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Developmental Medicine &Child Neurology, Volume 63, Issue 8, Page e1-e4, August 2021., 2021 目的 探討全基因體定序 (WGS) 對兒童神經疾病的診斷率及治療影響。 方法 從 2016 年 1 月至 2019 年 12 月, 使用全基因體定序對疑似患有遺傳性神經疾病的兒科病人進行評估。符合條件的病人依其臨床表現型分為四組: 神經發展障礙病人、癲癇病人、神經肌肉疾病病人及運動障礙病人。我們描述全基因體定序的診斷率及經全基因體定序確診後對病人治療的影響。 結果 共有 214 例病人 (男性 128 例, 女性 86 例) 接受了全基因體定序檢測, 病人平均 (SD) 發病年齡為 13.8 (27.6) 個月, 範圍為 1 天至 15 年 5 個月, 接受全基因體定序檢測的平均 (SD) 年齡為 71.7 (58.9) 個月, 範圍從 8 天到 18 歲。 43.9 ...
李 秀芬, 遲景 上, 蔡 啟仁
wiley +1 more source
Journal of Mathematics, Volume 2021, Issue 1, 2021., 2021 Fractional order research has interdisciplinary characteristics and has been widely used in the field of natural sciences. Therefore, fractional order research has become an important area of concern for scholars. This paper used 2854 literatures collected from China National Knowledge Infrastructure (CNKI) database from 2001 to 2020 as the data source
Yunfei Yang +4 more
wiley +1 more source
Multi-Task and Multi-Step Computation Offloading in Ultra-dense IoT Networks [PDF]
, 2022 With the rapid development of Internet of Things(IoT),various IoT mobile devices(IMDs) need to process more and more computing-intensive and delay-sensitive tasks,which puts forward new challenges for the mobile edge networks.To address these challenges ...
ZHOU Tian-qing, YUE Ya-li
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Zhejiang Daxue xuebao. Lixue ban, 2018 针对粒子群算法容易陷入局部最优解的问题，提出了一种基于动态分级和邻域反向学习的改进粒子群算法.该算法通过构建动态分级机制，将种群中的粒子动态地划分成3个等级，对不同等级内的粒子采取不同的扰动行为，使得粒子在增强种群多样性的同时保持向全局最优方向进化；采用粒子智能更新方式，提高了粒子的搜索能力；引入动态邻域反向学习点建立全局搜索策略，促使种群快速寻优.最后，利用多种典型测试函数对该算法进行仿真实验，结果表明，与其他几种优化算法相比，本算法具有较好的收敛性和稳定性.
RENYanzhi(任燕芝)
doaj +1 more source
Zhejiang Daxue xuebao. Lixue ban, 2016 为提高粒子群算法的收敛速度和优化性能，避免陷入局部最优，提出了一种基于动态学习因子和共享适应度函数的改进粒子群算法.在惯性权重w随着迭代次数非线性减少而动态调整学习因子的基础上，引入共享适应度函数.当算法未达到终止条件而收敛时，利用粒子和最优解间距离挑选一批粒子重新初始化形成新群体，并用共享适应度函数对新群体进行评价，新旧2个群体分别追随自己的局部最优解直至迭代结束.对4个典型多峰复杂函数的测试结果表明，该改进算法不仅加快了寻得最优解的速度，而且提高了粒子群算法全局收敛的性能.
TANYifeng(谭熠峰) +2 more
doaj +1 more source
大数据, 2022 提出基于粒子群优化特征选择（PSOFS）算法和TSK（Takagi-Sugeno-Kang）模糊系统的心电信号分类模型，即基于PSOFS和TSK的并行集成模糊神经网络（PE-PT-FN），用于心电图预测。首先对训练集中的各类样本进行随机放回抽样，然后将抽样得到的样本合并在一起，再独立且并行地通过PSOFS算法进行特征选择。PSOFS算法中不同的位置表示不同的特征子集，初始位置随机的粒子经过多次迭代收敛至最佳位置。每个子集得到一个特征子集用于并行训练多组独立的小型TSK模糊神经网络（TSK-FNN ...
李鑫辉, 申情, 张雄涛
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PSO based task scheduling for medical big data [PDF]
, 2014 How to select a suitable task scheduling strategy to accomplish the task of medical data query in scheduling and allocation inside each hospital is a important problem demanded to be dealt with in medical big data processing.In order to content the ...
Chao HU, Jun PENG, Wen-tao YU
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Clustering routing protocol based on improved PSO algorithm in WSN [PDF]
, 2019 Aiming at the problem that the location distribution of cluster head nodes filtered by wireless sensor network clustering routing protocol was unbalanced and the data transmission path of forwarding nodes was unreasonable,which would increase the energy ...
Chuyun ZHANG +3 more
core +1 more source
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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Inverse Kinematics Obstacle Avoidance Solution for Industrial Robot Based on Quaternion - 基于四元数的工业机器人逆运动学避障求解 [PDF]
, 2022 With the development of artificial intelligence technology, industrial robots are widely used in work scenarios such as gripping and handling. However, due to the complex inverse kinematics solution and the existence of multiple solutions for poses, the ...
Dong, Gui-rong +5 more
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