computational complexity. …”
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Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case by Ivan Izonin, Roman Tkachenko, Nazarii Hovdysh, Oleh Berezsky, Kyrylo Yemets, Ivan Tsmots

“…The proposed method was tested on a small dataset within transplantology, focusing on binary classification. Optimal parameters for the method were identified using the Dual Annealing algorithm. …”
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Impedance-Driven Decoupling Water–Nitrogen Stress in Wheat: A Parallel Machine Learning Framework Leveraging Leaf Electrophysiology by Shuang Zhang, Xintong Du, Bo Zhang, Yanyou Wu, Xinyi Yang, Xinkang Hu, Chundu Wu

“…A parallel modelling strategy was implemented employing Gradient Boosting, Random Forest, and Ridge Regression, selecting the optimal algorithm per feature based on predictive performance. …”
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Remote Target High-Precision Global Geolocalization of UAV Based on Multimodal Visual Servo by Xuyang Zhou, Ruofei He, Wei Jia, Hongjuan Liu, Yuanchao Ma, Wei Sun

“…We design a step-convergent target geolocation optimization algorithm. By adjusting the step size and the scale factor of the cost function, we achieve fast accuracy convergence for different UAV reconnaissance modes, while maintaining the geolocation accuracy without divergence even when the laser ranging sensor is turned off for a short period. …”
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XSQ-Learning: Adaptive Similarity Thresholds for Accelerated and Stable Q-Learning by Ansel Y. Rodríguez González, Roberto E. López Díaz, Shender M. Ávila Sansores, María G. Sánchez Cervantes

“…Reinforcement Learning (RL) enables agents to learn optimal policies through environment interaction, with Q-learning being a fundamental algorithm for Markov Decision Processes (MDPs). …”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…To address this, we propose the IASL-YOLO algorithm, which optimizes the YOLOv8s model to enhance detection accuracy and lightweight efficiency. …”
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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

“…The paper provides an in-depth review of the literature, examining not only ML techniques but also optimization algorithms, evaluation methods, explainability techniques, and emerging technologies. …”
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