公开(公告)号：US20090112645A1

公开(公告)日：2009-04-30

申请号：US11924468

申请日：2007-10-25

Applicant: Pratik D. Jha ,  Rajesh Venkat Subbu ,  John Michael Lizzi ,  Naresh Iyer ,  Liviu Nedelescu

Inventor： Pratik D. Jha ,  Rajesh Venkat Subbu ,  John Michael Lizzi ,  Naresh Iyer ,  Liviu Nedelescu

IPC: G06Q10/00

CPC classification number: G06Q10/04 ,  G06Q10/06 ,  G06Q10/0631 ,  G06Q10/10 ,  G06Q50/30

Abstract: Systems and methods for planning and optimizing air traffic flow within an airspace are provided. In one embodiment, a system (200) includes: (1) a stakeholder objective evaluation module (212) receiving stakeholder preferences from stakeholders having an interest in flight routing within the airspace during an operational planning period and stakeholder metrics as feedback input and outputting strategic and flight route settings for the airspace based on the stakeholder preferences and stakeholder metrics; (2) a strategic optimization module (204) receiving the strategic settings, creating an initial airspace state, and generating an updated airspace state using the strategic settings; (3) a route optimization module (202) receiving the flight route settings and selecting preferred routes for flights during the operational planning period using the route settings; and (4) a simulation module (206) receiving simulation settings including the airspace state and the preferred routes, simulating flights during the operational planning period, and outputting the stakeholder metrics for feed-back.

Abstract translation: 提供了规划和优化空域内空中交通流量的系统和方法。 在一个实施例中，系统（200）包括：（1）利益相关者客观评价模块（212），在运营计划期间，利益相关者指标作为反馈输入并输出战略 并根据利益相关者的偏好和利益相关方的指标，为空域设置飞行路线; （2）接收战略设置的战略优化模块（204），创建初始空域状态，以及使用战略设置生成更新的空域状态; （3）路线优化模块（202），其使用所述路线设置接收所述飞行路线设置并且在所述运营规划期间选择所述航班的优选路线; 以及（4）模拟模块（206），其接收包括空域状态和优选路线的模拟设置，在操作规划期间模拟飞行，以及输出利益相关者度量以进行反馈。

公开(公告)号：US20090105935A1

公开(公告)日：2009-04-23

申请号：US12253690

申请日：2008-10-17

Applicant: Pratik D. Jha ,  Alexander Suchkov ,  Rajesh Venkat Subbu ,  John Michael Lizzi ,  Jingqiao Zhang ,  Ian Crook ,  Abderrazak Tibichte

Inventor： Pratik D. Jha ,  Alexander Suchkov ,  Rajesh Venkat Subbu ,  John Michael Lizzi ,  Jingqiao Zhang ,  Ian Crook ,  Abderrazak Tibichte

IPC: G06F19/00

CPC classification number: G08G5/0043 ,  G08G5/0034

Abstract: Hybrid-heuristic optimization of competing portfolios of flight paths for flights through one or more sectors of an airspace represented by an air traffic system. In one embodiment, a hybrid-heuristic optimization process (100) includes one or more heuristic based processes (110), a genetic optimization process (120), an evaluation process involving an approximation model (130), an optimal portfolio selection process (140) and a validation process involving simulation (150) of the air traffic system.

Abstract translation: 对通过由空中交通系统表示的空域的一个或多个部门的航班的飞行路线的竞争组合的混合启发式优化。 在一个实施例中，混合启发式优化过程（100）包括一个或多个基于启发式的过程（110），遗传优化过程（120），涉及近似模型（130），最佳投资组合选择过程（140） ）和涉及空中交通系统仿真（150）的验证过程。

公开(公告)号：US20090048876A1

公开(公告)日：2009-02-19

申请号：US12131545

申请日：2008-06-02

Applicant: Piero Patrone Bonissone ,  Kareem Sherif AGGOUR ,  Rajesh Venkat SUBBU ,  Weizhong YAN ,  Naresh Sundaram IYER ,  Anindya CHAKRABORTY

Inventor： Piero Patrone Bonissone ,  Kareem Sherif AGGOUR ,  Rajesh Venkat SUBBU ,  Weizhong YAN ,  Naresh Sundaram IYER ,  Anindya CHAKRABORTY

IPC: G06Q40/00 ,  G06Q10/00

CPC classification number: G06Q40/08 ,  G06Q40/00

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers. The reliability of each classifier can be represented by a static or dynamic discounting factor, which will reflect the expected accuracy of the classifier. A static discounting factor is used to represent a prior expectation about the classifier's reliability, e.g., it might be based on the average past accuracy of the model, while a dynamic discounting is used to represent a conditional assessment of the classifier's reliability, e.g., whenever a classifier bases its output on an insufficient number of points it is not reliable.

Abstract translation: 描述用于融合用于自动保险承保系统的分类器集合和/或其质量保证的方法和系统。 具体来说，分类器的集合的输出被融合。 数据的融合通常会导致一些共识和分类器之间的一些冲突。 共识将被测量并用于估计融合决策的信心程度。 根据融合的决定和信心程度以及生产​​决策引擎的决策和决策程度，然后可以使用比较模块来识别审计案例，增加用于重新调整生产的培训/测试集的案例 决策引擎，审查案例，或者可以简单地触发其发生记录以进行跟踪。 融合可以补偿分类器之间的潜在相关性。 每个分类器的可靠性可以由静态或动态折扣因子表示，这将反映分类器的预期准确性。 静态折扣因子用于表示对分类器的可靠性的先前期望，例如，可以基于模型的平均过去精度，而使用动态贴现来表示分类器的可靠性的条件评估，例如，每当 分类器的输出基于不可靠的点数不足。

公开(公告)号：US07469228B2

公开(公告)日：2008-12-23

申请号：US10781897

申请日：2004-02-20

Applicant: Piero Patrone Bonissone ,  Srinivas Bollapragada ,  Kete Charles Chalermkraivuth ,  Neil Holger White Eklund ,  Naresh Sundaram Iyer ,  Rajesh Venkat Subbu

Inventor： Piero Patrone Bonissone ,  Srinivas Bollapragada ,  Kete Charles Chalermkraivuth ,  Neil Holger White Eklund ,  Naresh Sundaram Iyer ,  Rajesh Venkat Subbu

IPC: G06Q40/00

CPC classification number: G06Q40/06

Abstract: The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: performing a first multi-objective optimization process, based on competing objectives, to generate an efficient frontier of possible solutions; observing the generated efficient frontier; based on the observing, identifying an area of the efficient frontier in which there is a gap; and effecting a gap filling process by which the efficient frontier is supplemented in the area of the gap, the efficient frontier being used in investment decisioning.

Abstract translation: 本发明的系统和方法针对组合优化和相关技术。 例如，本发明提供了一种用于基于竞争目标和构成投资组合问题的多个约束的投资决策中的多目标投资组合优化的方法，所述方法包括：基于竞争目标执行第一多目标优化过程 ，以产生可能的解决方案的有效前沿; 观察生成的有效边界; 根据观察，确定存在差距的有效边界的一个区域; 并在差距填补过程中，有效的前沿在差距领域得到补充，有效的前沿被用于投资决策。

公开(公告)号：US20080234994A1

公开(公告)日：2008-09-25

申请号：US11689885

申请日：2007-03-22

Applicant: Kai Frank Goebel ,  Rajesh Venkat Subbu ,  Dean Kimball Frederick

Inventor： Kai Frank Goebel ,  Rajesh Venkat Subbu ,  Dean Kimball Frederick

IPC: G06F17/00

CPC classification number: G06F17/5009 ,  G06F17/5095 ,  G06F2217/10

Abstract: A method for multi-objective deterioration accommodation using predictive modeling is disclosed. The method uses a simulated machine that simulates a deteriorated actual machine, and a simulated controller that simulates an actual controller. A multi-objective process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a deteriorated condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a deteriorated condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

Abstract translation: 公开了一种使用预测建模的多目标恶化调节方法。 该方法使用模拟恶化的实际机器的模拟机，以及模拟实际控制器的仿真控制器。 基于模拟控制器的指定控制设置和由模拟控制器控制的模拟机器的指定操作场景，执行多目标过程，以生成将仿真机器的性能与模拟机器的性能相关联的基于帕累托前沿的解空间 模拟控制器，包括对操作场景的调整，以表示模拟机器的劣化状况。 由模拟控制器表示的实际控制器的控制设置根据基于帕累托前沿的解决方案空间，根据实际机器的劣化情况，对模拟机器所代表的实际机器进行调整，以最大化 期望的操作条件，并且在由帕累托边界限定的解空间的区域中操作实际机器时最小化不期望的操作条件。

公开(公告)号：US20080229754A1

公开(公告)日：2008-09-25

申请号：US11689874

申请日：2007-03-22

Applicant: Kai Frank Goebel ,  Rajesh Venkat Subbu ,  Randal Thomas Rausch ,  Dean Kimball Frederick

Inventor： Kai Frank Goebel ,  Rajesh Venkat Subbu ,  Randal Thomas Rausch ,  Dean Kimball Frederick

IPC: F02C1/00

CPC classification number: F02C9/00 ,  F05D2270/44 ,  F05D2270/71 ,  Y02T50/671

Abstract: A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a fault condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

Abstract translation: 公开了一种使用预测建模的多目标故障调节方法。 该方法包括使用模拟故障实际机器的仿真机，并使用模拟实际控制器的仿真控制器。 基于模拟控制器的指定控制设置和由模拟控制器控制的模拟机器的指定操作场景，执行多目标优化过程，生成与仿真机器的性能相关的基于Pareto前沿的解空间， 模拟控制器，包括对操作场景的调整，以表示模拟机器的故障状态。 实际控制器的控制设置由模拟控制器进行调整，用于根据基于Pareto前沿解决方案空间的实际机器的故障情况来控制由仿真机器表示的实际机器，以最大化 期望的操作条件，并且在由帕累托边界限定的解空间的区域中操作实际机器时最小化不期望的操作条件。

公开(公告)号：US20080201183A1

公开(公告)日：2008-08-21

申请号：US11924435

申请日：2007-10-25

Applicant: Pratik D. Jha ,  Alexander Suchkov ,  Rajesh Venkat Subbu ,  John Michael Lizzi ,  Naresh Iyer

Inventor： Pratik D. Jha ,  Alexander Suchkov ,  Rajesh Venkat Subbu ,  John Michael Lizzi ,  Naresh Iyer

IPC: G06F17/00

CPC classification number: G08G5/0043 ,  G06Q10/063 ,  G06Q10/06316

Abstract: Systems and methods for optimizing a plurality of competing portfolios of logistical alternatives are disclosed. In one embodiment, where the competing portfolios of logistical alternatives are competing portfolios of flight paths, a method (1100) for optimizing a plurality of competing portfolios of logistical alternatives includes receiving (1102) competing flight path portfolios from one or more flight operation centers. Dominance criteria are applied (1104) to select a subset of the portfolios from the plurality of competing portfolios for further consideration. Multi-objective genetic optimization is applied (1106) to the subset of portfolios to identify an optimal portfolio among the plurality of competing portfolios of logistical alternatives. Where the method (1100) is undertaken by executing computer program code on at least one computer processor, information identifying the logistical alternatives included in the optimal portfolio may be output (1108) on an output device in communication with the computer processor.

Abstract translation: 公开了用于优化多个竞争的后勤备选组合的系统和方法。 在一个实施例中，在物流替代品的竞争组合是竞争的飞行路径组合的情况下，用于优化多个竞争的后勤备选组合的方法（1100）包括从一个或多个飞行运行中心接收（1102）竞争的飞行路径组合。 应用优势标准（1104）从多个竞争投资组合中选择投资组合的一部分进行进一步考虑。 多目标遗传优化（1106）应用于投资组合的子集，以确定多个相互竞争的后勤备选组合中的最佳投资组合。 在通过在至少一个计算机处理器上执行计算机程序代码来执行方法（1100）的情况下，可以在与计算机处理器通信的输出设备上输出识别最佳投资组合中包括的物流备选方案的信息（1108）。

公开(公告)号：US20080004792A1

公开(公告)日：2008-01-03

申请号：US11427728

申请日：2006-06-29

Applicant: Gerald Bowden Wise ,  John Michael Lizzi ,  Louis John Hoebel ,  Rajesh Venkat Subbu ,  Daniel Joseph Cleary ,  Liviu Nedelescu ,  Paul W. Mettus ,  Bradley A. Culbertson ,  Jonathan Dehn

Inventor： Gerald Bowden Wise ,  John Michael Lizzi ,  Louis John Hoebel ,  Rajesh Venkat Subbu ,  Daniel Joseph Cleary ,  Liviu Nedelescu ,  Paul W. Mettus ,  Bradley A. Culbertson ,  Jonathan Dehn

IPC: G06G7/76

CPC classification number: G08G5/0043

Abstract: Systems and methods for airspace demand prediction with improved sector level demand prediction are provided. In one embodiment, an air traffic demand prediction system (10) operable to predict demand within an airspace divided into sectors includes an expanded route predictor (14) operable to generate predicted two-dimensional expanded route information (40) associated with at least one requested flight (34), a trajectory modeler (16) operable to generate predicted four-dimensional expanded route information (46), a sector crossing predictor (18) operable to generate predicted sector crossing information (48), a departure time predictor (22) operable to generate predicted departure time information (54), and a demand modeler (62) operable to generate a demand model (28), the demand model (28) including predicted time intervals associated with the at least one requested flight indicating when it is expected to be present within one or more sectors of the airspace.

Abstract translation: 提供了改善部门级需求预测的空域需求预测系统和方法。 在一个实施例中，可操作以预测划分为扇区的空域内的需求的空中交通需求预测系统（10）包括扩展路由预测器（14），其可操作以产生与至少一个请求的相关联的预测的二维扩展路由信息（40） 飞行（34），可操作以产生预测的四维扩展路径信息（46）的轨迹建模器（16），可操作以产生预测扇区交叉信息的扇区交叉预测器（48），出发时间预测器（22） 可操作以产生预测的出发时间信息（54），以及可操作以生成需求模型（28）的需求建模器（62），所述需求模型（28）包括与所述至少一个请求的飞行相关联的预测时间间隔， 预计将在空域的一个或多个部门内存在。

公开(公告)号：US20120215434A1

公开(公告)日：2012-08-23

申请号：US13032151

申请日：2011-02-22

Applicant: Rajesh Venkat Subbu ,  Jon David Petersen ,  Weiwei Chen

Inventor： Rajesh Venkat Subbu ,  Jon David Petersen ,  Weiwei Chen

IPC: G08G5/00

CPC classification number: G08G5/0013

Abstract: Methods and systems suitable for processing multiple trajectory modification requests received from multiple aircraft within an airspace. The methods include receiving multiple trajectory modification requests that are transmitted from multiple aircraft and request alterations of the altitudes, speeds and/or lateral routes thereof, sequentially performing conflict assessments on the multiple trajectory modification requests to determine if any of the multiple trajectory modification requests pose conflicts with the altitudes, speeds and lateral routes of any other of the multiple aircraft, placing in a computer memory data queue n trajectory modification requests of the multiple trajectory modification requests that are identified by the conflict assessments as posing conflicts, and periodically processing the queue to perform subsequent conflict assessments on the n trajectory modification requests to determine if any of the n trajectory modification requests still pose conflicts with the altitudes, speeds and lateral routes of any other of the multiple aircraft.

Abstract translation: 适用于处理从空域内的多架飞机接收的多轨迹修改请求的方法和系统。 所述方法包括接收从多个飞行器发送的多个轨迹修改请求，并请求对其高度，速度和/或横向路线的改变，对多个轨迹修改请求顺序执行冲突评估，以确定多个轨迹修改请求中是否存在任何姿势 与多个飞机中的任何其他飞机的高度，速度和横向路线冲突，将由冲突评估识别的多个轨迹修改请求的轨迹修改请求放置在计算机存储器数据队列中，构成冲突，并周期性地处理队列 对n个轨迹修改请求执行随后的冲突评估，以确定n个轨迹修改请求中的任何一个是否仍然与多个飞行器中的任何另一个的高度，速度和横向路线相冲突。

公开(公告)号：US20120215433A1

公开(公告)日：2012-08-23

申请号：US13032101

申请日：2011-02-22

Applicant: Rajesh Venkat Subbu ,  Feng Xue ,  Mauricio Castillo-Effen ,  Joel Kenneth Klooster ,  Joachim Karl Ulf Hochwarth ,  Sergio Torres ,  Weiwei Chen

Inventor： Rajesh Venkat Subbu ,  Feng Xue ,  Mauricio Castillo-Effen ,  Joel Kenneth Klooster ,  Joachim Karl Ulf Hochwarth ,  Sergio Torres ,  Weiwei Chen

IPC: G08G5/00

CPC classification number: G08G5/0043 ,  G06Q10/047 ,  G06Q10/06 ,  G06Q50/30

Abstract: Methods and systems suitable for negotiating air traffic trajectory modification requests received from multiple aircraft that each has trajectory parameters. The methods include transmitting from at least a first aircraft a first trajectory modification request to alter the altitude, speed and/or lateral route thereof. A first conflict assessment is then performed to determine if the first trajectory modification request poses a conflict with the altitudes, speeds and lateral routes of other aircraft. If a conflict is not identified, the first trajectory modification request is granted and the first aircraft is notified of the first trajectory modification request being granted. Alternatively, if a conflict is identified, the first trajectory modification request is not granted and the first aircraft is notified thereof. If the first trajectory modification request was not granted, the first trajectory modification request is placed in a queue, which is periodically processed to perform subsequent conflict assessments.

Abstract translation: 适用于协商从多台飞机接收的空中交通轨迹修改请求的方法和系统，每个航空器具有轨迹参数。 所述方法包括从至少第一飞行器发送第一轨迹修改请求以改变其高度，速度和/或横向路线。 然后执行第一冲突评估以确定第一轨迹修改请求是否与其他飞行器的高度，速度和侧向路线形成冲突。 如果没有识别到​​冲突，则授予第一轨迹修改请求，并且向第一飞机通知被授予的第一轨迹修改请求。 或者，如果确定了冲突，则未授予第一轨迹修改请求，并且通知第一飞行器。 如果未授予第一轨迹修改请求，则将第一轨迹修改请求放置在队列中，该队列被周期性地处理以执行随后的冲突评估。