Forest Non-Lambertian Modeling Error Correction Based on DART by Dacheng Li, Hui Jia, Yue Lv, Kaiqi Nan, Shengzhen Zhang

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Experiments on software error prediction using Decision Tree and Random Forest algorithms by Ilona Bluemke, Paweł Borsukiewicz

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Temporal pattern in basal area prediction error of a growth model for Quebec’s temperate forest by Hugues Power, Isabelle Auger

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Evaluation of Radiometric and Polarimetric Errors in the LT-1A Satellite Data Based on Tropical Forests in the Amazon by Lei SHI, Weidong SUN, Le YANG, Jie YANG, Lingli ZHAO, Pingxiang LI, Yabo LIU

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Incorporating Forest Mapping-Related Uncertainty into the Error Propagation of Wall-to-Wall Biomass Maps: A General Approach for Large and Small Areas by Hassan C. David, Alexander C. Vibrans, Rorai P. Martins-Neto, Ana Paula Dalla Corte, Sylvio Péllico Netto

“…The sources of uncertainty in wall-to-wall AGB maps propagate from the tree to pixel, but uncertainty due to forest cover mapping is rarely incorporated into the error propagation process. …”
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Implementing GitHub Actions continuous integration to reduce error rates in ecological data collection by Albert Y. Kim, Valentine Herrmann, Ross Barreto, Brianna Calkins, Erika Gonzalez‐Akre, Daniel J. Johnson, Jennifer A. Jordan, Lukas Magee, Ian R. McGregor, Nicolle Montero, Karl Novak, Teagan Rogers, Jessica Shue, Kristina J. Anderson‐Teixeira

“…Yet, data collection errors are common, and data analysis often lags far enough behind its collection that many errors can no longer be corrected, nor can anomalous observations be revisited. …”
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Retracted: An Automatic Pronunciation Error Detection and Correction Mechanism in English Teaching Based on an Improved Random Forest Model by Journal of Electrical and Computer Engineering

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Defect Detection and Error Source Tracing in Laser Marking of Silicon Wafers with Machine Learning by Hsiao-Chung Wang, Teng-To Yu, Wen-Fei Peng

Subjects: “…random forest…”
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Allometric Equations for Aboveground Biomass Estimation in Natural Forest Trees: Generalized or Species-Specific? by Yuxin Shang, Yutong Xia, Xiaodie Ran, Xiao Zheng, Hui Ding, Yanming Fang

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Source Code Error Understanding Using BERT for Multi-Label Classification by Md Faizul Ibne Amin, Yutaka Watanobe, Md Mostafizer Rahman, Atsushi Shirafuji

“…To aid in understanding and classifying these errors, we propose a multi-label error classification approach for source code using fine-tuned BERT models (BERT_Uncased and BERT_Cased). …”
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Towards an effective in-situ biodiversity assessment in European forests by Sabina Burrascano, Lucas Chojnacki, Lorenzo Balducci, Francesco Chianucci, Elena Haeler, Sebastian Kepfer-Rojas, Yoan Paillet, Rafael B. de Andrade, Steffen Boch, Pallieter De Smedt, Markus Fischer, Itziar Garcia Mijangos, Jacob Heilmann-Clausen, Jeňýk Hofmeister, Jan Hošek, Daniel Kozák, Gergely Kutszegi, Thibault Lachat, Martin Mikoláš, Ferenc Samu, Sonia Ravera, Peter Schall, Tommaso Sitzia, Miroslav Svoboda, Giovanni Trentanovi, Mariana Ujhazyova, Kris Vandekerkhove, Flóra Tinya, Peter Odor

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Improving extraction of forest canopy height through reprocessing ICESat-2 ATLAS and GEDI data in sparsely forested plain regions by Ruoqi Wang, Yagang Lu, Dengsheng Lu, Guiying Li

Subjects: “…Forest canopy height…”
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The Influence of the Spatial Co-Registration Error on the Estimation of Growing Stock Volume Based on Airborne Laser Scanning Metrics by Marek Lisańczuk, Krzysztof Mitelsztedt, Krzysztof Stereńczak

“…One of them, which is related to the core aspect of this method, is the spatial co-registration error between ground measurements and RS data. This error arises mainly from the imperfection of the methods for positioning the sample plots under the forest canopy. …”
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Virtual fencing in remote boreal forests: performance of commercially available GPS collars for free-ranging cattle by Erik Versluijs, Morten Tofastrud, Anna Hessle, Robert Serrouya, Derek Scasta, Petter Wabakken, Barbara Zimmermann

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Utilizing Machine Learning Approach to Forecast Average Location Determination Errors in Wireless Sensor Networks by Zhihui Zhu, Meifang Zhu

Subjects: “…average localization error…”
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Evaluating the impact of field-measured tree height errors correction on aboveground biomass modeling using airborne laser scanning and GEDI datasets in Brazilian Amazonia by Nadeem Fareed, Izaya Numata

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A hybrid method for forest aboveground biomass estimation: fusion of individual tree- and area-based approaches over northeast China by Zhen Zhen, Xiang Li, Ye Ma, Yinghui Zhao, Xiaochun Wang

“…This study provides technical support for upscaling AGB estimation from individual tree to extensive forest and lays a solid foundation for precise forestry, sustainable forest management, and the attainment of carbon neutrality.…”
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Winter Wheat Yield Prediction and Influencing Factors Analysis Based on FourierGNN–Random Forest Combined Modeling by Jianqin Ma, Yijian Chen, Bifeng Cui, Yu Ding, Xiuping Hao, Yan Zhao, Junsheng Li, Xianrui Su

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How much timber from Norway spruce (Picea abies L.) is left on the harvesting site as treetops? A study on scaling and grading yields of harvesters by Jiří Dvořák, Marcel Štolc, Martin Jankovský, Pavel Natov, Arkadiusz Stańczykiewicz, Michal Allman, Andrej Liška

Subjects: “…Forest harvesting…”
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Forest attribute maps: a support for small area estimation of forest disturbances by Ankit Sagar, Cédric Vega, Olivier Bouriaud, Christian Piedallu, Jean-Pierre Renaud

“…Abstract Key Message Forest attribute maps generated using national forest inventory and remote sensing data can be used to quantify forest attributes (i.e., growing stock volume, basal area) affected by disturbance events (like bark-beetle induced damage) through small area estimation techniques. …”
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