Results 1 to 10 of about 2,180 (133)
Classification of coal-bearing strata abnormal structure based on POA–ELM [PDF]
, 2023 In order to identify and classify the abnormal structures in coal-bearing strata more accurately, a POA−ELM model based on the pelican optimization algorithm (POA) and the extreme learning machine (ELM) is proposed.
Jie GAO +4 more
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Rapid detection of moisture content of pineapple based on near infrared spectroscopy and SSA-RELM [PDF]
, 2023 Objective: A method for a fast and non-destructive detection of pineapple moisture content was established. Methods: A novel detection model of pineapple moisture content was proposed based on continuous projection feature wavelength selection and ...
LI Zhiqiang, ZHAO Qian, ZHAO Yanli
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Review on autoencoder and its application [PDF]
, 2021 As a typical deep unsupervised learning model, autoencoder can automatically learn effective abstract features from unlabeled samples.In recent years, autoencoder has been widely used in target recognition, intrusion detection, fault diagnosis and many ...
Jie LAI +4 more
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Target Tracking System Constructed by ELM-AE and Transfer Representation Learning [PDF]
, 2022 In the target tracking algorithm, the feature model’s ability to quickly learn image features and the ability to adapt to changes in target features during tracking has always been one of the main research directions of target tracking algorithms.
YANG Zheng, DENG Zhaohong, LUO Xiaoqing, GU Xin, WANG Shitong
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Parameter identification of a shell transfer arm using FDA and optimized ELM [PDF]
, 2017 To identify the unmeasurable parameters of a shell transfer arm, a virtual prototype of the shell transfer arm was built, and the built virtual prototype is regard as the source of the sample data.
HOU Bao-lin, ZHAO Qiang-qiang
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RGB-D object recognition algorithm based on improved double stream convolution recursive neural network [PDF]
, 2021 An algorithm (Re-CRNN) of image processing is proposed using RGB-D object recognition, which is improved based on a double stream convolutional recursive neural network, in order to improve the accuracy of object recognition.
Lazovik, Alexander +4 more
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全球能源互联网, 2019 光伏发电具有随机性、间歇性等特点，其大规模接入配电网给电网安全、经济运行带来挑战。储能是解决高渗透率光伏输出功率波动的有效手段。为此，提出一种结合相邻时段实时预测误差和极限学习机的光伏功率区间预测方法；提出一种分布式储能的区间离散SOC均衡控制策略。在此基础上，构建了包含储能运行成本、系统网损和电压偏差的多目标区间优化运行模型。应用区间泰勒展开的仿射算法将不确定区间潮流问题转化为确定性代数方程组实现潮流计算，同时依据电压-功率和网损-功率灵敏度矩阵重新表达目标函数，采用线性规划法求解。最后 ...
袁晓冬 +4 more
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Zhongguo cuzhong zazhi, 2023 目的 开发基于机器学习算法的缺血性卒中患者院内复发风险的预测模型，并进行外部验证，为相关研究提供借鉴。 方法 开发队列为中国卒中联盟（China Stroke Center Alliance，CSCA）研究队列，将此队列中的缺血性卒中患者按照8∶2随机划分为训练集和内部验证集。验证队列为第3次中国国家卒中登记（the third China national stroke registry，CNSR-Ⅲ）研究队列。基于指南、文献回顾，确定备选预测因子，然后采用拉索（least absolute ...
陈思玎1，姜英玉1，王春娟2，杨昕2，李子孝2，姜勇1，3，王拥军1，4，5，谷鸿秋1，2
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Developmental Medicine &Child Neurology, Volume 61, Issue 3, Page E1-E35, March 2019., 2019 目的 本国际临床指南由欧洲残疾儿童学会（the European Academy of Childhood Disability，EACD）牵头制定，旨在解决发育性协调障碍（developmental coordination disorder，DCD）的定义、诊断、评估、干预以及与社会心理方面的临床应用关键问题。 方法 本指南针对五个领域的关键问题，通过文献综述和专家团队的正式讨论达成共识。为保证指南的循证基础，以“机制”、“评估”和“干预”为检索词, 对2012年更新以来提出的最新建议以及新增的“社会心理问题”和“青少年/成人”为检索词进行检索。根据牛津大学循证医学中心证据等级 (证据水平 [level of evidence, LOE]1–4) 将结果进行分类，最终转化为指南建议。并由国际 ...
Jing Hua +6 more
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Zhongguo youzhi, 2023 为实现山茶油与3种常见食用植物油(菜籽油、大豆油和玉米油)的区分，制备可视化传感器阵列，采用嗅觉可视化技术对4种不同种类的食用植物油进行分类识别。采用主成分分析(PCA)对4种油样的特征数据进行降维，然后将降维后的数据导入K近邻(KNN)、极限学习机(ELM)、支持向量机(SVM) 3种分类模型中进行模型参数优化，对比了3种分类模型的分类结果。结果表明：建立的SVM分类模型性能最优，当输入主成分向量数为7、c=1.741 1、g=4.549 8时，SVM分类模型的测试集分类识别准确率为95.8 ...
杨干， 李大鹏，文韬，蒋涵，龚中良 YANG Gan, LI Dapeng, WEN Tao, JIANG Han, GONG Zhongliang
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