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1. 发明申请

WO2023085560A1 제약 강화 학습이 적용된 이산 산업 제조 시스템의 수요반응 관리 방법 审中-公开
公开(公告)号：WO2023085560A1
公开(公告)日：2023-05-19
申请号：PCT/KR2022/012145
申请日：2022-08-12
申请人： 네스트필드(주)
发明人： 홍승호 , 장시옹펑
IPC分类号： G06Q50/06 , G06F17/15 , H02J3/14
摘要： 수요반응(DR)은 전력망의 안정성과 재정적 효율성을 향상시키는 효과적인 방법으로 인정받고 있다. 1차 소비자로서 산업 부문에 대한 DR 구현이 시급하다. 본 발명은 에너지 비용과 일일 생산 목표를 동시에 고려하여 산업용 이산 제조 시스템을 위한 새로운 산업용 가격 기반 DR 관리 접근 방식을 제안한다. 이를 달성하기 위해 이산 제조 시스템은 CMDP(Constrained Markov Decision Process)로 모델링되고, CRL(Constrained Reinforcement Learning) 알고리즘을 채택하여 이산 제조 시스템에 대한 비용 효율적인 운영 전략을 결정한다. 본 발명에 따른 방법의 성능을 검증하기 위해 실제 리튬 이온 배터리 조립 시스템을 사용하여 시뮬레이션을 수행하였고, 그 평가 결과는 본 발명에 따른 방법이 생산 목표를 위반하지 않고 에너지 비용을 최적화할 수 있음을 보여 주었다.

2. 发明申请

WO2022237090A1 一种同步确定二极管边界电场与电流密度的方法审中-公开
公开(公告)号：WO2022237090A1
公开(公告)日：2022-11-17
申请号：PCT/CN2021/127813
申请日：2021-11-01
申请人：华南理工大学
发明人：朱映彬 , 廖美焱 , 姚若河 , 耿魁伟
IPC分类号： G06F30/20 , G06F17/15 , G06F17/11
摘要：本发明公开了一种同步确定二极管边界电场与电流密度的方法，包括以下步骤：一、给定两个电子电流密度初始值以及一个离子电流密度初始值；二、将电子电流密度初始值以及一个离子电流密度初始值代入泊松方程，获取对应的阴极边界电场值；三、预测电子电流密度值；四、基于预测的电子电流密度值，得到新的阴极边界电场值，判断新的阴极边界电场值是否满足所要求的阴极边界条件；五、给定新的离子电流密度值，执行步骤一到步骤四，得到两个阳极边界电场值；六、预测离子电流密度值；七、预测阳极边界电场值，判断预测的阳极边界电场值是否满足所要求的阳极边界条件；八、输出最终的电子和离子电流密度。

3. 发明申请

WO2022057054A1 一种卷积运算优化方法、系统、终端以及存储介质审中-公开
公开(公告)号：WO2022057054A1
公开(公告)日：2022-03-24
申请号：PCT/CN2020/127128
申请日：2020-11-06
申请人：深圳先进技术研究院
发明人：王峥 , 廖健 , 刘江佾
IPC分类号： G06F17/15
摘要：本申请涉及一种卷积运算优化方法、系统、终端以及存储介质。包括：将数据内存模块中的图像数据输入多线程数据缓存模块，并记录每个线程中图像数据的数据特征；当所有线程均填满图像数据时，分别对至少两个相邻线程的数据特征进行时空相似性分析，并当至少两个相邻线程的数据特征存在时空相似性时，过滤掉至少两个相邻线程中至少一个线程的图像数据，将过滤图像数据后的线程作为空闲线程重新缓存数据内存模块输入的图像数据，并在所有线程再次填满图像数据时重新进行时空相似性分析；根据缓存的图像数据进行卷积计算，并输出新的图像数据。本申请极大减少了实际卷积运算量，提高了数据复用性，降低网络整体计算时间，提升芯片性能。

4. 发明申请

WO2022038476A1 HYDROCARBON FLUID PROPERTIES PREDICTION USING MACHINE-LEARNING-BASED MODELS 审中-公开
公开(公告)号：WO2022038476A1
公开(公告)日：2022-02-24
申请号：PCT/IB2021/057475
申请日：2021-08-13
申请人： ABU DHABI NATIONAL OIL COMPANY , ABU DHABI COMPANY FOR ONSHORE PETROLEUM OPERATION LIMITED
发明人： GHORAYEB, Kassem , MAWLOD, Arwa Ahmed , MUSTAPHA, Hussein , MOHAN, Richard
IPC分类号： G06N20/20 , G06F17/15 , G06F17/18 , G06F16/215 , G06K9/62 , E21B49/08 , G01N33/28 , G06F16/26
摘要： A computer-implemented method (100) for predicting hydrocarbon fluid properties using machine-learning-based models is provided. The computer-implemented method comprises the step of receiving (101) a incomplete set of pressure-volume-temperature (PVT) data for hydrocarbon fluid samples from a PVT data base; reading (102) the incomplete set of PVT data by a reader module; transforming (103) the incomplete set of PVT data into a unified data structure by the reader module; selecting (104) items of the PVT data from the incomplete set of PVT data by the reader module; processing (105) the selected items of the PVT data by a correlating module to identify a plurality of correlations in the selected items of the PVT data based on one or more of the fluid properties of the hydrocarbon fluid samples; clustering (106), using of at least one of a plurality of clustering schemes, the selected items of the PVT data into a plurality of clusters by a clustering module; and performing (107) machine learning by a machine learning module on ones of the plurality of clusters to predict missing fluid properties in the incomplete set of PVT data and thus to obtain a complete set of PVT data. Further a computer-implemented method (200) for generating equations of state (EoS) for a plurality of hydrocarbon fluids is provided. The computer-implemented method comprises the step of delumping (201) pressure-volume- temperature (PVT) data for hydrocarbon fluid samples from a complete set of PVT data to one of a set of detailed fluid components, or to a common set of components and pseudo- components; lumping (202) the PVT data from the complete set of PVT data into a pre- defined set of components and pre-defined set of pseudo-components to generate a plurality of equation of state (EoS) models; generating (203) for the PVT samples on the PVT data set an EoS model using a same set of tuning parameters and thereby generating an EoS fluid model fingerprint for the hydrocarbon fluid samples; and associating (204) properties of the hydrocarbon fluid samples with the generated EoS fluid model fingerprint.

5. 发明申请

WO2022038416A1 SYSTEMS AND METHODS FOR PERFORMING NEURAL NETWORK OPERATIONS 审中-公开
公开(公告)号：WO2022038416A1
公开(公告)日：2022-02-24
申请号：PCT/IB2021/000573
申请日：2021-08-19
申请人： MOBILEYE VISION TECHNOLOGIES LTD. , AGAM, Oren
发明人： AGAM, Oren
IPC分类号： G06N3/08 , G06F17/15 , G06F17/16
摘要： A method for retrieving neural network coefficients may include executing neural network operations and storing, in at least one data memory, one or more intermediate results of the neural network operations. The method may also include retrieving, in an iterative manner, subsets of neural network coefficients related to a particular layer of a neural network associated with at least one of the neural network processors. Different ones of the neural network processors may use at least one of the subsets of the neural network coefficients. The retrieving the subsets of neural network coefficients may include caching the subsets in coefficient cache memory. At least some of the subsets may be cached in the coefficient cache memory for up to a first duration, and at least some of the intermediate results may be stored in the at least one data memory for a duration that exceeds the first duration.

6. 发明申请

WO2022007230A1 一种基于稀疏结构元素的数学形态学信号处理方法审中-公开
公开(公告)号：WO2022007230A1
公开(公告)日：2022-01-13
申请号：PCT/CN2020/122113
申请日：2020-10-20
申请人：华南理工大学
发明人：吴青华 , 张禄亮 , 黄鸣畅
IPC分类号： G06F17/15
摘要：本发明公开了一种基于稀疏结构元素的数学形态学信号处理方法，包括步骤：1）构建稀疏型结构元素；2）利用稀疏型结构元素对信号进行形态学滤波；3）对滤波结果使用多阶段稀疏算法或二阶段稀疏算法改善滤波效果；4）构建游离型结构元素和双极性形态学梯度；5）利用游离型结构元素对信号进行双极性形态学梯度提取。本发明可有效减少数学形态学信号处理的计算量和计算时间，并增强了形态学梯度的幅值。

7. 发明申请

WO2021196504A1 一种多维度航空器碰撞冲突风险评价系统审中-公开
公开(公告)号：WO2021196504A1
公开(公告)日：2021-10-07
申请号：PCT/CN2020/110222
申请日：2020-08-20
申请人：中国民用航空飞行学院
发明人：潘卫军 , 王思禹 , 陈宽明 , 张晓磊 , 王玄 , 陈佳炀 , 练婧瑜
IPC分类号： G08G5/04 , G08G5/00 , G06F17/15 , G08G5/003
摘要：民航航空器碰撞冲突预测领域的一种多维度航空器碰撞冲突风险评价系统，系统执行的步骤包括：S1，计算出三个维度上本航空器与其他航空器发生重叠的概率；S2，计算出本航空器三个维度的丢失间隔率；S3，求出本航空器三个维度方向上与其他航空器发生冲突碰撞的概率；S4，将本航空器三个维度方向上发生冲突碰撞的概率进行比较，得出最大概率以及最大概率对应的维度；S5，将求出的最大概率与安全标准进行差值计算，根据差值给出安全评价；实现了多维度的航空器碰撞冲突风险概率的计算。求出了碰撞冲突风险概率的最大值，并基于最大值，提出了对飞行器全面的安全评估的判断依据。

8. 发明申请

WO2021191704A1 MACHINE LEARNING BASED DATA MONITORING 审中-公开
公开(公告)号：WO2021191704A1
公开(公告)日：2021-09-30
申请号：PCT/IB2021/051533
申请日：2021-02-24
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION , IBM (CHINA) INVESTMENT COMPANY LTD. , IBM DEUTSCHLAND GMBH
发明人： BIGAJ, Rafal , CMIELOWSKI, Lukasz , SOBALA, Wojciech , ERAZMUS, Maksymilian
IPC分类号： G06N99/00 , G06N20/00 , G06F11/3409 , G06F17/15 , G06K9/6262
摘要： Overall performance metric of computer system may be determined for each bin of set of analysis bins. In case one or more bins of the set of analysis bins do not have at least a predefined minimum number of records, a new set of analysis bins may be redefined by joining analysis bins of the set of analysis bins. For each bin of the redefined set of bins a machine learning (ML) performance metric of the ML model may be computed. The ML performance metric may be estimated for the set of analysis bins using the ML performance metrics of the redefined bins. The computer system may be configured based on a correlation over the set of analysis bins between the computed overall performance metric and the ML performance metric.

9. 发明申请

WO2021172797A1 트랜스포즈드 콘볼루션 하드웨어 가속장치 审中-公开
公开(公告)号：WO2021172797A1
公开(公告)日：2021-09-02
申请号：PCT/KR2021/001814
申请日：2021-02-10
申请人： 오픈엣지테크놀로지 주식회사
发明人： 최정환
IPC分类号： G06N3/063 , G06N3/08 , G06F17/15
摘要： 입력 데이터 행렬에 커널 행렬로 트랜스포즈드 콘볼루션 연산하여 출력 데이터 행렬을 생성하기 위한 데이터를 생성하는 연산장치를 공개한다. 상기 연산장치는 상기 커널 행렬로부터 추출된 제1서브커널 행렬의 각 가중 요소값에 대응하는 단위연산부들로 이루어진 제1단위연산부 그룹으로서, 상기 제1단위연산부 그룹에 속한 상기 단위연산부들은 상기 제1서브커널 행렬의 인덱스 순서에 따라 서로 직렬로 연결되어 있는, 상기 제1단위연산부 그룹을 포함한다.

10. 发明申请

WO2021159605A1 一种雾化喷头出口旋转角度的优化方法审中-公开
公开(公告)号：WO2021159605A1
公开(公告)日：2021-08-19
申请号：PCT/CN2020/086576
申请日：2020-04-24
申请人：江苏大学
发明人：朱兴业 , 刘俊萍 , 袁寿其 , 亚历山大福尔朱尔 , 陆科骥
IPC分类号： B05B1/30 , G06F17/15
摘要：一种雾化喷头出口旋转角度的优化方法，雾化喷头包括喷芯和喷体，包括如下步骤：喷芯与喷体之间的出口间隙d＝0时，测量在额定工作压力下，雾化喷头的出口流量Q 0；通过改变喷芯与喷体之间的相位角度，使喷芯与喷体之间产生出口间隙，测量在额定工作压力下，雾化喷头在稳定工作状态出口流量为Q 1；计算雾化喷头的流量系数；根据期望的雾化喷头的出口流量Q 2和雾化喷头的流量系数，计算雾化喷头的出口间隙；根据喷芯与喷体的装配关系得出，改变喷芯与喷体之间的相位角度为a 2。该方法可以快捷的将出口旋转角度调节至合适的位置，用于实现雾化喷头喷洒时预期的出口流量。

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