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Solicitudes publicadas en los últimos 360 días / Applications published in the last 360 days



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METHOD AND SYSTEM FOR ANALYZING INTERNET OF THINGS (IoT) DATA IN REAL-TIME AND PROVIDING PREDICTIONS

NºPublicación: US2020090070A1 19/03/2020

Solicitante:

WIPRO LTD [IN]

Resumen de: US2020090070A1

This disclosure relates to method and system for analyzing IoT data in real-time and predicting future events. In one embodiment, the method may include acquiring the real-time IoT data corresponding to one or more IoT devices, and building a predictive model based on the real-time IoT data. The predictive model may include a machine learning algorithm that generates an output parameter representing a future event based on a set of input parameters derived from the real-time IoT data. The predictive model may be built by training the predictive model for one or more explanatory input parameters and an expected output parameter. The method may further include predicting the future event based on the real-time IoT data using the predictive model, determining a deviation between the future event and an actual event, and tuning the predictive model based on the deviation.

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CIRCADIAN PHASE ESTIMATION, MODELING AND CONTROL

NºPublicación: US2020090781A1 19/03/2020

Solicitante:

RENSSELAER POLYTECH INST [US]

US_2015186594_A1

Resumen de: US2020090781A1

Method, system and computer program product are provided for estimating a circadian phase of a subject by: obtaining a sensed biological signal for the subject; and using, by one or more processors, adaptive frequency tracking to adaptively estimate the circadian phase of the subject from the sensed biological signal. Circadian phase estimation may be accelerated by providing a feedback loop for the adaptive frequency tracking, which utilizes, in part, a circadian phase model in automatically ascertaining a phase correction for the adaptive frequency tracking. The circadian phase estimation may be used in automatically constructing a light-based circadian rhythm model for the subject using a linear parameter-varying (LPV) formulation, and once constructed, the circadian rhythm model for the subject may be used to provide light-based circadian rhythm regulation.

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SYSTEMS AND METHODS FOR MATCHING ELECTRONIC ACTIVITIES TO RECORD OBJECTS USING FEEDBACK BASED MATCH POLICIES

NºPublicación: US2020089682A1 19/03/2020

Solicitante:

PEOPLE AI INC [US]

US_2020089681_A1

Resumen de: US2020089682A1

Systems and methods for matching electronic activities to record objects using feedback based match policies can include accessing a plurality of electronic activities and record objects. The systems and method can include identifying candidate record objects by applying a matching model. The systems and methods can include selecting a record object based on a match score. The systems and methods can include configuring the matching model in a first configuration responsive to a first feedback type or configuring the matching model in a second configuration responsive to a second feedback type.

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SYSTEMS AND METHODS FOR DETERMINING THE SHAREABILITY OF VALUES OF NODE PROFILES

NºPublicación: US2020089681A1 19/03/2020

Solicitante:

PEOPLE AI INC [US]

US_2020089682_A1

Resumen de: US2020089681A1

The present disclosure relates to determining the shareability of values of node profiles. Record objects and electronic activities of a system of record corresponding to a data source provider may be accessed. Each record object may correspond to a record object type and have one or more object field-value pairs. Node profiles may be maintained. Values of fields corresponding to a predetermined type of field including fewer than a predetermined threshold number of data source providers may be identified. A restriction tag used to restrict populating other node profiles may be generated. Provision of the value with a second data source provider may be restricted.

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FUZZY HASH ALGORITHMS TO CALCULATE FILE SIMILARITY

NºPublicación: US2020073959A1 05/03/2020

Solicitante:

MCAFEE LLC [US]

Resumen de: US2020073959A1

Methods, apparatus, systems and articles of manufacture to classify a first file are disclosed herein. Example apparatus include a feature hash generator to generate respective sets of one or more feature hashes for respective features of the first file. The number of the one or more feature hashes to be generated is based on an ability of the feature to distinguish the first file from a second file. The apparatus also includes a bit setter to set respective bits of a first fuzzy hash value based on respective ones of the one or more feature hashes, a classifier to assign the first file to a class associated with a second file based on a similarity between the first fuzzy hash value and a second fuzzy hash value for a second file.

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Fano-Based Information Theoretic Method (FBIT) for Design and Optimization of Nonlinear Systems

NºPublicación: US2020074339A1 05/03/2020

Solicitante:

MALAS JOHN A [US]
RYAN PATRICIA A [US]
CORTESE JOHN A [US]
U S GOVERNMENT AS REPRESENTED BY SECRETARY OF THE AIR FORCE [US]

Resumen de: US2020074339A1

The present disclosure includes theoretical models and methods for identifying and quantifying information loss in a system due to uncertainty and analyzing the impact on the reliability of system performance. These models and methods join Fano's equality with the Data Processing Inequality in a Markovian channel construct in order to characterize information flow within a multi-component nonlinear system and allow the determination of risk and characterization of system performance upper bounds based on the information loss attributed to each component. The present disclosure additionally includes methods for estimating the sampling requirements and for relating sampling uncertainty to sensing uncertainty. The present disclosure further includes methods for determining the optimal design of components of a nonlinear system in order to minimize information loss, while maximizing information flow and mutual information.

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一种基于模糊层次分析法的道路选线方法

NºPublicación: CN110826792A 21/02/2020

Solicitante:

莆田学院

Resumen de: CN110826792A

一种基于模糊层次分析法的道路选线方法,本发明通过影响因素集合的定量化、确定权重矩阵、求取权重矩阵的最大特征值对应的特征向量、特征向量归一化作为权向量、一致性检验、获取稳定性系数、根据实际情况选择串联或者并联路线、结合获取稳定性系数及现场资料确定P,T,P,T的值、分别调用模型计算、计算所有路线步骤获取最佳路径。地震发生时,导致岩土体失稳,救援路线被挡,时间即是生命,通过本发明能选择一条最佳的救援之道,能为救援争取时间。

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基于模糊预测的网络可疑资产识别方法

NºPublicación: CN110830467A 21/02/2020

Solicitante:

中国人民解放军战略支援部队信息工程大学网络通信与安全紫金山实验室

Resumen de: CN110830467A

本发明属于网路安全领域,特别涉及一种基于模糊预测的网络可疑资产识别方法,包含步骤1,扫描目标网段,获取资产信息、开放的端口信息和资产系统版本信息,输出已知资产、未知资产的详细参数清单;步骤2,异常监控模块负责监控资产清单中的指标变化;步骤3,根据步骤2获取的资产清单中参数的历史数据和实时数据、异常次数和异常数据,结合模糊预测信任模型,计算出资产的信任值;步骤4,对资产的信任值进行分析,识别出可疑资产。本发明以模糊预测算法的形式线性刻画资产的表现,减少预警的误报率。

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一种多能源协调优化运行评价方法

NºPublicación: CN110826868A 21/02/2020

Solicitante:

广东电网有限责任公司广东电网有限责任公司珠海供电局

Resumen de: CN110826868A

本发明涉及能源优化的技术领域,更具体地,涉及一种多能源协调优化运行评价方法,包括以下步骤:S10.建立包括一级指标和二级指标的风险指标评估体系;S20.运用模糊层次分析法,对一级指标采用G1群组进行主观评估;S30.运用模糊层次分析法,对二级指标采用熵权法进行客观评估;S40.建立多能源协调优化运行评估模型、算例实现对评价因素的风险预估。本发明通过一级指标的主观评估、二级指标的客观评估以及最后综合赋权完成区域能源互联网多源优化能效综合评价模型的搭建,给出了风险评估各评价因素的权重系数及计算过程。本发明兼顾了多能源评估各因素间存在的模糊性和层次性,并通过专家经验打分表明各因素在系统中表现,使系统风险评估更具客观性。

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LEARNING SPARSITY-CONSTRAINED GAUSSIAN GRAPHICAL MODELS IN ANOMALY DETECTION

NºPublicación: US2020057956A1 20/02/2020

Solicitante:

IBM [US]

Resumen de: US2020057956A1

A first dependency graph is constructed based on a first data set by solving an objective function constrained with a maximum number of non-zeros and formulated with a regularization term comprising a quadratic penalty to control sparsity. The quadratic penalty in constructing the second dependency graph is determined as a function of the first data set. A second dependency graph is constructed based on a second data set by solving the objective function constrained with the maximum number of non-zeros and formulated with the regularization term comprising a quadratic penalty. The quadratic penalty in constructing the second dependency graph is determined as a function of the first data set and the second data set. An anomaly score is determined for each of a plurality of sensors based on comparing the first dependency graph and the second dependency graph, nodes of which represent sensors.

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SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT FOR MACHINE-LEARNING-BASED TRAFFIC PREDICTION

NºPublicación: EP3610226A1 19/02/2020

Solicitante:

VISA INT SERVICE ASS [US]

US_2020033151_A1

Resumen de: WO2019245555A1

Described are a system, method, and computer program product for machine-learning-based traffic prediction. The method includes receiving historic transaction data including a plurality of transactions. The method also includes generating, using a machine-learning classification model, a transportation categorization for at least one consumer. The method further includes receiving at least one message associated with at least one transaction, identifying at least one geographic node of activity in the region, and generating an estimate of traffic intensity for the at least one geographic node of activity. The method further includes comparing the estimate of traffic intensity to a threshold of traffic intensity and, in response to determining that the estimate of traffic intensity satisfies the threshold: generating a communication configured to cause at least one navigation device to modify a navigation route; and communicating the communication to the at least one navigation device.

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一种基于二元联系数的犹豫模糊多属性决策方法

NºPublicación: CN110796255A 14/02/2020

Solicitante:

湖州师范学院

Resumen de: CN110796255A

本发明提出了一种基于二元联系数的犹豫模糊多属性决策方法,通过把犹豫模糊决策值转换成二元联系数A+Bi,建立基于二元联系数的犹豫模糊多属性决策模型,借助二元联系数中i取不同值作m个方案在犹豫模糊环境下的优劣排序分析,配合二元联系数模的计算确定最优方案,根据不同排序给出不同条件下的决策建议。最终得到更为客观合理的最优备选方案及其他方案的优劣排序。该基于二元联系数的犹豫模糊多属性决策模型具有一定的通用性,不仅能客观确定出犹豫模糊性对m个方案排序影响条件下的最优方案,还能包容同一个犹豫模糊决策问题用其他方法的结果,有利于决策者根据不同的犹豫模糊条件做出针对性决策。

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MAPPING DATA SOURCES TO STORAGE DEVICES BASED ON FUZZY LOGIC-BASED CLASSIFICATIONS

NºPublicación: US2020050372A1 13/02/2020

Solicitante:

ENTIT SOFTWARE LLC [US]

Resumen de: US2020050372A1

A technique includes, for each storage device of a plurality of storage devices, applying, by a processor, fuzzy logic to assign the plurality of storage devices to respective storage classes based on the weights that are assigned to the plurality of storage devices. The technique includes assigning, by the processor, weights to attributes of a data source. In response to an operation to backup data of the data source, mapping, by the processor, the data source to a given storage device based on the weights that are assigned to the attributes of the data source and the storage class that is associated with the given storage device.

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SYSTEMS AND METHODS FOR PROVIDING FLEXIBLE, MULTI-CAPACITY MODELS FOR USE OF DEEP NEURAL NETWORKS IN MOBILE DEVICES

NºPublicación: WO2020033898A1 13/02/2020

Solicitante:

UNIV MICHIGAN STATE [US]

Resumen de: WO2020033898A1

Systems and methods are disclosed which allow mobile devices, and other resource constrained applications, to more efficiently and effectively utilize deep learning neural networks using only (or primarily) local resources. These systems and methods take the dynamics of runtime resources into account to enable resource-aware, multi-tenant on-device deep learning for artificial intelligence functions for use in tasks like mobile vision systems. The multi-capacity framework enables deep learning models to offer flexible resource-accuracy trade-offs and other similar balancing of performance and resources consumed. At runtime, various systems disclosed herein may dynamically select the optimal resource-accuracy trade-off for each deep learning model to fit the model's resource demand to the system's available runtime resources and the needs of the task being performed by the model. In doing so, systems and methods disclosed herein can efficiently utilize the limited resources in mobile systems to maximize performance of multiple concurrently running neural network-based applications.

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Fraud detection system and method

NºPublicación: AU2018301643A1 06/02/2020

Solicitante:

VAIL SYSTEMS INC [US]

CA_3069731_A1

Resumen de: AU2018301643A1

A system and method for fraud detection for a telephony platform based on an analysis of call detail records (CDRs) that are generated by the telephony platform. The analysis is based on collecting, organizing, transforming, analyzing, and quantifying the CDR data into a plurality of data analytics and data correlations and then applying fuzzy logic to the data analytics to generate a fraud risk rating for each incoming call into the platform.

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一种基于遗传算法的云制造多视角协同调度优化方法

NºPublicación: CN110751292A 04/02/2020

Solicitante:

浙江财经大学

Resumen de: CN110751292A

本发明公开了一种基于遗传算法的云制造多视角协同调度优化方法,用于从用户、制造企业和制造平台三个视角的相关属性优化调度方案,用户的相关属性包括时间、成本和可靠性,制造企业的相关属性包括外包,制造平台的相关属性包括能耗,基于遗传算法的云制造多视角协同调度优化方法,包括:采用三角模糊数表示时间、成本、可靠性和能耗的模糊属性值,以时间、成本、可靠性和能耗的模糊属性值以及外包建立FMILP模型;利用基于区间直觉模糊熵权法的遗传算法求解FMILP模型。本发明从用户、制造企业和制造平台三个视角优化调度方案,并且采用区间直觉模糊熵权法设置FMILP模型的相关参数,考虑了QoS属性权重和任务权重,以得到更优的调度方案。

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一种滚动直线导轨综合性能模糊评价方法

NºPublicación: CN110750940A 04/02/2020

Solicitante:

大连理工大学

Resumen de: CN110750940A

本发明公开了一种滚动直线导轨综合性能模糊评价方法。该方法的具体步骤为:建立滚动直线导轨综合性能模糊评价层次结构模型;通过三尺度法建立比较矩阵,由比较矩阵得到层级内各指标的权重系数;进行层级单一排序和总体排序以及一致性检验;利用折中规划法和平均功率法建立滚动直线导轨静态性能、动态性能以及综合性能模糊评价函数;依据评价函数对滚动直线导轨的静、动态性能和综合性能进行评价,得到评价结果。本方法解决了传统静态和动态性能单目标评价以及评价指标的权重系数难以确定的问题,能够合理描述滚动直线导轨的静动综合性能,具有较高的工程实用性。

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一种视角约减的多视角TSK模糊系统

NºPublicación: CN110728369A 24/01/2020

Solicitante:

南通大学

Resumen de: CN110728369A

本发明公开了一种视角约减的多视角TSK模糊系统,该多视角TSK模糊系统的目标函数包含2个部分,第一部分为协同学习机制,第二部分为视角约减机制,在该模型的目标函数中,引入误差约束项,使得当前视角的决策结果与其他视角决策结果的均值之差最小,从而实现多视角协同学习;另外,引入“变体信息熵”,学习各视角的权重,并设计约减规则,剔除噪声视角或弱相关视角。这对于提高多视角数据的分类精度有着非常重要的作用。

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一种电力二次设备差异化改造方案选择方法

NºPublicación: CN110727912A 24/01/2020

Solicitante:

河海大学

Resumen de: CN110727912A

本发明公开了一种电力二次设备差异化改造方案选择方法,通过根据二次设备使用历史信息与相关规范和标准构建了包括方案层、准则层和目标层的层次分析结构,随后给出上述各指标的计算模型和量化方法,采用三角直觉模糊数理论,将所有指标模糊化处理;通过定义新的得分函数改进模糊层次分析法,基于模糊数运算法则求取各指标权重,并进行分层排序。本发明基于三角直觉模糊理论进行电力二次设备差异化改造方案选择,相比其他线性评估排序方�x6CD5;,解决了评估过程中存在界定不清的模糊性和统计信息的不完整性问题,同时保留有效信息,降低主观因素的影响,提高变电站进行精准的二次设备差异化技术改造的能力。

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利用模糊聚类的基因网络分析方法

NºPublicación: CN110717541A 21/01/2020

Solicitante:

吉林大学

Resumen de: CN110717541A

本发明提供一种利用模糊聚类的基因网络分析方法,该方法将现有基因网络分析中硬聚类替换为模糊聚类。本发明由于模糊聚类具有簇之间非斥的特点,即对象可以同时属于多个簇,而簇之间可以有交集,这与系统生物学中基因参与多种生物功能子系统的运作的观点很契合,进而使得簇的划分更准确和更符合生物学逻辑,从而达到从生物学角度优化基因网络分析算法的目的。

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METHOD AND SYSTEM FOR MUTING CLASSIFIED INFORMATION FROM AN AUDIO

NºPublicación: US2020020340A1 16/01/2020

Solicitante:

TATA CONSULTANCY SERVICES LTD [IN]

EP_3598444_PA

Resumen de: US2020020340A1

This disclosure relates generally to a method and system for muting of classified information from an audio using a fuzzy approach. The method comprises converting the received audio signal into text using a speech recognition engine to identify a plurality of classified words from the text to obtain a first set of parameters. Further, a plurality of subwords associated with each classified word are identified to obtain a second set of parameters associated with each subword of corresponding classified word. A relative score is computed for each subword associated with the classified word based on a plurality of similar pairs for the corresponding classified word. A fuzzy muting function is generated using the first set of parameters, the second set of parameters and the relative score associated with each subword. The plurality of subwords associated with each classified word is muted in accordance with the generated fuzzy muting function.

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一种非线性模糊逻辑决策算法

NºPublicación: CN110689132A 14/01/2020

Solicitante:

厦门钛尚人工智能科技有限公司

Resumen de: CN110689132A

本发明提供一种非线性模糊逻辑决策算法,涉及家居厨房领域。该非线性模糊逻辑决策算法,包括以下步骤:S1:采集移动数据,记录对应时间下的相关参数,统计出关于时间的特征值;S2:将统计的特征值进行分段处理,以时间参数为节点,设置对应的特征区间;S3:将精确量转换为标准论域上的模糊单点集,精确量经对应关系转换为标准论域上的基本元素。通过建立非线性模糊化模型,训练非线性模糊化算法,使得运动模糊决策中能够有相关的有效算法计算出运动员非线性的模糊加速度变化,对模糊值进行推理,决策出精确值之后,得到最终精准量输出,在一定程度上让运动过程分析更加真实有效。

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基于FAHP与规划图融合的Web服务组合方法

NºPublicación: CN110691000A 14/01/2020

Solicitante:

山东理工大学

Resumen de: CN110691000A

本发明涉及Web服务组合技术领域,具体涉及一种基于FAHP与规划图融合的Web服务组合方法。它包括输入用户请求和Web服务存储库中的服务;通过FAHP方法分别计算每个服务的归一化QoS值;执行规划图的向前扩展阶段;根据用户请求执行规划图向后搜索阶段,所述向后搜索阶段包括根据用户需要寻找的每一个目标输出g,在A层中寻找满足最多功能性需求且归一化QoS值最高的服务ws;将服务ws的输入参数作为P层中的目标状态,重复此过程直至到达初始状态层;将得到的该最佳服务组合路径输出。本方法可以匹配出能够实现用户复杂需求的服务组合,也能准确反应候选服务对于用户偏好的综合QoS水平。

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一种基于双向投影的图像模糊多属性决策方法

NºPublicación: CN110674946A 10/01/2020

Solicitante:

安阳师范学院

Resumen de: CN110674946A

本发明公开了一种基于双向投影的图像模糊多属性决策方法。根据TOPSIS方法,构造基于双向投影的图像模糊相对贴近度公式,在多属性决策问题中,考虑方案和图像模糊绝对正理想解、图像模糊绝对负理想解的关系,构造图像模糊权重绝对正则投影模型,以及基于双向投影的图像模糊绝对贴近度公式。然后,将基于双向投影的图像模糊相对贴近度公式和图像模糊绝对贴近度公式融合并建立图像模糊综合贴近度公式。最后,利用方案的图像模糊综合贴近度数值的大小对方案集进行优劣排序,并确定图像模糊综合贴近度最大的方案为最优方案,实现精准分析和决策。

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一种基于图像模糊集的多属性决策系统

Nº publicación: CN110674945A 10/01/2020

Solicitante:

安阳师范学院

Resumen de: CN110674945A

一种基于图像模糊集的多属性决策系统,包括:获取模块从输入端获取决策矩阵;数据判断模块从所述获取模块中获取所述决策矩阵并对其进行规范化判断;规范化处理模块从所述数据判断模块中获取非规范决策矩阵并进行规范化处理;相对值计算模块计算各个方案的图像模糊相对贴近度;绝对值计算模块计算各个方案的图像模糊绝对贴近度;融合计算模块计算各个方案的图像模糊综合贴近度;决策模块从所述融合计算模块中获取各个方案的图像模糊综合贴近度,并以此对方案进行优劣排序后确定图像模糊综合贴近度最大的方案为最优方案;显示模块从所述决策模块中获取所述最优方案并进行显示。

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