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Analysis

1 / 756
1.20140188462System and method for analyzing ambiguities in language for natural language processing
US - 03.07.2014
Int.Class G06F 17/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
 Appl.No 14201974 Applicant Zadeh Lotfi A. Inventor Zadeh Lotfi A.

Specification covers new algorithms, methods, and systems for artificial intelligence, soft computing, and deep learning/recognition, e.g., image recognition (e.g., for action, gesture, emotion, expression, biometrics, fingerprint, facial, OCR (text), background, relationship, position, pattern, and object), large number of images (“Big Data”) analytics, machine learning, training schemes, crowd-sourcing (using experts or humans), feature space, clustering, classification, similarity measures, optimization, search engine, ranking, question-answering system, soft (fuzzy or unsharp) boundaries/impreciseness/ambiguities/fuzziness in language, Natural Language Processing (NLP), Computing-with-Words (CWW), parsing, machine translation, sound and speech recognition, video search and analysis (e.g. tracking), image annotation, geometrical abstraction, image correction, semantic web, context analysis, data reliability (e.g., using Z-number (e.g., “About 45 minutes; Very sure”)), rules engine, control system, autonomous vehicle, self-diagnosis and self-repair robots, system diagnosis, medical diagnosis, biomedicine, data mining, event prediction, financial forecasting, economics, risk assessment, e-mail management, database management, indexing and join operation, memory management, and data compression.

2.20030140020Plausible neural network with supervised and unsupervised cluster analysis
US - 24.07.2003
Int.Class G06E 1/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
EOPTICAL COMPUTING DEVICES
1Devices for processing exclusively digital data
 Appl.No 10294773 Applicant CHEN YUAN YAN Inventor Chen Yuan Yan

A plausible neural network (PLANN) is an artificial neural network with weight connection given by mutual information, which has the capability of inference and learning, and yet retains many characteristics of a biological neural network. The learning algorithm is based on statistical estimation, which is faster than the gradient decent approach currently used. The network after training becomes a fuzzy/belief network; the inference and weight are exchangeable, and as a result, knowledge extraction becomes simple. PLANN performs associative memory, supervised, semi-supervised, unsupervised learning and function/relation approximation in a single network architecture. This network architecture can easily be implemented by analog VLSI circuit design.

3.20050149459Automatic creation of neuro-fuzzy expert system from online anlytical processing (OLAP) tools
US - 07.07.2005
Int.Class G06F 17/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
 Appl.No 11020542 Applicant Dintecom, Inc. Inventor Kofman Gene I.

A method for automatic generation of a Neuro-Fuzzy Expert System (Fuzzy Logic Expert System implemented as a Neural Network) from data. The method comprising a Data Interface allowing description of location, type, and structure of the Data. The Interface also allows designation of input attributes and output attributes in the Data Structure; automatic Neuro-Fuzzy Expert System generation driven by the Data; Training of the Expert System's Neural Network on the Data and the presentation of results which include new knowledge embedded in the parameters and structure of the trained Neuro-Fuzzy Expert System to a user.

4.5448681Intelligent controller with neural network and reinforcement learning
US - 05.09.1995
Int.Class G06F 15/18
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
15Digital computers in general; Data processing equipment in general
18in which a program is changed according to experience gained by the computer itself during a complete run; Learning machines
 Appl.No 07859328 Applicant National Semiconductor Corporation Inventor Khan Emdadur R.

A plant controller using reinforcement learning for controlling a plant includes action and critic networks with enhanced learning for generating a plant control signal. Learning is enhanced within the action network by using a neural network configured to operate according to unsupervised learning techniques based upon a Kohonen Feature Map. Learning is enhanced within the critic network by using a distance parameter which represents the difference between the actual and desired states of the quantitative performance, or output, of the plant when generating the reinforcement signal for the action network.

5.20090276391CREATION OF NEURO-FUZZY EXPERT SYSTEM FROM ONLINE ANALYTICAL PROCESSING (OLAP) TOOLS
US - 05.11.2009
Int.Class G06N 7/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
7Computing arrangements based on specific mathematical models
 Appl.No 12434952 Applicant Dintecom, Inc. Inventor KOFMAN Gene I.

A method for automatic generation of a Neuro-Fuzzy Expert System (Fuzzy Logic Expert System implemented as a Neural Network) from data. The method comprising a Data Interface allowing description of location, type, and structure of the Data. The Interface also allows designation of input attributes and output attributes in the Data Structure; automatic Neuro-Fuzzy Expert System generation driven by the Data; Training of the Expert System's Neural Network on the Data and the presentation of results which include new knowledge embedded in the parameters and structure of the trained Neuro-Fuzzy Expert System to a user.

6.12125146Multimodal 3D deep learning fusion system and method for reducing the need of 3D training dataset of 3D object tracking for enterprise digital twin mixed reality
US - 22.10.2024
Int.Class G06T 19/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
19Manipulating 3D models or images for computer graphics
 Appl.No 17575091 Applicant GridRaster, Inc. Inventor Yiyong Tan

A mixed reality (MR) system and method performs three dimensional (3D) tracking using 3D deep neural network structures in which multimodal fusion and simplified machine learning to only cluster label distribution (output of 3D deep neural network trained by generic 3D benchmark dataset) is used to reduce the training data requirements of to directly train a 3D deep neural network structures for non-generic user case. In one embodiment, multiple 3D deep neural network structures, such as PointCNN, 3D-Bonet, RandLA, etc., may be trained by different generic 3D benchmark datasets, such as ScanNet, ShapeNet, S3DIS, inadequate 3D training dataset, etc.

7.20250323822REAL-TIME MONITORING ECOSYSTEM
US - 16.10.2025
Int.Class H04L 41/0631
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
41Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
06Management of faults, events, alarms or notifications
0631using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
 Appl.No 19248372 Applicant Citibank, N.A. Inventor Japan Mehta

A network system to provide real-time integration and processing of user data with infrastructure data to generate solutions to user pain points. Real-time user data, including feedback and interactions, is generally not uniform and overwhelmingly large. The system provides solutions to user pain-points at scale, which, in some instances, may be unknown to the service provider. The system does so by contextually linking user data and categorizing it into standardized taxonomies. The infrastructure data is then analyzed against the taxonomies by the system's AI/ML network. The system then provides one or more pain point identifications and solutions. The system may also provide an interface to visualize the taxonomies, pain points, and trend analysis of the pain points.

8.20200160200Method and system for predictive modeling of geographic income distribution
US - 21.05.2020
Int.Class G06Q 30/02
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
QINFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
30Commerce
02Marketing; Price estimation or determination; Fundraising
 Appl.No 16194715 Applicant ADP, LLC Inventor Kurt D. Newman

A method, computer system, and computer program product that aggregates sample data regarding a plurality of factors associated with income and geographic location; performs iterative analysis on the sample data using machine learning to construct a predictive model; populates, using the predictive model, a database with predicted values of average income for a selected set of predefined geographic regions; converts the predicted values of average income in the database into percentages of observed values of average income for geographic regions within the selected set over a specified time period to create indices of average income; and rank orders the regions within the selected set according to their indices of average income.

9.20230135553AI-managed additive manufacturing for value chain networks
US - 04.05.2023
Int.Class G05B 17/02
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
17Systems involving the use of models or simulators of said systems
02electric
 Appl.No 17942061 Applicant Strong Force VCN Portfolio 2019, LLC Inventor Charles Howard Cella

A distributed manufacturing network information technology system includes a cloud-based additive manufacturing management platform with a user interface, connectivity facilities, data storage facilities, and monitoring facilities. The distributed manufacturing network information technology system includes a set of applications for enabling the additive manufacturing management platform to manage a set of distributed manufacturing network entities. The distributed manufacturing network information technology system includes an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from the distributed manufacturing network entities to optimize manufacturing and value chain workflows.

10.WO/2024/206464REAL-TIME MONITORING ECOSYSTEM
WO - 03.10.2024
Int.Class G06F 9/50
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
FELECTRIC DIGITAL DATA PROCESSING
9Arrangements for program control, e.g. control units
06using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
46Multiprogramming arrangements
50Allocation of resources, e.g. of the central processing unit
 Appl.No PCT/US2024/021707 Applicant CITIBANK, N.A. Inventor MEHTA, Japan
A network system to provide real-time integration and processing of user data with infrastructure data to generate solutions to user pain points. Real-time user data, including feedback and interactions, is generally not uniform and overwhelmingly large. The system provides solutions to user pain-points at scale, which, in some instances, may be unknown to the service provider. The system does so by contextually linking user data and categorizing it into standardized taxonomies. The infrastructure data is then analyzed against the taxonomies by the system's AI/ML network. The system then provides one or more pain point identifications and solutions. The system may also provide an interface to visualize the taxonomies, pain points, and trend analysis of the pain points.
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