Ngā hua rapu - Small sample data
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Classification of Leguminous Wood Species Based on Small Sample Hyperspectral Images
I whakaputaina 2025-06-01“…However, existing studies are still deficient in classification methods under small sample conditions. This paper uses hyperspectral image data and combines models such as support vector machine (SVM), random forest (RF), logistic regression (LR), and one-dimensional convolutional neural network (1-CNN). …”Leguminous wood occupies an important position in the market of cultural and high-end wood. Accurate identification and classification of its species is crucial for the development of the industry. However, existing studies are still deficient in classification methods under small sample conditions....
Whiwhi kuputuhi katoa
Tuhinga -
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Small-sample-data augmentation and transfer strategies for forest cover change monitoring
I whakaputaina 2025-09-01Ngā marau: Whiwhi kuputuhi katoaThe Qilian Mountains serves as a critical ecological barrier in northwest China, where the forest coverage strongly connected with the regional ecosystem stability, water conservation as well as climate change. However, a high resolution and accuracy of forest coverage data is still missing for this...
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Optimal Scheduling Strategy of Newly-Built Microgrid in Small Sample Data-Driven Mode
I whakaputaina 2025-06-01“…This reduces the domain distribution discrepancy in the data, and uses the rich operation data of power stations with similar output characteristics to predict the output of the target station, which overcomes the challenge of poor accuracy under the conditions of small samples. …”Newly built microgrids lack historical operation data, making it challenging to predict renewable power output accurately using conventional data-driven methods, which in turn affects the accuracy of scheduling plans. To address this problem, an optimal scheduling method for newly built microgrids i...
Whiwhi kuputuhi katoa
Tuhinga -
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A Small-Sample Scenario Optimization Scheduling Method Based on Multidimensional Data Expansion
I whakaputaina 2025-06-01Ngā marau: Whiwhi kuputuhi katoaCurrently, deep reinforcement learning has been widely applied to energy system optimization and scheduling, and the DRL method relies more heavily on historical data. The lack of historical operation data in new integrated energy systems leads to insufficient DRL training samples, which easily trig...
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The research on enhancing LA estimation accuracy across domains for small sample data based on data augmentation and data transfer integration optimization system
I whakaputaina 2025-12-01Ngā marau: “…Small sample data…”Context: The efficient and precise monitoring of rice leaf area (LA) is essential for variety selection and agricultural management. At present, LA estimation models based on high-throughput phenotyping technologies primarily depend on homogenized large sample datasets. These models encounter genera...
Whiwhi kuputuhi katoa
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A data-driven hybrid framework for voltage transformer ratio error prediction: Addressing challenges in complex power systems
I whakaputaina 2025-09-01“…Additionally, a Wasserstein Generative Adversarial Network (WGAN) generates fault samples, thereby enhancing the model’s ability to handle small sample conditions. …”The measurement accuracy of voltage transformers (VTs) is crucial for power system protection and trade fairness. However, the large-scale integration of renewable energy into the grid affects the transient performance of power systems, presenting significant challenges for the accurate measurement...
Whiwhi kuputuhi katoa
Tuhinga -
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Cross-Domain Feature Enhancement-Based Password Guessing Method for Small Samples
I whakaputaina 2025-07-01“…This paper introduces a small-sample password guessing technique that enhances cross-domain features. …”As a crucial component of account protection system evaluation and intrusion detection, the advancement of password guessing technology encounters challenges due to its reliance on password data. In password guessing research, there is a conflict between the traditional models’ need for large traini...
Whiwhi kuputuhi katoa
Tuhinga -
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Prediction of Propellant Electrostatic Sensitivity Based on Small-Sample Machine Learning Models
I whakaputaina 2025-07-01Whiwhi kuputuhi katoaHydroxyl-terminated-polybutadiene (HTPB)-based composite solid propellants are extensively used in aerospace and defense applications due to their high energy density, thermal stability, and processability. However, the presence of highly sensitive energetic components in their formulations leads to...
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TRENDS OF DEVELOPING AGRICULTURE AND SMALL AGRICULTURAL ENTERPRISES IN CONDITIONS OF NEO-INDUSTRIALIZATION AND ENHANCING PROCESSES OF INVESTMENT AND INNOVATION IN THIS SPHERE
I whakaputaina 2018-01-01Ngā marau: “…key formulas of estimating the sample observation on statistic data of farms…”Today’s agriculture is a complicated biotechnological and social-economic system, which consists of many interconnected elements. Agricultural production is characterized by high capital-intensity and power – intensity, as well as by high risk, due to this capital inflow from other types of econo...
Whiwhi kuputuhi katoa
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A transfer learning-based method for marine machinery diagnosis with small samples in noisy environments
I whakaputaina 2025-08-01Whiwhi kuputuhi katoaThe operating conditions of marine machinery are demanding, and their operational state significantly affects the safety of marine structures. Detecting faults is crucial for machinery health management and necessitates a highly precise diagnostic method. In this paper, we propose a fault diagnosis...
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Fault diagnosis method of mine hoist main bearing with small sample based on VAE-WGAN
I whakaputaina 2025-06-01“…However, the proportion of normal service and fault status in the monitoring data of the operation status of mine hoists is severely imbalanced, showing characteristics such as a large number of normal samples, a small number of fault samples, and insufficient label samples, resulting in unsatisfactory training results and low diagnostic accuracy of the main bearing fault model of mine hoists. …”As a key component of the hoist, the main bearing may deteriorate in performance and cause faults during long-term high-speed and heavy-duty service. Therefore, conducting fault diagnosis of the main bearing of the hoist is of great significance for ensuring the safe and efficient operation of the m...
Whiwhi kuputuhi katoa
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Regression-based leaf nitrogen concentration estimation of young Cephalotaxus hainanensis in small and imbalanced samples
I whakaputaina 2025-12-01“…The research employed an image processing workflow to extract color and texture features, combined with data preprocessing techniques such as natural logarithmic transformation, feature selection based on Least Absolute Shrinkage and Selection Operator (LASSO), and resampling methods, especially the application of the Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise (SMOGN) and Adaptive Synthetic combined with a relevance function for regression (ADASYNR) to address critical challenges associated with small and imbalanced samples in regression. …”Estimating leaf nitrogen concentration (LNC) is essential for effective plant nutrition management, yet conventional destructive methods are unsuitable for endangered tree species. This study used a non-destructive method that combines computer vision and machine learning to estimate the LNC in Ceph...
Whiwhi kuputuhi katoa
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Short-term wind power forecasting method for extreme cold wave conditions based on small sample segmentation
I whakaputaina 2025-09-01“…To address this issue, this paper proposes a segmented wind power forecasting method based on the generation of small sample cold wave data. First, the characteristics of wind power fluctuations during cold wave conditions are analyzed. …”With the intensification of global warming, the frequency of extreme weather events has increased, drawing significant attention from countries worldwide to the deteriorating environmental conditions. In this context, nations have accelerated the transition of their energy structures to reduce depen...
Whiwhi kuputuhi katoa
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Protocol to quantify total intracellular magnesium in small samples using a fluorescent plate reader and fluorescent dye
I whakaputaina 2025-09-01Whiwhi kuputuhi katoaSummary: Assessing total magnesium (Mg) becomes challenging when cell quantities are minimal. Here, we present a protocol to quantify total intracellular Mg in samples with as few as several thousand cells using a fluorescent plate reader and the fluorescent dye diaza-18-crown-6-hydroxyquinoline-5 (...
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Transfer Learning-Based Interpretable Soil Lead Prediction in the Gejiu Mining Area, Yunnan
I whakaputaina 2025-07-01“…Accurate prediction of soil lead (Pb) content in small sample scenarios is often limited by data scarcity and variability in soil properties, with traditional spectral modeling methods yielding suboptimal precision. …”Accurate prediction of soil lead (Pb) content in small sample scenarios is often limited by data scarcity and variability in soil properties, with traditional spectral modeling methods yielding suboptimal precision. To address this, we propose a transfer learning-based framework integrated with SHAP...
Whiwhi kuputuhi katoa
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Research on Improved YOLO11 for Detecting Small Targets in Sonar Images Based on Data Enhancement
I whakaputaina 2025-06-01“…Lastly, we employ a hybrid training strategy that combines pre-training with ADA-StyleGAN3-generated data and transfer learning with real data to alleviate the problem of insufficient training samples. …”Existing sonar target detection methods suffer from low efficiency and accuracy due to sparse target features and significant noise interference in sonar images. To address this, we introduce SFE-YOLO, an improved model based on YOLOv11. We replace the original detection head with an FSAFFHead modul...
Whiwhi kuputuhi katoa
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Boosting Crowdsourced Annotation Accuracy: Small Loss Filtering and Augmentation-Driven Training
I whakaputaina 2024-01-01“…SLNC first filters the crowdsourced data, leveraging the characteristic of neural networks to preferentially fits clean samples, thereby obtaining relatively clean and noisy sets. …”Crowdsourcing platforms provide an efficient and cost-effective means to acquire the extensive labeled data necessary for supervised learning. However, the labels provided by untrained crowdsourcing workers often contain a considerable amount of noise. Although the application of ground truth infere...
Whiwhi kuputuhi katoa
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THE PGR NETWORKS IN FRANCE: COLLABORATION OF USERS AND THE GENETIC RESOURCE CENTRE ON SMALL GRAIN CEREALS
I whakaputaina 2014-12-01“…All these data obtained from the French small grain cereal Network will be progressively available through the INRA Genetic Resource Website (http://urgi.versailles.inra.fr/siregal/siregal/welcome.do).…”Plant genetic resources (PGR) have been used in breeding programs for many decades to produce modern varieties by introducing genes of interest, in particular, resistance genes. Nevertheless, these resources remain underestimated if we focus on abiotic stress tolerance or new agricultural techniques...
Whiwhi kuputuhi katoa
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Prediction of Survival in Patients With Esophageal Cancer After Immunotherapy Based on Small-Size Follow-Up Data
I whakaputaina 2024-01-01“…The model proves efficient in guiding clinical decisions, especially in scenarios with small-size follow-up data.…”Esophageal cancer (EC) poses a significant health concern, particularly among the elderly, warranting effective treatment strategies. While immunotherapy holds promise in activating the immune response against tumors, its specific impact and associated reactions in EC patients remain uncertain. Prec...
Whiwhi kuputuhi katoa
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