Objective weighing and ranking
    3.
    发明授权
    Objective weighing and ranking 有权
    客观称重和排名

    公开(公告)号:US09305266B2

    公开(公告)日:2016-04-05

    申请号:US14178331

    申请日:2014-02-12

    CPC classification number: G06N7/005 G06N7/08 G06Q10/04

    Abstract: A method comprising using at least one hardware processor for: receiving a multi-objective optimization problem; projecting a Pareto frontier of candidate solutions for said multi-objective optimization problem to a hyperplane; decomposing said hyperplane into multiple Voronoi regions each associated with a candidate solution of said candidate solutions; determining a robustness degree for each candidate solution of said candidate solutions, by computing a hypervolume for each region of said multiple Voronoi regions; and ranking said candidate solutions based on the robustness degree.

    Abstract translation: 一种方法,包括使用至少一个硬件处理器:接收多目标优化问题; 将用于所述多目标优化问题的候选解决方案的帕累托前沿投影到超平面; 将所述超平面分解成多个Voronoi区域,每个Voronoi区域与所述候选解决方案的候选解决方案相关联; 通过计算所述多个Voronoi区域的每个区域的超音阶来确定所述候选解的每个候选解的鲁棒性度; 并根据鲁棒性程度对候选解决方案进行排名。

    Multi objective design selection
    4.
    发明授权
    Multi objective design selection 有权
    多目标设计选择

    公开(公告)号:US09299032B2

    公开(公告)日:2016-03-29

    申请号:US13674108

    申请日:2012-11-12

    Abstract: A method of selecting a group from a plurality of multi objective designs which comply with a plurality of objectives. The method comprises providing a plurality of multi objective designs, each the multi objective design having a plurality of multi objective design objective values which comply with at least one constraint of a Pareto Frontier of an objective space of a plurality of objectives, selecting a group from the plurality of multi objective designs, each member of the group is selected according to a match between at least one objective of respective the plurality of objectives and at least one of a respective gain threshold and a respective loss threshold, and outputting the group.

    Abstract translation: 从符合多个目标的多个多目标设计中选择组的方法。 该方法包括提供多个多目标设计,每个多目标设计具有多个符合多个目标的客观空间的帕累托前沿的至少一个约束的多目标设计目标值,从多个目标设计中选择一组 所述多个多目标设计中,根据所述多个目标的至少一个目标与相应的增益阈值和相应的损失阈值中的至少一个之间的匹配来选择所述组中的每个成员,并输出所述组。

    MULTIOBJECTIVE OPTIMIZATION THROUGH USER INTERACTIVE NAVIGATION IN A DESIGN SPACE
    7.
    发明申请
    MULTIOBJECTIVE OPTIMIZATION THROUGH USER INTERACTIVE NAVIGATION IN A DESIGN SPACE 审中-公开
    通过设计空间中的用户互动导航的多重优化

    公开(公告)号:US20150019173A1

    公开(公告)日:2015-01-15

    申请号:US13937231

    申请日:2013-07-09

    CPC classification number: G06F17/50

    Abstract: A computerized method of providing a multiobjective optimal design through user interactive navigation, comprising: 1) Designating a user reference design which defines multiple objectives in a design space. 2) Exploring the design space to identify a multiobjective optimal design, evolved from the reference design, through multiple navigation iterations. During each iteration the user is interacted to reach an intermediate candidate design which is closer to a Pareto frontier. Each iteration comprising: (a) Identifying and presenting the user, optimal designs which are closer to the Pareto frontier and are within a pre-defined evolution distance from an intermediate design of previous iteration, improving one or more of the objectives. (b) Selecting a preferred design from those candidate designs, according to user instructions, the preferred design is used as the starting point for the next iteration. (c) Outputting the preferred design selected at the final iteration and considered as the multiobjective optimal design.

    Abstract translation: 一种通过用户交互式导航提供多目标优化设计的计算机化方法,包括:1)指定在设计空间中定义多个目标的用户参考设计。 2)探索设计空间,以确定多目标优化设计,从参考设计,多重导航迭代演化而来。 在每次迭代期间,用户进行交互以达到更靠近帕累托边界的中间候选设计。 每个迭代包括:(a)识别和呈现用户,更接近帕累托边界的优化设计,并且在与先前迭代的中间设计之间的预定演化距离内,改进一个或多个目标。 (b)根据用户指令从这些候选设计中选择一个优选的设计,将优选的设计用作下一次迭代的起始点。 (c)输出在最终迭代中选择的优选设计,并将其视为多目标优化设计。

    CREATING PLUGGABLE ANALYSIS VIEWPOINTS FOR AN OPTIMIZATION SYSTEM MODEL
    8.
    发明申请
    CREATING PLUGGABLE ANALYSIS VIEWPOINTS FOR AN OPTIMIZATION SYSTEM MODEL 审中-公开
    为优化系统模型创建可插拔分析视图

    公开(公告)号:US20140201706A1

    公开(公告)日:2014-07-17

    申请号:US13740284

    申请日:2013-01-14

    CPC classification number: G06F8/10

    Abstract: A method of creating a system having pluggable analysis viewpoints over a design space model based on templates for analytical representation of different system aspects, comprising: a) Ontologically representing each of a plurality of system viewpoints with a subset of the components and classes using attributes and inter-attribute relationships. b) Automatically creating a unified design space model represented by the design space components according to a plurality of user defined pluggable analysis viewpoints and modeling viewpoints. c) Automatically generating a design space model derived from a plurality of analysis and modeling viewpoints. d) Receiving at least one change marked by a user with respect to a certain one of the plurality of analysis and modeling viewpoints. e) Automatically updating the design space model and the plurality of viewpoint models to reflect the at least one change. f) Outputting the updated design space model and the plurality of viewpoint models.

    Abstract translation: 一种创建具有基于用于不同系统方面的分析表示的模板的设计空间模型的具有可插拔分析视点的系统的方法,包括:a)使用属性使用组件和类的子集在本体上表示多个系统视点中的每一个, 属性间关系。 b)根据多个用户定义的可插拔分析视点和建模视点,自动创建由设计空间组件表示的统一设计空间模型。 c)自动生成从多个分析和建模视点导出的设计空间模型。 d)相对于所述多个分析和建模视点中的某一个接收用户标记的至少一个改变。 e)自动更新设计空间模型和多个视点模型以反映至少一个变化。 f)输出更新的设计空间模型和多个视点模型。

    Computerized dialog system improvements based on conversation data

    公开(公告)号:US11605386B2

    公开(公告)日:2023-03-14

    申请号:US17000397

    申请日:2020-08-24

    Abstract: The computer receives a group of conversation data associated with the escalation node, identifies agent responses in the conversation data, and clusters them into agent response types. The computer identifies dialog state feature value sets for the conversations. The computer identifies feature value set associations with response types, and generates, Boolean expressions representing the feature value sets associated with each of the response types. The computer makes a recommendation to add to at least one child node for the escalation node, with the child node corresponding to one of the response types. The child node has, as an entry condition, the Boolean expression for the response type to which the child node corresponds. The child node has as an action, which according to some aspects, provides a response representative of the cluster of agent responses for the response type to which the child node corresponds.

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