公开(公告)号：US07664596B2

公开(公告)日：2010-02-16

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: G06F17/00 ,  G06F19/00

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：US20080288280A1

公开(公告)日：2008-11-20

申请号：US11748611

申请日：2007-05-15

Applicant: Deborah J. Belcher ,  Mary J. Ammer ,  William Estel Cheetham ,  Rajesh Venkat Subbu ,  Feng Xue ,  Bernhard Joseph Scholz ,  Piero Patrone Bonissone

Inventor： Deborah J. Belcher ,  Mary J. Ammer ,  William Estel Cheetham ,  Rajesh Venkat Subbu ,  Feng Xue ,  Bernhard Joseph Scholz ,  Piero Patrone Bonissone

IPC: G06Q10/00 ,  G06F17/18

CPC classification number: G06F19/328 ,  G06Q10/10 ,  G06Q50/22

Abstract: A system and method for processing healthcare service data is herein disclosed. The system comprising a decision engine in communication with a process manager and a knowledge source. The decision engine receives at least one protocol from the knowledge source that is derived by automated learning and applies the at least one protocol to healthcare service data and transmits a response to the process manager such that the response is indicative of a next workflow step to be taken.

Abstract translation: 本文公开了一种用于处理医疗服务数据的系统和方法。 该系统包括与进程管理器和知识源通信的决策引擎。 所述决策引擎从所述知识源接收至少一个通过自动学习获得的协议，并将所述至少一个协议应用于医疗保健服务数据，并向所述过程管理器发送响应，使得所述响应指示下一工作流步骤为 被采取。

公开(公告)号：US20080016013A1

公开(公告)日：2008-01-17

申请号：US11485101

申请日：2006-07-12

Applicant: Rajesh Venkat Subbu ,  Stefano Romoli Bonissone

Inventor： Rajesh Venkat Subbu ,  Stefano Romoli Bonissone

IPC: G06N3/12

CPC classification number: G06N3/126

Abstract: A system for implementing a multi objective evolutionary algorithm (MOEA) on a programmable hardware device is provided. The system comprises a random number generator, a population generator, a crossover/mutation module, a fitness evaluator, a dominance filter and an archive. The random number generator is configured to generate a sequence of pseudo random numbers. The population generator is configured to generate a population of solutions based on the output from the random number generator. The crossover/mutation module is configured to adapt the population of solutions to generate an adapted population of solutions. The fitness evaluator is configured to evaluate each member comprising the population of solutions and the adapted population of solutions. The fitness evaluator is implemented on the programmable hardware device. The dominance filter is configured to select a subset of members from the population of solutions and the adapted population of solutions and generate a filtered population of solutions. The archive configured to store populations of solutions.

Abstract translation: 提供了一种在可编程硬件设备上实现多目标演化算法（MOEA）的系统。 该系统包括随机数生成器，总体生成器，交叉/变异模块，健身评估器，优势过滤器和存档。 随机数生成器被配置为生成伪随机数序列。 群体生成器被配置为基于来自随机数生成器的输出来生成解的群体。 交叉/变异模块被配置为适应解决方案的群体以产生适应的解决方案群体。 健身评估器被配置为评估包括解决方案群体和适应的解决方案群体的每个成员。 健身评估器在可编程硬件设备上实现。 优势过滤器被配置为从解决方案群体和适应的解决方案群体中选择成员的子集，并生成过滤的解答群体。 归档配置为存储解决方案的数量。