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Sampling design plays an important role in soil survey and soil mapping. Conditioned Latin hypercube sampling (cLHS) has been proven as an efficient sampling strategy and used widely in digital soil m...
The current mainstream approach of using manual measurements and visual inspections for crop lodging detection is inefficient, time-consuming, and subjective. An innovative method for wheat lodging de...
The development of new methods for estimating precise forest structure parameters is essential for the quantitative evaluation of forest resources. Conventional use of satellite image data, increasing...
In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality paramete...
Precise coastal shoreline mapping is essential for monitoring changes in erosion rates, surface hydrology, and ecosystem structure and function. Monitoring water bodies in the Arctic National Wildlife...
Accurate land use and cover data are essential for effective land-use planning, hydrological modeling, and policy development. Since the Okavango Delta is a transboundary Ramsar site, managing natural...
Previous wildfire risk assessments have problems such as subjectivity of weight allocation and the linearization of statistical models, resulting in generally low robustness and low generalization abi...
苏州大学计算机科学与技术学院杨壮副教授撰写的论文“Improved Powered Stochastic Optimization Algorithms for Large-Scale Machine Learning”在机器学习顶级期刊Journal of Machine Learning Research(JMLR)上在线发表,杨壮副教授为该论文的唯一作者,苏州大学计算机科学与技术学院为该论文...
Solvents are widely used in chemical processes. The use of efficient model-based solvent selection techniques is an option worth considering for rapid identification of candidates with better economic...
转录因子(TF)在基因表达调控中发挥了重要作用。鉴定转录因子的靶基因或与靶基因启动子结合的转录因子对于解析转录因子-靶基因模块的生物学功能和调控网络至关重要。2023年6月15日,作物生物信息学课题组在Plant Physiology发表了题为“RiceTFtarget: A Rice Transcription Factor-Target Prediction Server Based on C...
Machine learning (ML) programs computers to learn the way we do—through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big da...
本报告介绍我们近期的两项工作。(1) 求解PDE的PINN方法在处理时间发展方程时往往遇到难以收敛的困难。我们发展了时间方向的预训练PINN方法及自适应步长方法,解决了收敛性困难,使PDE求解精度能够得到系统性提高。我们在一系列时间发展方程上获得了比文献报道更精确的训练结果。(2) 辐射调源问题是一个典型的反问题,要求调整辐射输运方程的边条件(源),使解满足特定设计目标。我们针对辐射输运方程的时序...
Nonlinear dynamics play a prominent role in many domains and are notoriously difficult to solve. Whereas previous quantum algorithms for general nonlinear equations have been severely limited due to t...
Learning to grow machine-learning models(图)     机器学习  LiGO技术  AI应用程序       font style='font-size:12px;'> 2023/6/20
It’s no secret that OpenAI’s ChatGPT has some incredible capabilities — for instance, the chatbot can write poetry that resembles Shakespearean sonnets or debug code for a computer program. These abil...
2023年2月25日,农学院智慧农业团队在《Science of The Total Environment》期刊发表了题为“Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed ...

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