General Electric Company

Genworth Financial, Inc.

Lockheed Martin Corporation

General Electric Capital Corporation

Ge Corporate Financial Services, Inc.

Leidos Innovations Technology, Inc.

Rajesh Venkat Subbu

Piero Patrone Bonissone

Naresh Sundaram Iyer

Kete Chalermkraivuth

Srinivas Bollapragada

Richard Paul Messmer

Neil Holger White Eklund

Weizhong Yan

Kareem Sherif Aggour

Avinash Vinayak Taware

Marc Pavese

Angela Patterson

Dan Yang

John Erik Hershey

Xiao Liang Hu

Joel Kenneth Klooster

Robert J Mitchell, Jr

Sergio Torres

Anindya Chakraborty

John Michael Lizzi

Vivek Venugopal Badami

Glen William Brooksby

Kai F Goebel

Joachim Karl Ulf Hochwarth

Mauricio Castillo-Effen

Anil Varma

Feng Xue

Antonio A Mogro-Campero

Diane Marie Russell

Jason Wayne Black

Rasiklal Punjalal Shah

Robert Frank Hoskin

Weiwei Chen

James Joseph Schmid

David So Keung Chan

Neil Colin Widmer

Daniel Joseph Cleary

Louis John Hoebel

Noemie Dion Ouellet

John Andrew Ellis

William Michael Durham

Gerald Bowden Wise

Lincoln Mamoru Fujita

Joachim Karl Hochwarth

Chad Eric Knodle

Michael Craig Clark

Neil H Eklund

Randal T Rausch

Sean Coleman Keenan

James G Russo

Matthew Allen

Pratik Jha

Jonathan Dehn

Vishwanath Avasarala

Radu Neagu

Jingjiao Zhang

David Chienju Li

Alexander Suchkov

Jingqiao Zhang

Ian Crook

Abderrazak Tibichte

Jose R Celaya

Hoai-Hai Doan

Melissa Ialeggio

Dean Kimball Frederick

Stefano Romoli Bonissone

Liviu Nedelescu

Paul W Mettus

Bradley A Culbertson

David So Chan

Richard J Mitchell

Joachim Karl Ulf Hocewarth

A system and method to improve efficiency in aircraft maneuvers meant to accommodate time-related constraints in air traffic. Information related to flight performance and atmospheric conditions is gathered onboard an aircraft, then transmitted to an air traffic control center. In the event of a delay or any other event which necessitates an alteration in an aircraft trajectory, the data is sent to a decision support tool to compute and provide alternative trajectories, preferably including operator-preferred trajectories, within air traffic constraints. Air traffic controllers can then offer an alternative trajectory to an aircraft that is more efficient, cost effective, and/or preferable to the aircraft operator.

Schedule management system and method for managing air traffic

Methods and system are provided for scheduling and negotiating air traffic within an airspace surrounding an airport and scheduled to land at the airport. An air traffic control (ATC) system is used to monitor the altitudes, speeds and lateral routes of aircraft. The ATC system generates a scheduled time-of-arrival (STA) at one or more meter fix points associated with the airport, the STA is stored, and data is received or inferred with the ATC system for at least a first of the aircraft, including a minimum fuel-cost speed and predicted trajectory parameters of the first aircraft based on current values of its existing trajectory parameters. Auxiliary data, including earliest and latest estimated time-of-arrival (ETAmin) and (ETAmax) at the meter fix point, STA being within/ outside ETAmin, ETAmax are generated, instructions are transmitted to the first aircraft, and the STA is updated for each aircraft stored in a queue.

Methods and systems for managing air traffic

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.

A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

System and method for advanced condition monitoring of an asset system

A method for generating an optimized transition probability matrix (OTPM) is provided. The method is performed using a computer system coupled to a database. The method includes storing in the database financial data including obligor credit ratings, generating multi-period empirical transition probability matrices (ETPMs) for a selected time horizon using the financial data stored within the database, generating a mathematical expression to minimize a difference between target ETPM values and candidate OTPM values, and calculating the OTPM from the generated mathematical expression and the financial data stored within the database, wherein the calculated OTPM includes a first set of optimized transition probability values for predicting a likelihood that a credit rating of an obligor will migrate from one credit state to another credit state during a first time interval in the future.

Methods and systems for generating transition probability matrices through an optimization framework

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: generating an initial population of solutions of portfolio allocations; committing the initial population of solutions to an initial population archive; performing a multi-objective process, based on the initial population archive and on multiple competing objectives, to generate an efficient frontier, the multi-objective process including a evolutionary algorithm process, the evolutionary algorithm process utilizing a dominance filter, the efficient frontier being used in investment decisioning.

Systems and methods for multi-objective portfolio analysis using pareto sorting evolutionary algorithms

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.

System and process for a fusion classification for insurance underwriting suitable for use by an automated system

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 () includes one or more heuristic based processes (), a genetic optimization process (), an evaluation process involving an approximation model (), an optimal portfolio selection process () and a validation process involving simulation () of the air traffic system.

Hybrid heuristic national airspace flight path optimization

A method for advanced condition monitoring of an asset system includes monitoring a variable of an asset system using the at least one sensor of a smart sensor system; determining whether the asset system has departed from normal operation; and identifying the variable of the asset system indicating the departure from normal operation. In another method, the time sequential values of the monitored variable is analyzed by using a Rank Permutation Transformation test, a Hotelling's Tstatistic test, and a Likelihood Ratio Test; and a change of an operating condition of the asset system is determined using the analyzed values. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

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: generating an initial population of solutions of portfolio allocations, the generating the initial population of solutions of portfolio allocations including systematically generating the initial population of solutions to substantially cover the space defined by the competing objectives and the plurality of constraints; and generating an efficient frontier in the space based on the initial population, the efficient frontier for use in investment decisioning.

Systems and methods for initial sampling in multi-objective portfolio analysis

A visual interactive multi-criteria decision-making method and computer-based apparatus for portfolio management. The method/apparatus supports partitioning of a portfolio of physical or other assets into two mutually exclusive categories, such as assets recommended for sale and assets recommended for retention. The method/apparatus utilizes one or more coupled 2-D projections of the portfolio in criteria space. The user interacts with the projections to express and record preferences.

Methods and interface for set-partitioning decision support tool

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.

Method and system for fault accommodation of machines

A robust process for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

Process for optimization of insurance underwriting suitable for use by an automated system

A robust system for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

System for optimization of insurance underwriting suitable for use by an automated system

A process for at least a partial underwriting of insurance policies is described. Based on the similarity to previous insurance applications, a decision on the current request for underwriting may be made. This decision-making process represents an analogical approach to the placement of an insurance application to an underwriting category, whereby a given insurance application request is compared to previous requests.

Process for case-based insurance underwriting suitable for use by an automated system

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Clifton Park, NY, United States of America

Rajesh Venkat Subbu