4699 results about "Business forecasting" patented technology

Here, we introduce Z-webs, including Z-factors and Z-nodes, for the understanding of relationships between objects, subjects, abstract ideas, concepts, or the like, including face, car, images, people, emotions, mood, text, natural language, voice, music, video, locations, formulas, facts, historical data, landmarks, personalities, ownership, family, friends, love, happiness, social behavior, voting behavior, and the like, to be used for many applications in our life, including on the search engine, analytics, Big Data processing, natural language processing, economy forecasting, face recognition, dealing with reliability and certainty, medical diagnosis, pattern recognition, object recognition, biometrics, security analysis, risk analysis, fraud detection, satellite image analysis, machine generated data analysis, machine learning, training samples, extracting data or patterns (from the video, images, and the like), editing video or images, and the like. Z-factors include reliability factor, confidence factor, expertise factor, bias factor, and the like, which is associated with each Z-node in the Z-web.

A statistical patent rating method and system is provided for independently assessing the relative breadth ("B"), defensibility ("D") and commercial relevance ("R") of individual patent assets and other intangible intellectual property assets. The invention provides new and valuable information that can be used by patent valuation experts, investment advisors, economists and others to help guide future patent investment decisions, licensing programs, patent appraisals, tax valuations, transfer pricing, economic forecasting and planning, and even mediation and / or settlement of patent litigation lawsuits. In one embodiment the invention provides a statistically-based patent rating method and system whereby relative ratings or rankings are generated using a database of patent information by identifying and comparing various characteristics of each individual patent to a statistically determined distribution of the same characteristics within a given patent population. For example, a first population of patents having a known relatively high intrinsic value or quality (e.g. successfully litigated patents) is compared to a second population of patents having a known relatively low intrinsic value or quality (e.g. unsuccessfully litigated patents). Based on a statistical comparison of the two populations, certain characteristics are identified as being more prevalent or more pronounced in one population group or the other to a statistically significant degree. Multiple such statistical comparisons are used to construct and optimize a computer model or computer algorithm that can then be used to predict and / or provide statistically-accurate probabilities of a desired value or quality being present or a future event occurring, given the identified characteristics of an individual patent or group of patents.

A method to generate a strategic business plan to improve operations, and to closely monitor various performance measures of an enterprise. This is accomplished employing a more comprehensive approach to maximizing profitability, increasing revenue, and explicitly considering risk. In particular, the method extends supply chain management using financial management considerations, extends financial management using supply chain management considerations, employs supply chain management techniques to improve financial management, and employs financial management techniques to improve supply chain management. The method uses information and models derived from at least one of the following business processes: accounting; cash management; funds management, financing, profitability analysis, risk management, loan management, treasury management, investments management, business development, order management, demand planning and forecasting, procurement, production planning, inventory management, transportation and distribution, and supply chain design.

The system enables business people to understand the impact of business transactions, changes and events in real-time using advanced rules and analytics to filter, categorize and interpret the significance of streams of real-time information. Most business performance analysis today is done manually and this process is a time consuming and skilled task leading to a time delay in producing the analysis. This time lag between the transaction or event happening and being able to take action on the analysis is measured in weeks or months at many companies. By blending real-time information with historical data and performance goals, this system enables business users to assess business events and collaborate within teams to drive optimal business performance. Using forecasting techniques enables business managers to predict the likelihood of achieving a particular goal without relying on manual analysis by a skilled analyst. The system automatically updates the forecast based on real-time changing data, enabling the business manager to have an up to the minute and statistically valid projection of future business performance.

Systems and methods for time series data error detection, correction, and transformation may detect gaps and anomalies in time series data, such as from a meter device, and may correct the gaps and adjust the anomalies prior to long-term record storage. Data forecasting may be used to correct the errors in the time series data. The error corrected data may be regarded as an actual set of time series data and become a base data set against which additional heuristic projections are generated. In addition, the time series data may be transformed into any number of physical and virtual device hierarchies that represent the underlying data source configurations, and may then be stored in an analytical database for further analysis. The hierarchies may be irregular and may change over time.

A decision support system for supply chain management is disclosed. In one embodiment, an organizational structure of an enterprise value chain is mock-constructed as a framework model and solutions are logically distributed through the organization in accordance with the model. Product management, demand management and inventory management are performed on an exception basis and these processes are implemented incrementally and organizationally such that enterprise activities may be tracked and monitored, by exception, at multiple levels of granularity. In a general aspect, the invention enables collaborative ordering, forecasting, inventory and replenishment management by implementing such systems through an enterprise organizational model.

Disclosed herein are systems and methods for demand forecasting that enable multiple-scenario comparisons and analyses by letting users create forecasts from multiple history streams (for example, shipments data, point-of-sale data, customer order data, return data, etc.) with various alternative forecast algorithm theories. The multiple model framework of the present invention enables users to compare statistical algorithms paired with various history streams (collectively referred to as “models”) so as to run various simulations and evaluate which model will provide the best forecast for a particular product in a given market. Once the user has decided upon which model it will use, it can publish forecast information provided by that model for use by its organization (such as by a downstream supply planning program). Embodiments of the present invention provide a system and method whereby appropriate demand responses can be dynamically forecasted whenever given events occur, such as when a competitor lowers the price on a particular product (such as for a promotion), or when the user's company is launching new sales and marketing campaigns. Preferred embodiments of the present invention use an automatic tuning feature to assist users in determining optimal parameter settings for a given forecasting algorithm to produce the best possible forecasting model.

The present invention relates to a method and system for aggregating advertising pricing data and providing that data to one or more clients. This data may be provided to the client in the form of various reports that allow a client to gauge the advertisement market more accurately and make a better informed decision when deciding to purchase advertisements. In one embodiment, a client is also able to access forecasting reports that predict the future of the advertisement market so that the client can more accurately make a decision about purchasing advertisement slots in advance.

Methods and systems are disclosed for developing a software application through requirements specification, design, effort estimation, assigning and tracking work items, development, testing, collaboration and project management. The system is structured as an integrated software development system allowing for structured, systematic and user friendly set up of requirements specification (including workflow, user interface, business rules and integrations), technical design for UI features and integrations using design patterns, automated effort estimation, automated story card and task creation. The system also provides a novel, audio-video playback capability for workflow visualization. Further, the system provides visual depiction of defects and changed items side-by-side with requirements, as well as predictive modeling of defects that allows for forecasting of defect completion rate. In the preferred embodiment, the system is delivered as a multi-tenant Software as a Service.

Historical data is measured for a computer server system. Future demand for service in the computer server system is forecast based on the historical data, and the mapping of virtual machines to physical machines is updated based on the forecast of the future demand. Measurement, forecasting, and placement modules can be employed.

Methods and apparatus for determining a value of a commercial market that can be supported by an electronic payment solution, forecasting a growth of the commercial market, and using the commercial expenditure value are disclosed. The value of the commercial market can be estimated using auditable economic data that forms part of a Gross Domestic Product (GDP) calculation. The commercial market can be estimated using intermediate inputs, inventory purchase, private fixed investments, and government expenditures. A market growth can then be estimated from the commercial expenditure value and other economic data. The commercial expenditure value can be used in a number of resource allocation and market solution processes.

A system for forecasting predicted thermal loads for a building comprises a thermal condition forecaster for forecasting weather conditions to be compensated by a building environmental control system and a thermal load predictor for modeling building environmental management system components to generate a predicted thermal load for a building for maintaining a set of environmental conditions. The thermal load predictor of the present invention is a neural network and, preferably, the neural network is a recurrent neural network that generates the predicted thermal load from short-term data. The recurrent neural network is trained by inputting building thermal mass data and building occupancy data for actual weather conditions and comparing the predicted thermal load generated by the recurrent neural network to the actual thermal load measured at the building. Training error is attributed to weights of the neurons processing the building thermal mass data and building occupancy data. Iteratively adjusting these weights to minimize the error optimizes the design of the recurrent neural network for these non-weather inputs.

A method of forecasting, allocating and scheduling in a single or multi-site skills-based contact or call center environment organized into a hierarchy of zero or more business units at a first, upper level, one or more contact types at a second, intermediate level, and one or more management units at a third, lower level. A user creates (a) a set of given contact allocations that define how contacts are distributed from a given business unit to multiple contact types, and (b) a set of given requirement allocations that define how agent requirements are distributed from a contact type to one or more management units. Agent availability by contact type is then predicted to generate agent availability data. Thereafter, forecasted contacts and forecasted agent requirements are allocated based on the given contact and requirement allocations as well as the agent availability data. Preferably, the agent availability data is predicted using a schedule simulator and is characterized by contact type for agents in the same skill group.

The Accounts Receivable System's Credit Inquiry Module reviews payment history and performs credit inquiries by analyzing data from internal and external sources. The Credit Inquiry Module uses this analysis for credit management and customer contact. The Credit Inquiry Module based on customer payment data predicts overall cash forecasting for the client. The Credit Inquiry Module is utilized for account reconciliation and audit verification for tracking transactions at the customer level.

An apparatus and system to manage monitored traffic density in relationship to spatial locational flow rates. The system includes a variety of mobile and / or stationary transmitting and receiving comm-devices utilizing certified comm-devices equipped Avics iChipset arranged in a polarity of vehicles, in communication with stationary and / or mobile hub comm-devices and / or other certified comm-devices, strategically arranged within and / or along one or more roadways and in communication with a server channel networked to a central server. Configured to receive and / or transmit encrypted traffic data from the diversity of stationary and / or mobile transmitting and receiving comm-devices over the network, update traffic data in the non shared database, continuously calculate optimal traffic density flow for one or more of vehicles traveling along the one or more roadways based on the updated vehicular transit data, transmitting variations in speed adjustments in a network infrastructure to one or more vehicles; adjusting traffic light intersections based on traffic density traversing such roadways based on the optimal traffic flow suggestions combined with Predicated Traffic Artifacts transmitted via system generated encrypted digital comm-advice directives; and in turn share extracted and / or transmitted data with each state an federal DOT departments and other stack holders, including insurance companies and vehicle manufacturers and dealers with information to assist with making the traffic network safer. The present invention presents an Intuitive ITS engaged in Channeled Vehicular Telematics conveying statistical data, from an plurality of network devices, providing informational services forecasting safety-critical features and more, in return gathering and disseminating connected channelled intelligence between vehicles from within and surrounding infrastructures and other shareholders. Such data includes vehicle Phase-Change Spatial analytics from traffic congestion artifacts, along with Consumption Variable Analysis that provides real-time Energy Summation Data from combined vehicle exhausted energy by adjusting traffic flow based on traffic density in relationship with the human factor, vehicle capacity to navigate and topography and climatic variations in relationship with any area being traversed, and most importantly the use of the unique string identification. USIN acknowledged as ‘tMarker Audit Trail’ or simply tMarker Trail as to data inception creation point. Managed within a secure private network infrastructure, each comm-device is synchronized with localized cloud servers in communication will a central server. This invention embarks on a new era in vehicle management, further enhancing time sensitive movements, leaving no doubt as to Vehicle Symmetry Orientation, especially once you move your vehicle and additional particulars currently not beyond the scope of this art presented herein. ITTS will throughly reduce the worlds fossil fuel supply consumption rate and on many other fronts availed by extracted data, transmitted from each vehicles onboard vehicle processor equipped with Avics iChipSet on certified comm-devices, reducing navigational concerns to elementary variables creating a safe traffic network.

The invention discloses a motion vector forecasting method in a resolution quantizing structure, wherein, forecasting motion vectors of macro blocks in enhancement layers are acquired by utilization of relativity of motion vectors of a time domain, a space domain and an interlayer domain. The realization process is that: on the time domain, candidate motion vectors of the time domain are acquired from motion vectors of macro blocks with the same position with the prior frame; on the space domain, candidate motion vectors of the space domain are acquired from motion vectors of adjacent blocks; on the interlayer domain, candidate motion vectors of the interlayer domain are acquired from corresponding motion vectors with low space domain resolution hierarchy; candidate motion vectors with minimum motion estimation cost are selected to be forecasting motion vectors by selection among the candidate motion vectors of the time domain, the space domain and the interlayer domain. The invention has the advantages of capability of acquiring more accurate forecasting motion vectors, capability of compressing code rate of motion vectors, and obtaining of performance gain.

A data processing system and method for developing predictions regarding future asset price movements, based on pattern detection in a time sequence of historical price data. The system includes computer implementation of a kernal regression to effect a smooth estimator of the non-linear price-time relationship. As tested against known patterns, the system provides an expectation regarding a future price movement.

An automated system (100) and method for knowledge based performance management for an organization. After extracting data from existing narrowly focused systems, mission measures and organization levels are defined for one or more organizations. The elements, factors and risks that contribute to mission measure performance by organization level and organization are systematically defined and stored in a ContextBase using up to six context layers. ContextBase information is extracted for specified combinations of context layers, organization levels and organizations as required to produce complete context frames. The complete context frames are then used by a series of applications for reviewing, analyzing, forecasting, planning and optimizing organization performance.

An airborne network system (ANS) on a member aircraft receives incoming geo-referenced atmospheric data regarding atmospheric conditions from other member aircraft and can re-transmit the data to other members. An air data system senses local pressure and temperature conditions. A navigation system calculates geo-referenced aircraft position. An inertial data system senses member aircraft attitude, angular rates and accelerations. A data processing system (DPS) generates the member aircraft's perspective of the atmospheric conditions, based on input data from the above-mentioned systems. Network directed DPS output atmospheric data is provided to the ANS to be transmitted to other airborne network systems positioned on other member aircraft. An airborne display system is adapted to receive crew directed DPS output atmospheric data and in response thereto display desired atmospheric forecast conditions. An airborne caution / advisory system receives the crew directed DPS output atmospheric data and alerts the pilot(s) of hazardous flight conditions.

An integrated patient monitoring and control system is provided which includes a closed-loop control system for monitoring and adjusting the heparin infusion rate for a patient. The system includes a processor which uses a dynamic patient model that is continuously adjusted based on the patient's aPTT measurements to calculate an optimal heparin infusion rate to achieve an operator-input aPTT target range. The processor also includes a forecasting model to calculate the optimum sample time interval for measuring the patient's aPTT to calculate a new infusion rate. An automated sampling system, which includes a storage device for storing a series of assay devices, an advancement mechanism for moving the assay devices to a sample area, and a measurement device for analyzing a sample dispensed on the assay, is provided. The sampling system is used to repeatedly measure the patient's aPTT according to the sample time interval determined by the processor.

A novel Internet-based consumer product information system and method for use in retail shopping environments, wherein each Web-enabled bar code driven consumer product information kiosk deployed therewithin embodies e-mail messaging capabilities which enable consumers to automatically save and record the URLs of CPI-related Web documents within the message field of a preformatted e-mail message that is transmitted from a retailer-operated e-mail server, to a remote e-mail address specified by the consumer within the retail shopping environment. One or more central e-mail servers are used to collect copies of e-mail documents (and records thereof) transmitted from the Web / e-mail enabled kiosks within each retail shopping environments, for consumer and demographic information analysis, compilation, and storage within RDBMSs that are made accessible to retailers and manufacturers alike for use in product marketing, sales forecasting, customer intelligence, and like operations which enable more effective marketing of consumer products and services in both physical and electronic forms of commerce.

The present invention describes the use of a space-based Extremely Low Frequency (ELF) magnetic field detector in conjunction with ground-based network of ELF magnetic field detectors. In particular, a space based ELF detection system can be used to perform a wide area search and find precursor earthquake signals in both known and unknown earthquake zones, and a ground-based network of ELF detectors can be used to verify that the signals are indeed earthquake generated signals. The use of this invention will minimize cost and manpower necessary to effectuate an accurate and reliable earthquake detection system.

The present invention relates to utilizing identity and context-sensitive decision-making for handling communications, including, channel selection, routing, and rescheduling operations. The systems and methods provide a service that allows users to assess preferences regarding real-time call handling and performs dynamic decision-making about the best timing and channel for interpersonal communication. This service can be based on various cost-benefit analyses (e.g., basic and extended) that consider cost of interruption and preferences of contactors and contactees to guide communications, and / or on decision-making under uncertainty. Statistical models that are learned from data are joined with user preferences to generate expected costs of interruption for office activity and over time, based on a user's activities, locations, calendar information and preference assessments. In addition, statistical forecasting provides presence and availability predictions. The foregoing can provide an enhanced interpersonal communication system that can maximize the value and minimize the cost of communication among people.

Here, we introduce Z-webs, including Z-factors and Z-nodes, for the understanding of relationships between objects, subjects, abstract ideas, concepts, or the like, including face, car, images, people, emotions, mood, text, natural language, voice, music, video, locations, formulas, facts, historical data, landmarks, personalities, ownership, family, friends, love, happiness, social behavior, voting behavior, and the like, to be used for many applications in our life, including on the search engine, analytics, Big Data processing, natural language processing, economy forecasting, face recognition, dealing with reliability and certainty, medical diagnosis, pattern recognition, object recognition, biometrics, security analysis, risk analysis, fraud detection, satellite image analysis, machine generated data analysis, machine learning, training samples, extracting data or patterns (from the video, images, and the like), editing video or images, and the like. Z-factors include reliability factor, confidence factor, expertise factor, bias factor, and the like, which is associated with each Z-node in the Z-web.

A novel Internet-based consumer product information system and method for use in retail shopping environments, wherein each Web-enabled bar code driven consumer product information kiosk deployed therewithin embodies e-mail messaging capabilities which enable consumers to automatically save and record the URLs of CPI-related Web documents within the message field of a preformatted e-mail message that is transmitted from a retailer-operated e-mail server, to a remote e-mail address specified by the consumer within the retail shopping environment. One or more central e-mail servers are used to collect copies of e-mail documents (and records thereof) transmitted from the Web / e-mail enabled kiosks within each retail shopping environments, for consumer and demographic information analysis, compilation, and storage within RDBMSs that are made accessible to retailers and manufacturers alike for use in product marketing, sales forecasting, customer intelligence, and like operations which enable more effective marketing of consumer products and services in both physical and electronic forms of commerce.

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

A computer-implemented process of developing a person-level cost model for forecasting future costs attributable to claims from members of a book of business, where person-level data are available for a substantial portion of the members of the book of business for an actual underwriting period, and the forecast of interest is for a policy period is disclosed. The process uses development universe data comprising person-level enrollment data, historical base period health care claims data and historical next period claim amount data for a statistically meaningful number of individuals. The process also provides at least one claim-based risk factor for each historical base period claim based on the claim code associated with the health care claim and provides at least one enrollment-based risk factor based on the enrollment data. The process also develops a cost forecasting model by capturing the predictive ability of the main effects and interactions of claim based risk factors and enrollment-based risk factors, with the development universe data through the application of an interaction capturing technique to the development universe data.

A method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and / or magnetic stimulation.