1385 results about "Sensitivity analysis" patented technology

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building / editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

It is an object of the present invention to provide a method, an apparatus and a program having high optimization precision and capable of obtaining an answer required by a designer in a short time by combining optimization between individual transistors and optimization as the entire circuit, or by appropriately combining judgment of an operation region, an analysis of the operation region and a SWEEP sensitivity analysis when the optimization is carried out. An optimizing designing apparatus of an integrated circuit for designing a circuit, comprises operation region judging means for adjusting an operation region (linear region, saturation region) of the circuit, operation region analysis means for displaying liner characteristics (Ids-Vgs characteristics) of the circuit and saturation characteristics (Ids-Vds characteristics) of the circuit, and SWEEP sensitivity analysis means for displaying variation in output characteristics of the circuit.

An automated analyzer for analyzing patient samples. The analyzer includes a plurality of cuvettes, which allow the samples to be mixed with various reagents. The analyzer includes one or more detectors, including a detector adapted to detect luminescence of the reaction mixture in the cuvettes. The analyzer allows for various diagnostic assays to be performed on a single system, and provides for high-sensitivity analysis at faster speeds.

The present invention includes a method and system for determining the profile of a structure in an integrated circuit from a measured signal, the signal measured off the structure with a metrology device, selecting a best match of the measured signal in a profile data space, the profile data space having data points with a specified extent of non-linearity, and performing a refinement procedure to determine refined profile parameters. One embodiment includes a refinement procedure comprising finding a polyhedron in a function domain of cost functions of the profile library signals and profile parameters and minimizing the total cost function using the weighted average method. Other embodiments include profile parameter refinement procedures using sensitivity analysis, a clustering approach, regression-based methods, localized fine-resolution refinement library method, iterative library refinement method, and other cost optimization or refinement algorithms, procedures, and methods. Refinement of profile parameters may be invoked automatically or invoked based on predetermined criteria such as exceeding an error metric between the measured signal versus the best match profile library.

The invention discloses a power system load modelling method, including the steps that: A, load classification based on daily active load curve; B, load modelling based on statistic synthesis method; C, load model parameter sensitivity analysis and range analysis based on simulation analysis; D, load model parameter node identification based on genetic algorithm, namely node identification is carried out by taking fitted local disturbance data as target, setting low sensitivity parameter value as statistic synthesis method surveying parameter value and adopting the genetic algorithm, so as to obtain multiple groups of load model parameters; E, load model parameter wide area check based on WAMS, namely load model parameter check is carried out by taking the multiple groups of solutions identified by node as initial value and taking accurate fitting on system wide area dynamic characteristic as target, so as to obtain unique solution capable of reflecting wide area dynamic characteristic when system is subject to disturbance. The invention solves the problems of multiple solutions and identifiability of overall measuring identifying method by load point classification and load model parameter aggregation and has popularization and application values.

Many business problems involve too many complex and interacting variables for a person to solve them, unassisted. Linear programming, statistical and probability analyses provide effective tools for solving such problems, but until now, use of these tools has not been practical for persons without extensive mathematical training. The present invention provides an understandable user interface to these tools, enabling even mathematically unsophisticated users to effectively solve complex problems. The invention also incorporates sensitivity analyses, thereby permitting the user to explore how changes in input data would affect the results of the program calculations. In addition to a data-input program module, respective program modules are disclosed for managing a company product line, a securities portfolio, and a short-selling portfolio.

The present invention relates to systems and methods for calculating a segment's sensitivity to price changes. A histogram distribution is generated for transaction frequency by price as the initial part of the sensitivity analysis. The shape of this histogram may be used to extrapolate a sensitivity measure. This can be done in two distinct ways: statistical regression or slope approximation. For statistical regression, the inverse of the cumulative distribution function is first calculated. The slope of this function is determined to be the sensitivity; the steeper the curve the more sensitive the segment is to price changes. The second technique approximates the slope of the right hand side of the histogram in order to determine sensitivity.

The invention discloses a microgrid energy management system which comprises an information collection and data preprocessing unit, a network analysis unit and an energy optimization unit, wherein the information collection and data preprocessing unit performs data mining preprocessing on information, collected by SCADA / PMU mixed measurement, by adopting a CIM model and combining historical section management, the network analysis unit is used for realizing mixed measurement-based microgrid state estimation on the basis of network topology analysis, performing risk analysis and assessment and sensitivity analysis to realize early warning and warning for failure threat, and adopting corresponding precautionary measures or performing emergency control, and the energy optimization unit is used for performing microgrid energy optimization scheduling by combining forecast information and system operation analysis according to the information of the microgrid state estimation. The invention also provides a method which adopts the microgrid energy management system to perform microgrid energy management. The functions of the microgrid energy management system are further perfected, and the system safety, the power supply reliability and the system control accuracy and effectiveness of a microgrid are improved.

Heating is a significant factor in residential gas-energy usage. Saving energy on heating is receiving increasing attention with rising energy prices and the Kyoto Protocol on reducing greenhouse gas emissions. Energy awareness and energy efficiency hereby become important qualifications for human behavior and residential building codes, and become a factor in the evolution of the global climate. Here, we describe a novel measurement and validation system for domestic gas-energy usage in combination with primary weather data. We disclose a gas-energy observatory which visualizes human behavior in gas-energy consumption associated with domestic facilities, and measures home energy efficiency by calorimetry. Weather-sensitivity analysis quantifies energy-usage as a function of small variations in room temperature and home energy efficiency. Weather-sensitivity data can be used to calculate changes in room-temperature settings or improvements in home insulation for a desired reduction in CO2-output. By public dissemination of its primary weather data, it creates in dual-use at no additional cost a novel in-situ climate observational systems with unprecedented wide-area coverage and spatial resolution.

“Determining Validity Ranges of Query Plans Based on Suboptimality” A method for approximating a validity range for a domain of cardinalities of input to an optimal query plan is provided. Such a validity range is iteratively approximated using a modified Newton-Raphson method to find roots of cost functions for optimal and alternative query plans, respectively. The Newton-Raphson method is combined with a method of incrementing roots of cost functions, known as input cardinalities, such that discontinuous and non-differentiable points in cost functions are avoided. In this manner, input cardinalities remain within a domain for which a valid range can be specified. Additionally, a robustness measure is determined by a sensitivity analysis performed on an approximated validity range. Using a robustness measure provided by a sensitivity analysis and resultant validity range and, query plan sub-optimality detection is simplified, re-optimization is selectively triggered, and robustness information is provided to a system or user performing corrective actions.

Techniques for controlling delivery of a therapy to a patient by a medical device, such as an implantable medical device (IMD), involve a sensitivity analysis of a performance metric. The performance metric may relate to efficacy or side effects of the therapy. For example, the performance metric may comprise a sleep quality metric, an activity level metric, a movement disorder metric for patients with Parkinson's disease, epilepsy, or the like. The sensitivity analysis identifies values of therapy parameters that defines a substantially maximum or minimum value of the performance metric. The identified therapy parameters are a baseline therapy parameter set, and a medical device may control delivery of the therapy based on the baseline therapy parameter set.

A system and method that does trustworthy multi-objective structural synthesis of analog circuits, and extracts expert analog circuit knowledge from the resulting tradeoffs. The system defines a space of thousands of possible topologies via a hierarchically organized combination of designer-trusted analog building blocks, the resulting topologies are guaranteed trustworthy. The system can perform a search based on a multi-objective evolutionary algorithm that uses an age-layered population structure to balance exploration vs. exploitation, with operators that make the search space a hybrid between vector-based and tree-based representations. A scheme employing average ranking on Pareto fronts is used to handle a high number of objectives. Good initial topology sizings are quickly generated via multi-gate constraint satisfaction. To explicitly capture expert analog design knowledge, data mining is employed on the sized circuits to: automatically generate a decision tree for navigating from performance specifications to topology choice, to do global nonlinear sensitivity analysis, and to generate analytical models of performance tradeoffs.

A lightweight forward design method and system of automobile structure based on multi-performance constraints is disclosed. The finite element analysis model of automobile body structure is established by using finite element modeling technology. The typical force transfer path of automobile structure is identified by using topology optimization technology and the bending / torsional rigidity performance of automobile body is taken as constrained working condition, and lightweight design in conceptual stage is carried out. Then the strain energy analysis and the material thickness sensitivity analysis are carried out by using the sensitivity analysis technology, and the weak links and the critical design area of the vehicle body are found. Topography optimization is used to improve vehicle performance; Finally, based on business integration optimization software, The multi-performance target of automobile body is analyzed by integrated simulation, and the correlation between design parameters and performance, performance and performance is studied by using DOE sampling and data mining technology, and then the lightweight design of automobile body structure considering multi-disciplinary performance is carried out, which reduces the quality of automobile body structure, improves product performance, shortens R D and manufacturing cycle, and saves cost.

The invention provides a building construction quality safety online risk assessment system. The system comprises: a project management module, an engineering information module, a risk identification module, a risk assessment module and a dynamic risk assessment module. The project management module is used for information management of a building construction project and a case library. The engineering information module is used for general situation information management of the building construction project. The risk identification module can automatically identify a risk event and a risk factor according to an engineering general situation information system so as to form a risk list and a risk tree. The risk assessment module carries out data reasoning according to comparison of the project general situation information and the similar project information in a database, estimates a risk event generation probability and losses, determines a risk grade, determines an importance degree of the risk factor through a sensitivity analysis and automatically searches the database so as to obtain a pre-control measure and form a risk assessment report. The dynamic risk assessment module is used for risk tracking, monitoring and situation evaluation during an engineering construction process.

An advanced Geographic Information System (GIS) providing modeling, analysis, Multicriteria Decision Analysis (MCDA), data visualization, data sonification, web interface, risk management, sensitivity analysis, and telemetry capabilities is described. Telemetry can be provided by field sensors, field video, and / or field audio, and can be recorded or provided live in either direct or analyzed form. Data visualizations can be displayed along with GIS graphics, and can be superimposed or otherwise integrated with GIS graphics. GIS graphics can be used as the basis for an interactive user interface for other parts of the system. Web interfaces can support remote use, server based implementations, and / or collaboration. Advanced multi-channel data sonification can be used to prevent visual overloading of GIS graphics and interactions with it. The system can include rich data processing capabilities and interconnections of these so as to facilitate powerful data visualization and sonification results and can support multidimensional user interface devices.

In the Network Global Expectation Model, expectation values evaluated over the entire network are used as a multi-moment description of the required quantities of key network and network element (NE) resources and commensurate network costs. The Network Global Expectation Model naturally and analytically connects the global (network) and local (network element) views of the communication system, and thereby may be used as a tool to gain insight and very quickly provide approximate results for the preliminary evaluation and design of dynamic networks. Further, the Network Global Expectation Model may serve as a valuable guide in the areas of network element feature requirements, costs, sensitivity analyses, scaling performance, comparisons, product definition and application domains, and product and technology roadmapping. The network is arranged as a multiple tier network of nodes in order to apply the analysis methods of the Network Global Expectation Model. The analytical method is developed to include non-uniform demands on the network.

The invention, which belongs to the shale gas development field during oil-gas field development, discloses an initial productivity prediction method of a shale gas horizontal well. The method comprises the following steps: establishing a well logging interpretation and construction fracturing parameter database of a shale gas horizontal well; carrying out thickness weighting calculation to obtain relevant single-well geological and engineering parameters; carrying out a multi-factor sensitivity analysis by using an orthogonal test method to determine main controlling factors influencing the productivity of the shale gas horizontal well; and establishing an initial productivity prediction equation of the shale gas horizontal well based on multiple regression linearity and predicting the productivity of a newly-drilled shale gas horizontal well by using the equation as a model. On the basis of comparison of a predicted result and an actual measurement result, the relative error is less than 20%, so that the productivity precondition precision based on the method is high.

A method for controlling the synthesis gas composition obtained from a steam methane reformer (SMR) that obtains its feedstock as product gas directly from a steam hydro-gasification reactor SHR). The method allows control of the H2 / CO syngas ratio by adjusting the hydrogen feed and the water content of feedstock into a steam hydro-gasification reactor that supplies the SMR. The steam and methane rich product gas of the SHR is generated by means of hydro-gasification of a slurry of carbonaceous material and water. The mass percentages of the product stream at each stage of the process are calculated using a modeling program, such as the ASPEN PLUS™ equilibrium process. By varying the parameters of solid to water ratio and hydrogen to carbon ratio, a sensitivity analysis can be performed that enables one determine the optimum composition of the slurry feedstock to the SHR to obtain a desired syngas ratio output of the SMR. Thus one can adjust the hydrogen feed and the water content of feedstock into the SHR that supplies the SMR to determine the syngas ratio output of the SMR.

The invention provides an identification method of transient state power-angle stable key transmission cross-section corresponding to an expected fault, belonging to the field of electric power systemdispatching automation. Based on a transient state power-angle stable quantitative analysis theory and method, namely extended equal-area criterion (EEAC), the method identifies the key transmissioncross-section corresponding to the expected fault to provide decision support for the electric power system dispatching operation and control. The method comprises the following steps: carrying out atime domain simulation in an expected fault scene based on the operation state, model and parameters of an electric fence; identifying a generator critical group with stable transient state power-angle by EEAC based on simulation track and calculating the participation factor of the generator; calculating the sensitivity to the cross-section components power change caused by the output of each generator in the generator critical group by a power flow sensitivity analysis method; and taking the sum of products of the participation factor in each generator of the generator critical group and corresponding sensitivity of the cross-section component as a judging indicator of the transient state stable key transmission cross-section corresponding to the fault.

The invention provides a side slope stable reliability sensitivity analysis method based on Monte Carlo simulation. The side slope stable reliability sensitivity analysis method based on the Monte Carlo simulation includes: step 1, constructing a joint probability density function of uncertain parameters; step 2, using a Monte Carlo simulation method to obtain a side slope failure probability, and obtaining a failure sample; step 3, designing various sensitivity analysis schemes, and respectively constructing joint probability density functions of uncertain parameters under all the sensitivity analysis schemes; step 4, obtaining side slope failure probabilities under all the sensitivity analysis schemes; step 5, obtaining a variation trend of the side slope failure probabilities along with statistical characteristics of the uncertain parameters according to the side slope failure probabilities under all the sensitivity analysis schemes. The side slope stable reliability sensitivity analysis method based on the Monte Carlo simulation is wide in application range, simple in computation process, high in computation efficiency, and capable of effectively revealing a response regularity between the reliability level of a side slope and the statistical characteristics of the uncertain parameters, and has certain guiding significance for side slope risk control, design optimization and the like.

The invention relates to test data generating device and method based on a binary program. The test data generating method mainly comprises the following steps of: operating a dynamic symbol executing program for the state information of the binary program which corresponds to a guide path and initial test data; obtaining corresponding conditional jump address information according to an operating result; matching an actual operation path which corresponds to the initial test data with the guide path on the basis of the obtained conditional jump address information; and generating the test data which corresponds to the actual operation path and is matched with the guide path. The invention combines the advantages of static analysis and dynamic analysis and can enhance the availability and the accuracy of symbolic execution and the accuracy degree of the generated test data and generate the test data used for carrying out path sensitivity analysis on a key code segment, thereby effectively mitigating the problem of path explosion in the symbolic execution.

The invention discloses a blower fan load high-efficiency assessment system. The blower fan load high-efficiency assessment system includes a querying module of a load simulation database, wherein the querying module can query and manage simulation input data and load data of all types of research and development machines, such as a unit boundary condition, tower size, blade design data, a complete machine Bladed model, and load data of main parts, blades, and a tower; a load comparison and sensitivity analysis module which can perform comparison analysis on boundary conditions, main part loads, and blade and tower loads of different projects, and perform sensitivity analysis on loads of identical projects with different boundary conditions; and a unit load strength applicability assessment module which can interpolation-calculate a load corresponding to a specific site based on mass load simulation data change for boundary condition parameters such as the air density, the annual average wind speed, the turbulence intensity, wind shear, and the inflow angle, and can perform strength assessment on parts according to strength assessment margin of a reference project. The blower fan load high-efficiency assessment system can improve the calculation efficiency of a blower fan generator unit load, can shorten the life period, and can save cost.

The invention discloses an evaluation method of reliability of an aerospace electronic product based on a failure mechanism. On the basis that an analysis method with a combination of physical simulation and a test is adopted, a physical simulation model of the electronic product is constructed, the means such as sensitivity analysis, Monte Carlo analysis, and stress analysis are adopted, and product key elements are identified and in combination with actual working conditions of the elements, a failure mechanism analysis is conducted. Currently, the failure mechanism analysis aiming at the elements is a means used for analyzing a failure reason after a failure occurs during the test or in the using process of the electronic product, thus pertinent improvement is conducted on the product, the service life of the product is prolonged, and the reliability of the product is improved; the failure mechanism analysis aims at finding key characteristic parameters which affect the service life and the reliability of weak elements as an independent variable of the reliability model.

The invention discloses a recognition method of a critical geometrical error source of a machine tool and belongs to the technical field of machine precision designing. The recognition method of the critical geometrical error source of the machine tool is characterized by comprising the steps that the machine tool is abstracted into a multi-body system according to the structure and motion characteristics of the machine tool, relevance of parts of the machine tool is described by a topological structure and a low-order body array, a generalized coordinate system is built in the multi-body system, coupling relationship of error amounts of parts of the machine tool is described by a homogeneous transformation matrix, a characteristic matrix and a motion equation of the relative movement between two adjacent bodies of the machine tool are elicited, a precision model of a machining center is built, an ordinary mathematical model used for error sensitivity analysis of a four-shaft machine tool is built with a matrix differential method according to the precision model of the precision horizontal machining center, influence degrees on the whole space error of all error elements are compared by calculating the geometrical error sensitivities of all parts, and finally the critical error source influencing the machining precision of the machine tool is recognized.

A set of payment card transactions including a sparse set of fraudulent transactions is normalized, such that continuously valued literals in each of the set of transactions are transformed to discrete literals. The normalized transactions are used to train a classifier, such as a neural network, such that the classifier is trained to classify transactions as fraudulent or genuine. The fraudulent transactions in the set of payment card transactions are clustered to form a set of prototype transactions. Each of the discrete literals in each of the prototype transactions is expanded using sensitivity analysis using the trained classifier as an oracle, and a rule for identifying fraudulent transactions is generated for each prototype transaction based on the transaction's respective expanded literals.

In designing supersonic aircrafts, a method of designing a natural laminar flow wing is provided which reduces friction drag by delaying boundary layer transition under flight conditions of actual aircrafts. A target Cp distribution on wing upper surface, suited to natural laminarization in which boundary layer transition is delayed rearward in desired Reynolds number states, is defined by a functional type having as coefficients parameters depending on each spanwise station, a sensitivity analysis employing a transition analysis method is applied to the parameters, and a search is performed for the optimum combination of parameters to delay transition rearward.

Systems and methods are disclosed for analyzing building sensor information and decomposing the information therein to a more manageable and more useful form. Certain embodiments integrate energy-based and spectral-based analysis methods with parameter sampling and uncertainty / sensitivity analysis to achieve a more comprehensive perspective of building behavior. The results of this analysis may be presented to a user via a plurality of visualizations and / or used to automatically adjust certain building operations. In certain embodiments, advanced spectral techniques, including Koopman-based operations, are employed to discern features from the collected building sensor data.

The invention relates to an integration coordination control method of the early security and stability warning, prevention and control and emergency control of large power grids and includes the following steps: various steady data and dynamic data of large power grids are gathered; the present modes are matched with serious historical fault forms in real time as the online appending presupposition fault of stable analytic calculation; the curve data is mined with area methods such as expansion after the power grid is simulated to extract the stable quantitative characteristics of a system; when the power grid has positive secure stability margins, the stability margins and relevant sensitivity analysis technology are used for calculating the limit output and load of a generator and the limit power of a stability section; when the power grid has negative secure stability margins, the prevention and control and emergency control are calculated to confirm the amount of prevention and control measures and control cost thereof as well as the amount of emergency control measures and control cost thereof; the optimum combination of the prevention and control and emergency control are automatically searched. The integration framework of the optimization and coordination of the early security and stability warning, prevention and control and emergency control is built.