65 results about "Multi criteria" patented technology

The invention discloses a bidirectional selection computing unloading method based on MEC and MCC. The method comprises steps of: sending to a network side a request to unload an operation program when it is detected that the computing amount of the operation program exceeds a threshold; receiving a unloading sequence allocated by the network side according to the request; computing local energy consumption and unloading energy consumption based on the received unloading sequence, and further computing each unloading energy consumption benefit and sending the same to the network side; and computing a local operation delay and further computing a difference between each unloading delay and local computing delay and sending the same to the network side; receiving a unloding decision matrix obtained by the network side based on the energy consumption benefit and the delay benefit, and returning a decision message; and performing unloading according to the unloading decision message. Therefore, the bidirectional selection computing unloading method based on MEC and MCC can realize the multi-criterion, multi-objective and bidirectional selection computing amount unloading of terminal linear weighting and network side analytical hierarchy process.

What is disclosed is a system and method for specifying a custom document as a multi-criteria constraint optimization problem, and a method to automatically create the specified document using existing constraint optimization solving algorithms. The present method specifies the document, its content components, its layout requirements, and its desired aesthetic criteria are expressed as elements of a constraint optimization problem which when solved, results in an automated document layout for the set of content components that satisfies not only certain primitive content and layout constraints, but which also advantageously fulfills desired design properties and which provides a way to ensure that the generated document is well designed. The method for automatic document layout comprises the steps of determining a set of variables that can be adjusted to achieve a satisfactory layout; expressing said satisfactory layout as a set of constraints on said determined set of variables wherein at least one of said set of constraints is expressed as being optimizable; and solving said constraints to find a layout which solves for the variables over the constraints. The system for automatic document layout on multi-function office equipment comprises means for document layout constraint acquisition; means for document layout variable specification which specifies a set of variables that can be adjusted to achieve a satisfactory layout; means for relationship-constraint to optimization-constraint conversion which expresses said satisfactory layout as a set of constraints on said set of variables wherein at least one of said set of constraints is expressed as being optimizable; and means for constraint optimization for solving said constraints to find a layout which solves for the variables over said constraints.

Dietary micronutrient supplement formulations for specific ages, gender, special requirements and health conditions comprising, vitamins, minerals, fish and plant oils, amino acids, enzymes, phytochemicals, herb and fruit extracts and other natural compounds grouped into morning, mid-day and evening formulas based on their synergism and antagonism with each other, their interactions with ingredients in the food consumed during each meal and their bioavailability. The dietary micronutrient formulations are optimized to meet the Recommended Daily Allowances (RDA) and Adequate Intake (AI) standards for each segment of the population with larger amounts of nutrients used in condition-specific formulas.

A robust multi-criteria minimum timing for the best torque (MBT) timing estimation method and apparatus utilizes different ionization signal waveforms that are generated under different engine operating conditions. The MBT timing criteria is calculated based upon both ionization and analog derivative ionization. Multiple MBT timing criteria are determined and combined to increase the reliability and robustness of MBT timing estimation based upon spark plug ionization signal waveforms. In a preferred embodiment, a combination of the MBT timing estimation criteria comprises a maximum flame acceleration location, a 50% burn location, and a second peak location.

Methods and systems for estimating time-varying factor exposures of either an individual financial instrument or a portfolio of such instruments, through the solution of a constrained multi-criteria dynamic optimization problem, providing an estimation error function and one or more transition error functions to be minimized over a period of time. The factor exposures relay the influence of the factors on the return of the instrument or portfolio. The estimation error function provides the estimation error at each time interval between the return of the asset collection and a sum of products of each factor exposure and its respective factor. Each transition error function provides a transition error of each factor exposure between time intervals. In one embodiment, the constraints can include a budget constraint and non-negativity bounds applying to some or all of the factor exposures. In other embodiments, the method and system can be applied to estimating any time-varying weight that is used in a model, to relay the influence of one or more independent variables on a dependent financial or economic variable, through the solution of a constrained multi-criteria dynamic problem, minimizing estimation error and transition error terms. In other embodiments, the solution of a multi-criteria dynamic problem can be used as part of a method and system to determine structural breakpoints for each factor, and also as part of a method and system for determining optimal parameters to weight the transition error functions and selecting the factors included in the model.

A robust multi-criteria minimum timing for the best torque (MBT) timing estimation method and apparatus utilizes different ionization signal waveforms that are generated under different engine operating conditions. The MBT timing criteria is calculated based upon both ionization and analog derivative ionization. Multiple MBT timing criteria are determined and combined to increase the reliability and robustness of MBT timing estimation based upon spark plug ionization signal waveforms. In a preferred embodiment, a combination of the MBT timing estimation criteria comprises a maximum flame acceleration location, a 50% burn location, and a second peak location.

A method optimizes a dose of radiation for a radio-therapy treatment subject to constraints on diagnostic parameters of the radio-therapy treatment. The method determines a point of a polytope arranged in a coordinate system of the diagnostic parameters, such that a position of the point in the coordinate system is determined at least in part by values of each diagnostic parameter. The polytope is convex with boundaries formed by intersecting half-spaces of feasible values of each diagnostic parameter specified by the constraints. The point is the closest point of the polytope to an origin of the coordinate system with regard to a weighted Euclidean distance norm. The method determines a distribution of the dose of radiation for the radio-therapy treatment using the values of the diagnostic parameters corresponding to the position of the point.

The invention relates to a single-phase ground line selection method with the function of accuracy improvement for a small-current grounding system. The method comprises: (1), whether a fault occurs is monitored; if so, a fault line section algorithm is started; (2), Fourier transform is carried out on sampling data of a zero-sequence voltage and a zero-sequence current in a fifth cycle after fault occurrence and amplitudes and phase angles of the zero-sequence voltage and zero-sequence current fundamental waves of all paths of outgoing lines are obtained; and if a neutral point passes through an arc suppression ground system, amplitudes and phase angles of harmonic waves are calculated for five times; (3), amplitude-comparing-method fault measurement is constructed; (4), a phase-comparing-method fault measurement is constructed; (5), initial-half-wave-method fault measurement is constructed; (6), wavelet-analytical-method fault measurement is constructed; and (7), a serial number of a line with the largest fault measurement is found out under each criterion; if the serial numbers are identical, the line is a fault line and a line selection result is outputted, and the line selection is completed; and if the serial numbers are different, a multi-criterion fusion method based on a D-S evidence theory is started. With the method, accuracy of the fault line selection algorithm is improved effectively.

What is disclosed is a system and method for specifying a custom document as a multi-criteria constraint optimization problem, and a method to automatically create the specified document using existing constraint optimization solving algorithms. The present method specifies the document, its content components, its layout requirements, and its desired aesthetic criteria are expressed as elements of a constraint optimization problem which when solved, results in an automated document layout for the set of content components that satisfies not only certain primitive content and layout constraints, but which also advantageously fulfills desired design properties and which provides a way to ensure that the generated document is well designed. The method for automatic document layout comprises the steps of determining a set of variables that can be adjusted to achieve a satisfactory layout; expressing said satisfactory layout as a set of constraints on said determined set of variables wherein at least one of said set of constraints is expressed as being optimizable; and solving said constraints to find a layout which solves for the variables over the constraints. The system for automatic document layout on multi-function office equipment comprises means for document layout constraint acquisition; means for document layout variable specification which specifies a set of variables that can be adjusted to achieve a satisfactory layout; means for relationship-constraint to optimization-constraint conversion which expresses said satisfactory layout as a set of constraints on said set of variables wherein at least one of said set of constraints is expressed as being optimizable; and means for constraint optimization for solving said constraints to find a layout which solves for the variables over said constraints.

The invention discloses an annular neighborhood reference contour line-based grid model adaptive layering method. According to the method, the maximum thickness and minimum thickness of layers and residual height accuracy values are determined; the annular neighborhood surface patch order of vertexes is adjustable; initial vertexes are selected from model grid vertexes to construct a reference contour line; the initial vertexes are recursively traversed, so that vertexes with the maximum Gaussian curvature are obtained; multi-criteria fitting is performed all the vertexes with the maximum Gaussian curvature are obtained; multi-criteria fitting is performed all the vertexes with Gaussian curvature extreme values, so that an annular neighborhood reference contour line can be obtained; and grid model layer thicknesses are adaptively set from bottom to top according to the non-monotonic form change rate along a layering direction; residual height analysis is performed on the thickness of each layer; the steps of the method are repeated, so that the layer thicknesses of a plurality of neighborhood reference contour lines are obtained; and iterative weighting is performed, so that the final thickness of each layer is obtained, and the splicing plane position of each layer is determined, and splicing is performed. With the method of the invention adopted, the inner and outer surface forms of a grid model can be expressed in a multi-dimension manner, the accuracy of adaptive layering and slicing can be improved, and the high-precision layering and slicing of a geometric grid model with sharp changes in the inner and outer surface can be facilitated.

A multi-city criteria correlation and cost query (MCCQ) apparatus generates potential travel destination suggestions. The MCCQ apparatus is configured with a user interface adapted to receive source and destination criteria from a user which is processed using a multi-criteria correlation processor and comparing the destination criteria to information about destinations in a city database. City data record objects and city pair objects are formed for each identified destination alternative and transmitted to an internal or third party supplier of travel cost or other pertinent travel data. City response record objects or city pair report objects are generated corresponding to the data attributes of each city data record object or city pair object and are stored in a temporary aggregation database. In various embodiments results are sorted and / or filtered to generate a multi-destination comparison report including cost or other data which may be displayed as a physical document or on a user interface component.

A multi-criteria fire detection system, comprising a plurality of sensors, wherein each sensor is capable of detecting a signature characteristic of a presence of a fire and providing an output indicating the same. A processor for receiving each output of the plurality of sensors is also employed. The processor includes a probabilistic neural network for processing the sensor outputs. The probabilistic neural network comprises a nonlinear, nor-parametric pattern recognition algorithm that operates by defining a probability density function for a plurality of data sets that are each based on a training set data and an optimized kernel width parameter. The plurality of data sets includes a baseline, non-fire, fist data set; a second, fire data set, and a third, nuisance data set. The algorithm provides a decisional output indicative of the presence of a fire based on recognizing and discrimination between said data sets, and whether the outputs suffice to substantially indicate the presence of a fire, as opposed to a non-fire or nuisance situation.

The invention discloses a basin wind-light-water system multi-objective optimization scheduling method considering downstream ecology. The method comprises the steps of obtaining the basic informationof a cascade hydropower station; acquiring the basic information of the basin wind-solar power station; establishing a multi-objective power generation optimal scheduling mathematical model considering downstream ecology for a basin wind-light-water system objective and hard constraints according to the basin wind-light-hydropower station basic information; solving the established multi-objectivepower generation optimal scheduling mathematical model by adopting the improved AR-MOEA; and performing multi-attribute decision on the obtained non-dominated scheme by adopting SMAA-2. According tothe invention, the wind-solar-hydroelectric system is decoupled, so that the feasible solution is prevented from being damaged in the evolution process; a complete Pareto leading edge is obtained, a multi-attribute decision-making model of random multi-criterion acceptability analysis (SMAA)-2 capable of considering subjective willingness of a decision maker and uncertainty of attribute information is applied, more scheme sequencing information is provided for the decision maker, and the decision making can be conducted more scientifically and reasonably.

The invention discloses a low-current single-phase grounding fault line selection method based on multi-criterion integration. The method includes that a symbol t is used for indicating transient-state component strength, and a symbol r is used for indicating reliability; the higher the reliability r is, the higher the line selection accuracy is when a wavelet and energy method is adopted, and the line selection accuracy descends as the r is reduced and descends in an accelerated manner; when r is larger than or equal to 0.8 and smaller than or equal to 1, line selection accuracy is up to 99% when a line selection method based on transient-state component is adopted; when r is larger than or equal to 0 and smaller than or equal to 0.4, line selection accuracy of a line selection method based on transient-state component descends obviously, so that the line selection method based on steady-state component is unsuitable for adoption; when r is larger than or equal to 0.4 and smaller than or equal to 0.8, an integration method is started for line selection. The method utilizes both transient-state information of fault and steady-state information, so that the defect of single criterion is overcome to certain extent, and complementing of advantages of a transient-state algorithm and a steady-state algorithm is realized.

The invention relates to a fuzzy theory based power distribution network multi-criteria integrated fault line selection method which utilizes a fuzzy theory to intelligently integrate highly complementary methods of a high frequency modal energy based fault line selection method and a fifth time harmonic wave component based fault line selection method to achieve multi-criteria integrated fault line selection based on a fuzzy theory. The method is suitable for fault line selections in difficult line selection areas such as small angle earth faults, high resistance earth faults, line end faults, and arc earth faults with high accuracy and reliability.

Similarities among multiple near-neighbor objects are searched for based on multiple criteria. A query is received for an object closest to an object provided by a user, and weights are assigned by a user to distance functions among the multiple objects at the time of the query. Each distance function represents a different criterion. The weighted average is calculated for the distance functions, and the closest object to the query object based on the weighted average for the distance functions.

The invention provides a self-adaptive license plate character segmentation method in a complex scene. The method comprises the steps of 1, obliquely correcting a license plate, 2, prelocating the interval position between the second character and the third character, and using the projection texture characteristics and combining the aspect ratio of the license plate to set multi-criteria judgment to simply and quickly search the interval position between the second character and the third character to provide stable and reliable initial position judgment information of the next step of character segmentation, and segmenting the license plate characters. Furthermore, in order to enable character segmentation to be more accurate, 0 element sections meeting the criterions are searched to update the segmentation character width and the interval width between the characters, and the character width parameters are updated again according to the searched position of the middle character. Thus, the defect that the single character is instable to segment is effectively overcome. The method can adjust segmentation parameters adaptively by quickly and accurately searching the interval position between the second character and the third character, so that the license plate characters can be segmented stably and reliably. In addition, the roughness in the complex environment is strong.

The invention discloses an improved cellular automaton traffic flow simulation analysis method based on a geographic information system. According to the method, multi-criteria judgment, logistic regression, an improved principal component analysis method and an improved decision-making tree and kernel-based learning machine method are comprehensively used for mining and extracting the transformational rule of a cellular automaton, then the improved cellular automaton is used for conducting simulation analysis of traffic flow, and corresponding traffic flow data, geographic information data and the like are used for conducting traffic flow modeling and analysis. The method is based on a geographic information system technology and a database technology to conduct unified control and management on traffic flow information, geographic information and social information in a studied area. The method achieves integrated simulation analysis and maintenance management with diagrams and texts, comprehensive inquiry, thematic map and spatial analysis and traffic flow simulation analysis, the intelligence level and the aid decision making capacity of traffic management are improved, and the method is of certain reference significance to work study in the related fields.

The invention relates to an image sample processing method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the sorting of data in an unlabeled data set according to one or more criteria which are adjusted in a self-adaptive manner, and obtaining a plurality of sorting results; carrying out fusion processing on the plurality of sorting results to obtain a target sorting result; and sending the data in the target sorting result to a target object for data labeling according to a strategy in which the data is sent according to the front-back sequence, so as to carry out model training of active learning according to a data labeling result. With the adoption of the method and the device, the expected marking result can be achieved through the marking result obtained through multi-criterion and weight self-adaptive adjustment, so that the model can be better trained according to the marking result.

The invention discloses a distribution transformer data acquisition anomaly discrimination method based on multi-criterion fusion. The method comprises the following steps: carrying out statistical analysis on breakpoints and abnormal points of the acquired data and actual field operation data conditions; respectively using a prototype clustering method, a density clustering method, a probabilitydensity method, a deep learning method and the like to discriminate abnormal values, and two-out-of-four verification results are carried out on four models, that is, two models of the four models considering that a point to be judged is an abnormal point, and the point to be judged being an abnormal point. According to the method, the problems of high difficulty, low efficiency, low real-time performance and the like when a traditional machine learning method is used for processing mass data are solved.

The invention relates to a method and a device of screening digital pulse signal. The method mainly comprises a step of respectively setting a threshold value of each criterion parameter of the digital pulse signal. The method comprises a step of using a parallel stream line working way to capture a plurality of the criterion parameters of the digital pulse signal in real time, a step of judging whether each criterion parameter conforms to the set threshold value, and a step of judging the digital pulse signal as an effective digital pulse signal when each criterion parameter of the plurality of the criterion parameter conforms to the set threshold value. Because of adoption of the real-time dealing method of the multi-criterion parallel stream line, real-time performance can be improved, the digital pulse signal can be regarded as the criterion parameter to conduct grain screening only if wave forms of the digital pulse signal are different, and therefore, pulses with different wave forms can be distinguished to the utmost.

The invention discloses a multi-criterion screening method and a multi-criterion screening device for metering errors of intelligent watt-hour meters. According to the method, first, unqualified intelligent watt-hour meters are eliminated based on metrological verification regulations, and metering errors of remaining intelligent watt-hour meters are regarded as initial credible metering errors; and then, the most suspicious metering errors are found out from the initial credible metering errors based on combination of PauTa, Chauvenet and Grubbs gross error identification criteria, and the intelligent watt-hour meters corresponding to the most suspicious metering errors are regarded as intelligent watt-hour meters on the verge of failure, and are unqualified intelligent watt-hour meters. With the method and the device, loss to users and energy supply units is avoided, the mutual trust between related units and users is improved, and moreover, the check, repair and replacement workload of related departments is reduced.

The invention discloses a method for determining the flatness ratio of a shallow and long-span city tunnel. The method includes the following steps that geological conditions of a stratum of a project are hierarchically generalized according to engineering geological investigation results; a grid model is built through numerical analysis software to simulate the tunnel construction process under the flatness ratio condition, and mechanical responses of the stratum and a supporting structure are solved; according to the requirements for the building safety and the building economical efficiency of the shallow and long-span city tunnel and environment influence control over the shallow and long-span city tunnel, an optimized objective function is proposed, and a result is simulated according to numerical values. The calculation flow of the analytic hierarchy process mainly includes the steps of building a hierarchical structure model; building a pairwise comparison judgment matrix; carrying out single hierarchical arrangement and a consistency check of the single hierarchical arrangement; carrying out comprehensive hierarchical arrangement and a consistency check of the comprehensive hierarchical arrangement. Parameter influence factors under different flatness ratios are analyzed with the analytic hierarchy process, weight comparison and calculation among multiple parameters are achieved, and a simple and convenient evaluation method is provided for multi-target or multi-criteria or structural-characteristic-free complex decision making problems.

The invention discloses an abnormal data discrimination method based on multi-criterion fusion. The method comprises the following steps: S1, preprocessing a sample data set; S2, according to four detection models in the abnormal data discrimination model, establishing sample data sets corresponding to the four detection models respectively; S3, inputting the input data set of the deep learning method into the long-short-term neural network model for training, and obtaining the trained long-short-term neural network model; S4, respectively inputting the sample data sets into the correspondingmodels, discriminating abnormal values, and obtaining the probability that each data point is discriminated as an abnormal point by the corresponding model; and S5, fusing the discrimination result probabilities of the data points discriminated by the corresponding models, and judging a fusion result according to a set judgment criterion to obtain a final abnormal data discrimination result. The data abnormal point discrimination precision is improved, the data accuracy and the available value are also improved, and accurate data guarantee is provided for operation detection business.

The invention relates to the technical field of multi-boiler coordination optimizing control for header-system boilers and discloses a multi-criterion multi-boiler coordination control system based on the energy efficiency of boilers. The multi-criterion multi-boiler coordination control system based on the energy efficiency of the boilers is provided with a boiler energy efficiency statistics and correction module, a coordination optimizing control module, a fuel system advanced control module and a fuel regulation controller. By adoption of the multi-criterion multi-boiler coordination control system based on the energy efficiency of the boilers, the problems that pressure fluctuation of a pipe network in a header-system boiler system is large, coordination between the boilers is poor, and boiler efficiency cannot be used sufficiently due to mutual suppression of the boilers are effectively solved, and the boilers can operate more economically and efficiently.

A computer-implemented technology for planning routes is described herein. In accordance with one aspect, travel data of commuters of a transportation network are provided. Continuous distributions of travel time and waiting time are generated from the travel data. The continuous distributions of travel time and waiting time are associated to a transportation graph of the transportation network. The transportation graph includes nodes corresponding to stops of the transportation network and edges interconnecting the nodes. Travel time and waiting time are associated as costs of the edges in the transportation graph. In response to receiving input parameters, expected costs of candidate routes in the transportation graph are determined in accordance with a modified multi criteria shortest path technique. The modified multi criteria shortest path technique invokes a subroutine to retrieve accurate costs of routes based at least on the costs of the edges in the transportation graph. Route recommendations are provided based on the expected costs of the candidate routes.

The invention provides a charging facility optimal planning method taking regard of customer satisfaction and distribution network reliability. The charging facility optimal planning method taking regard of customer satisfaction and distribution network reliability includes the steps: establishing an electric private car charging facility planning mathematic model in a destination mode, includingrespectively establishing an objective function and a constrained condition; performing operation simulation of the charging facility, including simulating the step size charging simulation process, such as simulating condition setting and sequential; and performing model solution, including solving the Pareto leading edge by means of a non-dominated sorting genetic algorithm and determining the optimal scheme by means of a multi-criteria compromise sorting method. The charging facility optimal planning method taking regard of customer satisfaction and distribution network reliability can coordinate the three main bodies of an operator, an electric car customer and a power distribution network to perform scheme planning, and can provide theoretical basis and technical guidance for construction of the charging facility. The planning result of the charging facility optimal planning method taking regard of customer satisfaction and distribution network reliability can satisfy the demand of a decision maker for different stress aspects, and can realize stable operation. Besides, the load level of the distribution network node of each destination accords with the daily experience afterthe charging facility is put into operation, so that the charging facility optimal planning method taking regard of customer satisfaction and distribution network reliability can be applied to electric car charging facility planning construction guidance of typical urban areas.

The invention discloses a blasting scheme multi-criteria selection method based on an improved genetic algorithm. The blasting scheme multi-criteria selection method is characterized in that a TOPSIS method is used as the universal function of GA, and two sets of criteria of overbreak depth and flying-rock distance are synthesized to sort schemes. The method includes: using a fuzzy number intuitionistic fuzzy set expressed by a structural element method to perform fuzzification on blasting scheme parameters according to fuzzy semantic division of good, hesitate and bad; randomly generating 100 kinds of blasting schemes according to actual statistical features, using the TOPSIS method as the universal function of GA, and synthesizing the two sets of criteria of overbreak depth and flying-rock distance to sort the 100 kinds blasting schemes; considering actual association problems, using a neural network to screen schemes, whose BB and FR conform to requirements, in offspring, and performing number complement of eliminated schemes. By the method widely applicable to strip mine blasting scheme selection, the optimal blasting scheme comprehensively considering the overbreak depth and the flying-rock distance can be obtained.

The invention relates to a method for applying multi-criterion fusion to feature selection of high-dimensional small sample data. The method comprises the following steps of 1) initializing a sample data set and performing clustering on the sample data set; 2) performing feature selection on clustered samples by using a Fisher Ratio method and a Relief F method; 3) fusing feature selection results, applying different penalty factors to classes, and training a PSVM classifier by adopting a fused result; 4) performing regression on the sample data set by adopting the trained classifier, removing features with minimum correlativity, and updating the sample data set; and 5) judging whether coding is ended or not, and if yes, ending the iteration process, or otherwise, repeating the steps 2-4 until the feature selection is realized. According to the method for applying the multi-criterion fusion to the feature selection of the high-dimensional small sample data, in the field of the feature selection of the high-dimensional small sample data, the feature selection speed is remarkably increased, the feature selection efficiency is remarkably improved, and the stability of a feature selection result is greatly enhanced.

The invention discloses a fault line selection method for a distribution network based on an adaptive neural fuzzy inference system. According to the method, a waveform correlation quantity, an attenuated DC component, and an energy spectrum entropy quantity of a line after fault occurrence are extracted by using wavelet packet transformation and a fault feature matrix is generated; special normalization of the fault feature matrix is carried out to eliminate influences of criterion failures under different fault conditions; with an adaptive neural fuzzy inference system, a fuzzy logic rule and a membership function parameter in the fuzzy theory are learned, so that the subjectivity of manual selection of the membership function and weight coefficient is avoided; and according to the multi-criteria fusion result, the advantage complementation between multiple criteria is realized. The method is not affected by the changes in the network structure of the distribution network and the transition resistance of the ground point, so that the reliability and safety of the system operation are enhanced substantially.