60results about How to "Reasonable decision" patented technology

The invention discloses an elevator driving control and energy saving integrated system. A master control unit based on double DSPs and an FPGA is adopted in the system to collect voltage, current, speed position and other information of a traction machine, and control over the elevator traction machine is achieved after comprehensive judgment. A supercapacitor bank is adopted to serve as a power source for running of a regenerating braking energy storage device and an elevator driving control sub-system, and energy is stored in the running braking process of an elevator sub-system. A supercapacitor are directly connected with a direct-current bus in parallel through a two-way direct-current converter, the master control unit monitors the running state of an elevator in real time by means of an elevator signal collection unit, switching between a charging mode and a discharging mode of a supercapacitor module is finished, and the aim of saving energy is achieved. The system fully uses the characteristics that the supercapacitor is large in discharging current, long in service life, short in charging and discharging time, large in capacitance density and the like, improves energy saving efficiency and safety of elevator running, has very high social benefits and economic benefits, and accords with the concept of environment protection and sustainable development.

The invention discloses a multi-target planning method for power grids of wind farms based on improved NSGA-II. The multi-target planning method includes the steps of building an output force model of the wind farms, calculating the flicker value of a wind turbine generator system at a common connection point, creating a target function with shortest line length and minimal flicker value of a wind farm at a common access point, and realizing multi-target planning of the power grid of the wind farm based on NSGA-II algorithm of NDX operators, the output force model and the target function. The multi-target planning method overcome the defects of subjectivity of conventional multi-target optimization and obtaining one solution in one time, enhances overall searching capability than routine NSGA-II algorithm, and improves convergence.

The invention provides an urban road traffic identification method and system based on elastic coefficients. The method comprises the steps that a traffic flow parameter model is built, a traffic flow elastic coefficient threshold value is preset, the traffic flow states are divided according to the elastic coefficient threshold value, real-time identification or predication of the traffic states of a target road is achieved through comparison of the traffic flow information and the traffic flow parameter threshold value, and therefore the interactive relation between traffic state parameters can be described in an quantized mode, the dependency relation between the traffic state changes and the changes of the influence factors of the traffic state changes is weighed, the method can be suitable for different roads and traffic conditions, the identification result facilitates accurate and reasonable decision making by a traffic signal control system.

A system and method are disclosed for one-stop shopping for health-care services and related needs. The one-stop shopping system and method provide objective information for the system enrollee to assess and decide on health-care insurance and services. The system and method provide this objective information in a way that is easily accessible by system enrollees in an economical and rapid manner.

The invention relates to the technical field of block chain information sharing, and particularly discloses an intelligent law and regulation platform based on a block chain technology. The platform comprises a smart block chain module, a trusted data lake module, a data analysis module and a service platform. The smart block chain module is used for creating, managing, operating and maintaining asmart law data block chain, and comprises three hierarchical structures including a block chain account book edge calculation layer, a block chain consensus node cloud layer and a sub-chain layer; the trusted data lake module is used for performing data management on data of a block chain in the intelligent block chain module, and the data management sub-module comprises a data acquisition module, a data storage module, a data analysis module, a data application module and a data management module. According to the law and regulation platform, a system with credible data, decentralization, data sharing, high intelligent degree and unified data standard is established, and the intelligent law and regulation platform based on the block chain technology is provided.

The invention discloses a multi-objective reactive power optimization method for solving a Pareto optimal solution set. The method of the invention converts the problem into a problem of solving reactive power optimization containing two objective functions, boundary points of the two objective functions are respectively solved directly in a tangent method, an inequality constraint method is then adopted to solve Pareto frontier formed by the two objective functions, during the calculation process, algorithm for solving a single-objective reactive power optimization model adopts a primal dual interior point method, and a point for an initial value adopts a result of power flow calculation. The multi-objective reactive power optimization method for solving a Pareto optimal solution set has the advantages that optimization of multiple objectives is comprehensively considered during the reactive power optimization process, subjectivity generated when a single objective reactive power optimization model is built by other algorithms can be effectively avoided, the distribution condition of each objective function can be intuitively seen from the Pareto frontier surface, and a reasonable and reliable decision which can meet needs of system operation can be made conveniently by a decision maker.

The invention discloses a power grid dispatching dynamic capacity increasing evaluation method based on state multi-dimension comprehensive evaluation. The method includes the first step of establishing an available margin equation, in regard to transmission capacity of all lines in a load channel, of a total capacity increasing quantity deltaY, the second step of determining capacity increasing coefficients for all the lines in the load channel in consideration of the capacity increasing coefficient upper limit of through-flow equipment, the capacity increasing coefficient upper limit of a weather risk and the capacity increasing coefficient upper limit of a system abnormal risk, the third step of establishing the least square solution optimization model of the available margin equation, the fourth step of considering balance of capacity increasing load rates of the lines and setting capacity increasing coefficient initial values of the lines and the fifth step of obtaining actual capacity increasing coefficients of all the lines. The method is based on state monitoring parameters of power transmission and transformation equipment in the load channel, consideration is given to capacity limits of the power transmission and transformation equipment and health states and operational risks of the power transmission and transformation equipment, consideration is given to current moment evaluation and expected risk prediction, power grid dynamic capacity increasing evaluation and decision making can be more precise and reasonable, and the risks are lower.

The invention discloses a visualization method for emergency early warning of sudden toxic gas leakage. The method comprises the steps: completing the collection of meteorological wind field data, chemical plant data, road network data and geographic data, and carrying out the preprocessing of the collected data; establishing a streaming database for the wind field data; predicting a poison gas diffusion range after a sudden poison gas leakage accident occurs in the chemical plant through the Gaussian puff model, and calculating evacuation path plans of all citizens in the affected range according to a poison gas diffusion range prediction result; finally, outputting a fusion view of accident surrounding geographical condition visualization, wind field visualization, poison gas diffusion range prediction result visualization and evacuation path planning visualization in real time. According to the method disclosed in the invention, an urban emergency management department can be helpedto make reasonable emergency decisions more efficiently in a specific scene of sudden toxic gas leakage disasters, and life safety threats to citizens are reduced.

The invention discloses a KNN and three-way decision-based movie recommendation method. The method comprises the following steps: receiving a selection condition input by a user; dividing a movie sample set D into a movie sample set XP with a label P and a movie sample set Xn with a label N according to the received selection condition; calculating m nearest neighbor sets and corresponding label sets, in the movie sample set XP, of the ith movie sample x(i) in the movie sample set D as well as n nearest neighbor sets and corresponding label sets, in the movie sample set XN, of the ith movie sample x(i) in the movie sample set D ac to KNN; calculating a posterior probability P(XN / x(i)), in the movie sample sets XP and XN, of the movie sample x(i); and calculating a recommendation value (the formula is as shown in the specification) of the movie sample x(i) according to a movie three-way decision, and determining to classify the movie sample x(i) according to the calculated recommendation value (the formula is as shown in the specification).

The invention provides a data association method and device and a storage medium, and relates to the field of finance. The method comprises the steps of obtaining news information, and the news information is subjected to multi-dimensional clustering according to categories; obtaining information messages of multiple objects, and on the basis of the information messages, performing multi-dimensional clustering on the objects; according to the dimensions, building the mapping relation between the clustered objects and the clustered news information; displaying a result. By building the mappingrelation between the objects and the news information according to the dimensions, associated information can be automatically triggered, the information associated with the data association method iscomprehensive, information omission is avoided, more comprehensive information can be provided for an investor for reference, and more reasonable decisions are made; by building correlation among theclustered objects, ranking is performed according to the correlation among the clustered objects, a warning can be given to the investor in advance by building the correlation among the clustered objects, and decisions are made in advance.

The invention discloses a method for dividing three decision communities based on random walk boundary domain processing. The method comprises the following steps: 1) obtaining an abstract network; 2)clustering and granulating that abstract network after initial granulation, dividing the abstract network into a plurality of divided communities, the structure relationship of the divided communities being taken as a first dividing result; 3) obtaining that first partition result of the abstract network corresponding to the maximum value of the module degree of the overlap community; 4) dividingall nodes in that boundary region by using a random walk algorithm; 5), for each node in the updated boundary region, by using a three-branch decision method, processing to obtain a second partitionresult, the second partition result being taken as a target partition result. The invention discloses a device for dividing three decision communities based on random walk boundary domain processing.The application of the invention can improve the precision of the community division, thereby facilitating the analysis and understanding of the network structure, and facilitating the optimization and management of the network.

The invention provides a cross-regional day-ahead spot goods automatic transaction strategy method, which comprises the following steps of: predicting the total clearing electric quantity of the wholenetwork of the next day by using a BP neural network on the basis of the historical clearing electric quantity of the whole network; predicting the next day tradable abandoned wind power according tothe historical power generation data of the centralized control system station side, the current day power generation and limit data of the wind power plant and the next day wind power prediction result in combination with the grid structure condition, respectively generating a next day 96-point quantity price curve of each station, and taking the tradable electric quantity as a basis for reporting the electric quantity; calculating the declared electricity price according to the ratio of the tradable electricity quantity of the station side to the whole network clearing electricity quantitypredicted next day and the historical clearing electricity price distribution; and automatically declaring the generated price curve to a power grid information interaction platform by utilizing a timing task in a transaction declaration effective time period. The invention further discloses a trans-regional day-ahead spot goods automatic transaction economy evaluation method, and the actual economic benefits of participating in the spot goods transaction are obtained.

A multi-smartcard may include: a support; a touchscreen disposed on the support configured to receive an input operation from a user including a first input operation and a second input operation; and a processor configured to generate a first user interface (UI) of card information corresponding to the input operation applied to the touchscreen and instruct the touch screen to display the first UI, and to receive the first and second input operations, wherein the processor is configured to change the card category in response to receiving the first input operation and change the card type in response to receiving the second input operation.

The invention provides a multi-target cloud workflow scheduling method and device. The method comprises the steps: building a time population comprising N time individuals and a cost population comprising N cost individuals, and selecting a plurality of individuals as first optimization individuals to build a first external population; updating the time population, the cost population and the first external population, establishing a second external population by taking the obtained updated time individuals, the updated cost individuals, the updated first optimization individuals and the firstoptimization individuals as second optimization individuals, and performing updating operation on the second external population; and when the number of iterations reaches a preset value, schedulingthe cloud workflow according to a second optimization individual contained in the updated second external population. According to the method, the problems of individual fitness allocation and population diversity maintenance in a traditional multi-objective optimization method are solved, and the obtained optimal individual can optimize the execution time and the execution cost at the same time.

The invention discloses an Android software risk assessment method based on a probability ontology. An AHP (analytic hierarchy process) is utilized to construct an Android software risk assessment model; risk authority nodes are extracted from various apps; a corresponding relationship between the risk level and the authority support degree is described through a triangular fuzzy function; risk nodes, node weights and hierarchical relationships in the risk assessment model are selected; attribute setting is performed, instances are added, a probabilistic ontology model is constructed, a corresponding owl code is given; the ontology is analzyed by utilizing Jena; netica is imported to generate the Bayesian network model, the Bayesian network probability model is perfected by dynamically adding evidence information, risk reasoning is performed by utilizing the netica, risk level probability distribution of nodes to be assessed is calculated layer by layer, and finally app comprehensive risk level probability distribution is obtained to complete risk level assessment. The evaluation result can change along with the change of an app use scene, and a reasonable decision is made when theapp is installed and used.

A photovoltaic output 2D section prediction method based on fuzzy rules comprises the following steps: 1, inputting local electric and meteorology data of a to-be-predicted photovoltaic power generation system, and inputting internet meteorology data; 2, preprocessing various types of data of the inputted data; 3, obtaining the sunny inclined surface global radiation intensity of a to-be-predicted date, and using same to correct the power data of a power sunny model; 4, building a lasting 2D section prediction model; 5, building a 2D section prediction vector, and building a support vector regression 2D section prediction model; 6, building a first fuzzy rule, and using the built fuzzy membership function to modify the lasting 2D section prediction model and the support vector regression 2D section prediction model combined coefficient; 7, building a second fuzzy rule, and adjusting the deviations of the2D section prediction result according to the rules. The method can effectively predict the 2D section, and the prediction result is high in credibility.

The invention discloses a Shanghai-Shenzhen-Hong Kong exchange capital flow display method based on an electronic map. The method comprises the steps that geographical location information of the Shanghai Stock Exchange, the Shenzhen Stock Exchange and the Hong Kong Stock Exchange is acquired, and positioning points of the Shanghai Stock Exchange, the Shenzhen Stock Exchange and the Hong Kong Stock Exchange are displayed on the electronic map respectively according to the geographical location information; and stock exchange capital information of Shanghai stock exchange and Hong Kong share exchange-Shanghai of Shanghai-Hong Kong exchange and stock exchange capital information of Shenzhen stock exchange and Hong Kong share exchange-Shenzhen of Shenzhen-Hong Kong exchange are acquired to display the capital flowing trend between the mainland and Hong Kong. According to the method, the capital flowing trend between the mainland and Hong Kong is displayed in a graphic mode in combination with geographical locations of different exchanges in the electronic map, and therefore the stock capital flowing condition between the mainland and Hong Kong can be known visually and vividly. The invention furthermore provides a corresponding Shanghai-Shenzhen-Hong Kong exchange capital flow display system based on the electronic map.

The invention provides a flexible employment management system and a module cooperation method thereof, and relates to the technical field of teacher management systems. The flexible employment management system comprises a system entrance, a system function module and a basic function module; the system entrance comprises a nail, a CHR system and a night queen; the nail is used for undertaking communication and message transmission between a manager and flexible employment and supporting online handling of personnel business; the CHR system is used for personnel management of flexible employment; and the night queen is used for being responsible for communication between flexible employment and users and collection of service data. According to the invention, a decoupling mode is adopted, the related partial business system is connected to the HR system, offline manual operation is reduced, and the accuracy and maintainability of data are improved, so that a manager can refer to partial key business data and make reasonable judgment and decision while performing personnel management.

The invention discloses a college student behavior analysis system and method based on WiFi positioning data. The system comprises a data layer, a calculation layer and a business display layer. The data layer comprises a data cleaning module, a data storage module and a data mapping module, and the data layer further provides an interface for acquiring data for the calculation layer; the calculation layer comprises a hot spot region extraction module, a segmented track migration analysis module and a student behavior similarity analysis module; the calculation layer provides data conversion and mapping, and performs data analysis by using different algorithms according to different requirements; and the business display layer performs visual display on a result obtained by analysis of the calculation layer. According to the invention, by establishing a student behavior data analysis model based on positioning information, internal association among student behaviors, academic records, psychology and the like is found, relationships hidden in data are mined, school managers are helped to carry out accurate tracking service on student learning conditions, and construction of smart schools is further promoted.

The invention belongs to the technical field of credit approval, and particularly relates to a credit approval system, which comprises a business application layer, a business service layer and a technical support layer, and is characterized in that the business application layer comprises a foreground support unit, a risk management unit and a review approval unit, wherein the examination and approval unit comprises a data examination module, a financial analysis examination module and a policy examination module, and the business service layer comprises a quota calculation module, a guarantee mode examination module, a repayment mode examination module, an anti-fraud module, a loan pricing module, a credit extension period confirmation module and a client rating module. The technical support layer comprises a score card module, a neural network, a rule engine module and a decision-making module. The system gradually evolves to intellectualization on the basis of process. Intelligent decision support is used as an engine to gradually replace an operation mode mainly based on manpower, credit operation efficiency is improved through a comprehensive and objective method, and professionality is improved.

The invention provides a conference schedule conflict management method and system, electronic equipment and a storage medium, and the technical scheme of the method comprises the steps: an idle time obtaining step: setting a new conference schedule, and obtaining the idle time of a first participant participating in the new conference schedule; a conference conflict judgment step: traversing the idle time of the first conventioneers of the new conference, judging whether the schedule of the new conference conflicts with the idle time of any one of the first conventioneers, and if so, performing a conflict prompt; and a conflict backtracking analysis step: if the new meeting schedule conflicts with the idle time of any first conventioneer, obtaining the existing meeting schedule of the first conventioneer with the conflict, and analyzing and returning the reason for the conflict of the new meeting schedule according to the existing meeting schedule. The problem that an existing conference conflict management method cannot consider backtracking and conflict reason analysis is solved.

The invention discloses a broadband user access method in a satellite network, which is used for deciding a broadband access request of a user according to the geographic position of the user, the priority of the user, the resource demand of the user and the residual resource of a beam by comparing the income of accessing a new user and the cost of kicking out an original user. The serving beam is used as much as possible according to the user position, the spare beam resource is saved, the weighted base number of the user priority and the cost benefit coefficient of the user are introduced, and the user distinction degree between different priorities is improved; and, according to the invention, the access benefit maximization is ensured according to the profit cost comparison, a simple first arrival first acquisition mode is abandoned, and parameters can be changed according to the scheduling system and the requirements of the user, so that the decision of accessing and kicking out the user is more reasonable.

The invention discloses a dual-targeting multi-modal molecular imaging probe and a preparation method and application thereof. The probe of the invention is a tri-modal dual-targeting probe with nuclear magnetic, photoacoustic and near-infrared fluorescence signals. By adopting a unique EGFR and SEC61G dual-targeting strategy, the probe can significantly improve the accuracy of preoperative tumordiagnosis and potential intraoperative navigation application, and has broad application prospects and transformation value.

A system and method are disclosed for one-stop shopping for health-care services and related needs. The one-stop shopping system and method provide objective information for the system enrollee to assess and decide on health-care insurance and services. The system and method provide this objective information in a way that is easily accessible by system enrollees in an economical and rapid manner.

The invention provides a treatment plan recommending method based on combination of expert authority and case reliability, and a system. The method comprises the steps of determining k similar historical case samples of a target case, acquiring doctor ballot data and a final treatment plan of each case sample in the k similar historical case samples, calculating doctor ballot accuracies; sequencing the doctor ballot accuracies in the historical case samples, obtaining an authority expert list, and calculating ballot certainty degree according to the authority expert list; calculating a reliability function value according to the k similar historical case samples; multiplying the reliability function value of each historical case sample with the certainty degree, and obtaining the final reliability of the case sample; combining the final reliabilities of the case samples by means of a DS evidence theory, and selecting the treatment plan with highest reliability as a recommended plan. The reliabilities of the historical cases are optimized by means of the process, and finally the DC reliability is combined with the model for generating a final decision result.

The invention discloses a data standardization analysis method and system for small and medium-sized insurance enterprises, and the method comprises the following steps: S1, carrying out the preprocessing of original data: carrying out the filling of some incomplete data in the original data, and cleaning problem data; S2, after data is cleaned, standardizing data according to an XBRL-GL data standardization protocol, and then storing the standardized data;; S3, analyzing the stored data based on a machine learning method, and displaying the analysis result. According to the data standardization analysis method and system can provide more visual, accurate and reliable data standardization analysis service for enterprises, data nodes are opened up for the enterprises, data isolation is eliminated, meanwhile, the data utilization rate of small and medium-sized insurance enterprises is increased, and the data analysis threshold is lowered.