371 results about "Decision matrix" 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.

An automated traffic control system provides real time alternative traffic flow solutions to address traffic congestion on a roadway. A process will pick routes to scan for real-time statistics on the traffic conditions and calculate an average vehicle speed (AVS) for that route, road, highway, etc. If the AVS drops below a historical threshold, a decision matrix is created, whereby all the real-time data is compared with historical data and provides an ideal or best alternative route for “route X”. The operator is provided this information within seconds and is allowed to make a decision to “accept pr decline” the proposed changes in routes. If the proposed changes are accepted, the changes begin to occur automatically such as but not limited to updating electronic signage, changing traffic control signals (all green to keep traffic moving), moving electronic barriers, etc.

Systems and methods for developing business rules for decision engines are provided. A user interface may be provided for inputting business rules and one or more sets of data. The business rules may be in a format of a decision table and / or a decision matrix. The business rules may be applied on the sets of data to generate rule feedback, using an internal decision engine, which denotes coverage of the data by the business rules. The rule feedback may be provided on the user interface, such as with a data coverage indicator utilizing colors, and / or data coverage statistics. The business rules may be defined and validated prior to implementation in an external decision engine. Importable business rules that are adapted to be executed by the external decision engine may be generated based on the business rules. Components of the system may be executed locally on a personal computer.

A virtual device is created from a network of personal wireless devices so that they can query each other regarding the availability and sharing of resources. Each wireless device has a low power, limited range transceiver that enables it to communicate with other wireless devices similarly equipped. Once the network of wireless devices is formed, each wireless device stores a decision matrix that is made up of each wireless device's identification and the available resources within that device. A wireless device can then borrow those resources when an event occurs with that device that requires a resource that cannot be handled by the device.

The present invention relates to the allocation of resources to address scope items against an iteration of a project based on a rule set described by a decision matrix and threshold values. Rather than changing work item start and end dates based on resource availability, the present invention adds, modifies, and removes content from a collection of scope item items and allocates them to resources based on the skills required, the priority, estimated work and target iteration of the scope item items.

The invention discloses a method for comprehensively evaluating the electric energy quality by applying a TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) of a grey correlation coefficient matrix, which comprises the following steps of: taking electric energy quality data at all time intervals and standard data at all grades as an original decision matrix; determining subjective weights through an improved AHP (Analytic Hierarchy Process); determining objective weights through an entropy method; establishing a least square method decision model to obtain a comprehensive weight, so that the deviation of decision results under the subjective weights and the objective weights of all indexes is the least; carrying out standardization and weighted standardization on the decision matrix and obtaining the grey correction coefficient matrix by utilizing the grey theory; taking the grey correction coefficient matrix as a decision matrix of the TOPSIS to obtain the distance between positive ideal solutions and negative ideal solutions of all schemes and the relative closeness of the positive ideal solutions and the negative ideal solutions; and comparing the electric energy quality closeness at all the time intervals with the standard closeness at all the electric energy quality grades to finally obtain the electric energy quality grades at all the time intervals. With the adoption of the method, the electric energy quality evaluation result can be objectively and reasonably obtained under the situation of poor information, so that the practicability and the feasibility are stronger.

The invention relates to a method for comprehensively evaluating network performance based on subjective and objective combination evaluation, which comprises the following steps: A, selecting a comprehensive evaluation index of the network performance, collecting network performance data, and establishing a decision matrix; B, evaluating the network performance by using a subjective analysis method, and calculating the comprehensive evaluation value of the network performance; C, evaluating the network performance by using an objective analysis method, and calculating the comprehensive evaluation value of the network performance; and D, performing combined evaluation on the comprehensive evaluation values obtained by the subjective and the objective analysis methods respectively to obtain the final comprehensive evaluation value of the network performance. The method has the advantages that probable insufficient data information content by singly using the objective analysis method is avoided, subjective randomness caused by singly using the subjective analysis method is also avoided, and simultaneously, the subjective and the objective analysis methods are combined together to evaluate the network performance so that the evaluation is more scientific and comprehensive, and the method has reasonable design and strong practicability and provides a basis for monitoring and evaluating the practical network performance.

The invention discloses a resource allocation and base station service deployment method based on mobile edge computing, and the method comprises the following steps: when a computing task is detectedin a mobile terminal, sending a computing migration request to a smart base station; when a cache unit in the base station is short of computing data needed for the task request, sending the needed task data requirement to a network side; receiving the needed task data returned by the network side; computing a time delay gain and an energy consumption gain according to the received needed task data; obtaining a computing migration decision matrix according to an experienced utility function; and performing computing migration according to the computing migration decision matrix. The base station deployment scheme comprises a cache unit, a computing unit, an acquisition processing unit and a sending unit, and can provide computing ability and data caching ability. Thus, the MEC based resource scheduling method and base station service deployment scheme can realize the computing migration in which terminals have multiple tasks, the base stations are multifunctional and targets are diversified.

The invention relates to an urban parking induction system and method based on the Internet of Things technology. The system comprises four modules including an information acquisition module, an information transmission module, an information analysis and processing module, and an information management and publishing module. The method includes: 1) standardizing a decision matrix X as a matrix Yshown in the description; 2) calculating a combined weight Wi; 3) establishing a gray correlation coefficient matrix between a0 and ai; and 4) determining an optimal scheme. The beneficial effects ofthe system and the method are that users still receive parking spaces recommended by the system in a passive manner for parking space induction in a parking lot, and with the progress of science andtechnology, the driving users can actively and autonomously select satisfying parking spaces and paths for driving, which is a goal of parking guidance in the parking lot in the future.

The present invention describes a method and system for intelligent diagnostic relevant information processing and analysis. Information associated with a patient is processed via an image reading platform. Based on such processed information, a matrix of diagnosis decisions containing diagnostic related information is generated via a matrix of diagnosis decision platform. A diagnostic decision is made based on the diagnostic relevant information. The image reading platform and / or the matrix of diagnosis decision platform encapsulate information and toolkits to be used to manipulate the information.

The invention relates to a key node recognition method for a regional power grid, and the basic flow of the method comprises the steps: inputting a power system topological structure and electrical characteristic parameters; calculating the values of evaluation indexes of a node; obtaining a node importance evaluation decision making matrix according to the values of the evaluation indexes; generating a node importance evaluation decision making matrix of a standard regional power grid; giving consideration to a Gini coefficient and a Kendall correlation coefficient, and solving the objective weights of the indexes through a CRITIC method; and solving an evaluation result of the node importance through a TOPSIS method. According to the technical scheme of the invention, the method gives full consideration to the physical features of the network topological structure and the operation state parameters of the power grid. The method can achieve the better recognition of the key node of the power grid, avoids the subjectivity of manual determination of the weights, and enables an evaluation result to be more suitable for the actual operation conditions of the power grid.

The invention discloses a comprehensive assessment method for the operation effect of a power grid side energy storage power station, and the method comprises the steps: constructing an energy storagepower station operation effect assessment index system, and determining a to-be-assessed scheme set; According to the actual operation data of each power station, calculating and extracting evaluation indexes of all schemes in the scheme set to be evaluated of each power station to form an initial decision matrix, and performing standardized processing to obtain a normalized decision matrix; Adopting an analytic hierarchy process to obtain a subjective weight vector of the evaluation index, adopting an entropy weight method to determine an objective weight vector of the evaluation index, andobtaining a comprehensive weight vector of the evaluation index through a game theory combination weighting method; And comprehensively evaluating the operation effect of each power station. The constructed index system has scientificity, applicability and operability, the selected indexes are high in applicability, and calculation is easy; The actual operation effect of the power grid side energystorage power station is comprehensively evaluated from many aspects, and a basis is provided for planning construction, scheduling operation control and the like of a subsequent energy storage project.

A system and method for online creation and integration of service of process functions is provided, for use in conjunction with paper or electronic filing of court papers. By logging on to a web page, the user can access a rules and decision matrix database providing the rules and requirements for process service by jurisdiction and type. Such rules can be incorporated into process requests using online tools and document management software. Once entered, the requests are compiled in a database, and a system controller coordinates with affiliated process servers to procure process service in the desired jurisdiction.

The invention provides a lane decision method for automatic driving vehicles based on a multi-objective decision matrix. The lane decision method includes the following steps that (1), a left lane, alane where the automatic driving vehicles are located and a right lane of the automatic driving vehicles are regarded as to-be-decided lanes, continuous-running distance and speed-limiting informationof each to-be-decided lane are collected, quantification is carried out on the information of each to-be-decided lane and evaluated information of each to-be-decided lane is obtained; (2), the information of barriers, closest relative to the vertical distance of the automatic driving vehicles, of the front side and the back side of each to-be-decided lane is collected, current location and speedinformation of the two barriers on the front and back and the location information after setting time are judged, and the relative distance the two barriers on the front and back relative to the automatic driving vehicles correspondingly at the current time and setting time is calculated; (3), integral evaluating information of the to-be-decided lanes is obtained by arranging the above informationand the decision matrix is formed; and (4), a decision lane is obtained by dealing with and calculating the decision matrix, so that the real-time independent lane deciding of the automatic driving vehicles is achieved.

The invention provides a distribution network fault tolerance on-line fault location method based on a prediction correction technology. The method comprises the steps that the independent region topology connection and the power flow transmission relation of a distribution network are used to establish a distribution network priority structure identification matrix; based on an independent region over-current information vector set and the distribution network priority structure identification matrix, a fault independent region decision matrix is constructed; fault independent region fault identification coefficients are determined, and a failed independent region is identified; the independent region is used as a basic dividing limit to establish a switch function model described by an algebra relation; prediction and correction models of fault region identification of the distribution network are constructed; and a prediction correction algorithm is used to identify a single feeder fault or a complicated multi-fault section of the distribution network. The method provided by the invention has the advantages of high information distortion fault tolerance ability, high versatility, high reliability, global convergence, convenient realization and high fault identification efficiency, and can effectively identify any complex multi-short circuit fault section of the distribution network.

The invention discloses a TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model-based intelligent substation secondary equipment evaluation method. The method mainly comprises the following steps: (1) acquiring characteristic sample indexes of each secondary equipment of an intelligent substation; (2) constructing an initial matrix according to the characteristic sample indexes of each secondary equipment and further obtaining a standardized decision making matrix by using a vector standardization method; (3) determining a weight value matrix and performing point multiplication on the weight value matrix and the standardized matrix to obtain a standardized weight decision making matrix; (4) determining a positive ideal solution vector and a negative ideal solution vector, and calculating the relative similarity degree of an evaluation index and the positive ideal solution of each evaluation object; (5) obtaining the state level of each secondary equipment, then determining a weight value of each secondary equipment, and finally obtaining a weighted comprehensive state level of the secondary equipment of the intelligent substation. By using the method, large sample data with multiple indexes and multiple evaluation objects of the intelligent substation can be considered, so that the operation status of the secondary equipment of the intelligent substation is more accurately evaluated.

The invention provides a TOPSIS-method multi-target threat ordering method based on information entropy. The method includes first building a threat assessment threat factor model, building a target attribute decision matrix according to the threat factor model, adopting an entropy weight method to calculate a target attribute weight vector according to the decision matrix, adopting a TOPSIS method to calculate relative close degree of target schemes according to the weight vector calculated through the entropy weight method and conducting threat assessment ordering on the schemes according to the close degree, namely the threat degree. By means of the method, shortcomings of the traditional ideal solution approaching ordering method in determination of weight coefficients are effectively overcome, and the target threat degree prediction accuracy is improved.

The invention discloses a database cluster system load balancing method and a database cluster system, and belongs to the field of information technology. The method comprises the following steps: (a) utilizing a cluster controller to acquire index values at each database back end to constituent a decision matrix; (b) calculating a weighted normalizing matrix according to the decision matrix; (c)calculating the distance between each database back end and plus-minus ideal solutions; and (d) after sequencing according to the distance difference value, utilizing the cluster controller to call the database back end according to the sequence. The system comprises the cluster controller and one or a plurality of the database back ends, wherein the cluster controller comprises a load balancing decision module, a back end detection module, a user request distribution module and a load information table; and each database back end comprises a communication module, a database server and a loadmeasurement module. The invention can be used for database cluster systems.

An object tracking method tracks a target object between successively generated infrared video images using a grey-scale hat filter to extract the target object from the background. The filtered image is binarized, and candidate binary blobs are extracted. The binary blob that minimizes the Euclidian spatial distance to the previous position of the object and satisfies a specified appearance model is selected, and its center of mass is taken as the current position of the object. Where the object is a person's eye, the eye state and decision confidence are determined by analyzing the shape and appearance of the binary blob along with changes in its size and the previous eye state, and applying corresponding parameters to an eye state decision matrix.

The invention discloses a method and a device for selecting a network based on a converged heterogeneous radio access network. The network selection method comprises the following steps of: transforming the attribute evaluation value of each attribute of the spare network to respective intuition fuzzy number according to the network selection state information and the heterogeneous radio converged network information; obtaining a fuzzy multi-attribute decision matrix according to the respective intuition fuzzy number and further obtaining a normalized decision matrix; then, obtaining the optimal attribute weight by using the maximum total difference policy of all the attributes between the attribute evaluation values of all the spare network; and weighting the normalized decision matrix by using the optimal attribute weight vector, processing the optimal normalized weighting fuzzy policy matrix based on a possibility and sorting to obtain the optimal network. By the network selection method and device, the stability of the network selection mechanism is improved without influence on the network selection accuracy.

The invention discloses a multi-focus image fusion method. The method comprises the steps of firstly carrying out robust principal component analysis on a multi-focus image to obtain a spare component matrix corresponding to a source image, then weighting and averaging the sparse component matrix to obtain a temporary spare component matrix and carrying out quadtree decompression on the temporary sparse component matrix, calculating the gradient energy of matrix subblocks corresponding to the sparse component matrix of the source image according to QT decompression results and comparing the gradient energy to construct a fusion decision matrix, and finally combining the image subblocks corresponding to the source image according to the decision matrix to obtain a fusion image. The method solves the problem that image blocks cannot be divided in a self-adaptive mode by combining RPCA with QT decompression, can effectively restrain block effects and improves the image fusion quality.

A framework and method for use in determining appropriate information technology system disaster recovery and operational continuity solutions for an enterprise. In one embodiment the method includes identifying (504) business processes associated with achieving a defined mission of the enterprise. Assets of the information technology system are grouped (508) into one or more functional sub-system / data class groups and one or more of the business processes are selected. The functional sub-system / data class groups are mapped (524) to the selected business processes to establish a correspondence between each selected business process and one or more of the functional sub-system / data class groups. Thereafter, each functional sub-system / data class group corresponding with each selected business process is associated (602) with a solution class included in a three-dimensional disruption tolerance decision matrix.

An integrated multi-classifier fusion classification method based on graph clustering label propagation comprises the following steps: using a training sample to train a basic classifier and clustering the training sample and a testing sample for multiple times to obtain multiple clustering partition states; carrying out label propagation based on the clustering partition states to obtain a clustering category label of the testing sample; processing all the clustering partition states and the basic classifiers according to the above-mentioned steps to obtain a clustering category information set of the testing sample; and making the clustering category information and classification information of the basic classifiers jointly constitute a decision matrix of an integrated classifier, setting parameters of a classification fusion target equation according to the clustering category information and the classification accuracy rate of the classification information of the basic classifiers so as to limit the range of the parameters in fusion, and using a BGCM method to carry out fusion classification on clustering category information of a to-be-classified sample and predicted label information of the basic classifiers according to the classification fusion target equation to obtain a final category label. The integrated multi-classifier fusion classification method is high in classification accuracy rate when difference exists among samples.

A method and an apparatus to descreen a halftoned picture takes into account the actual distribution of black or colors on the print without the need for scanning printed images but, rather, using only the printing decision matrix and the printer characteristics. For the purpose of laser printing, or more generally for reproduction on any printing device with a limited number of printing levels, a color or grayscale image has to be transformed into an array of printing decisions at each pixel of the output image. Sometimes this array is the only available representation of the original image. One may desire to reconstitute a good approximation of the original grayscale image from this array, for instance to print the picture on a printer with different characteristics from the printer for which the array was originally prepared, or to display it on a high resolution monitor. The method and apparatus to solve this problem in a way which take precise account of printer characteristics is described.

The invention discloses a comprehensive energy system evaluation method and system based on optimal combination weighting. The method belongs to the technical field of comprehensive energy system evaluation and comprises the steps that an evaluation index system of a comprehensive energy system with p layers is established according to all evaluation indexes of the comprehensive energy system, thefirst layer is a quantitative evaluation result of the comprehensive energy system, and the p layer is a (p-1)-level evaluation index; acquiring numerical values corresponding to the evaluation indexes under different configuration schemes, and constructing an index evaluation standardized decision matrix; calculating subjective weight and objective weight of each evaluation index by adopting a subjective and objective combination weighting method; according to elements, subjective weights and objective weights in the standardized decision matrix, comprehensive energy system evaluation results under different configuration schemes are obtained, and the configuration scheme corresponding to the maximum evaluation result serves as the optimal comprehensive energy system configuration scheme. The subjective and objective combination weighting method is adopted, the evaluation result is more scientific, and the practicability is high.

The invention discloses a service-preference-and-network-condition- based vertical handoff method (SNVHO). The handoff method employs a new algorithm for computing weights. Related weights are divided into two kinds: one kind is subjective weights targeting at service preferences and the other kind objective weights determined by network characteristics. An analytic hierarchy process (AHP) is employed, and a decision matrix obtained through the utilization of relative importance is utilized in order to compute the weight of each handoff decision factor; and finally, final decision is carried out through the utilization of a accumulative sum of a product of each attribute multiplied by the corresponding weight. According to the method of the invention, targeting at different service calculation weights, the weights are dynamically changing instead of being fixed values, so that defects of setting the fixed values are overcome. A simulation result show that the service-preference-and-network-condition-based vertical handoff method (SNVHO) is greatly improved in terms performance parameters such as the vertical handoff times, the system throughput, the call drop rate and user costs.

The invention discloses a network selection method based on grey relational analytic hierarchy. The network selection method comprises the following steps of (1) utilizing an analytic hierarchy, establishing a hierarchical order and constructing a judgment matrix (formula); (2) calculating a normalized weight omegaj; (3) utilizing an entropy weight method, constructing an evaluation matrix (formula) and normalizing the evaluation matrix; (4) solving an entropy Ej of a decision-making property, and calculating the entropy weight phij; (5) utilizing a grey relational method, constructing a global decision matrix (formula) and finding out a group of reference solutions (formula); and (6) calculating a grey relational grade (formula), carrying out grey multi-attribute judgment (formula) and selecting a network having a largest correlation coefficient with the reference network as the optimal network. According to the method, the best network which is most matched with the reference networkis selected according to the grey correlation method, the problem that the network decision-making property is not a network selection problem of a monotonous function can be effectively solved.

A framework and method for use in determining appropriate information technology system disaster recovery and operational continuity solutions for an enterprise. In one embodiment the method includes identifying (504) business processes associated with achieving a defined mission of the enterprise. Assets of the information technology system are grouped (508) into one or more functional sub-system / data class groups and one or more of the business processes are selected. The functional sub-system / data class groups are mapped (524) to the selected business processes to establish a correspondence between each selected business process and one or more of the functional sub-system / data class groups. Thereafter, each functional sub-system / data class group corresponding with each selected business process is associated (602) with a solution class included in a three-dimensional disruption tolerance decision matrix.