181results about How to "Achieve optimal configuration" patented technology

The invention provides a project management progress arranging method and a project management progress arranging system which aim at re-optimizing a progress plan to enable resource allocation of a project to be optimal at any time. The project management progress arranging method includes the following steps: (1), generating a project quantity list, namely decomposing a building information model into work packages, reading material information in the work packages and creating the project quantity list according to defined project quantity calculating rules; (2), generating a progress plan, namely calculating labor time and forming the progress plan on the basis of the project quantity list and according to constraint conditions like a logical relationship between labor quotas and processes and total resources; (3), optimizing the progress plan, namely optimizing the progress plan within a reasonable time limit and based on a PSO (particle swarm optimization) algorithm to obtain an optimal progress schedule meeting requirements of optimization of resource allocation.

The invention relates to the technical field of big data and discloses a model system and method for talent ability evaluation based on big data. The system comprises a talent big data information collection module, a talent big data distributed management module, a talent big data analysis module, a talent ability accurate recommendation module and a talent ability multi-dimensional visual display module. Aiming at problems such as disconnection among a social talent chain, an industrial chain, an innovation chain and a capital chain, a regional talent supporting service platform based on the big data is established; an oriented pushing service of information involving science, technologies, innovation and entrepreneurship based on the big data is implemented; a service scope of innovation and entrepreneurship talents is expanded; a utilization rate of social, scientific and technological resources is increased; a service life of the high-level talents is increased; and optimal configuration of the social, scientific and technological resources can be implemented through combination of modern advanced network technologies and traditional docking manners.

The invention provides an electric automobile driving range optimization method based on battery pack heating. The method includes the steps that a system obtains parking time information, environment temperature information, battery pack information, electric automobile energy consumption information and battery pack relevant parameters of an electric automobile, and goal temperatures for heading k battery packs are determined; a heating current changing curve with minimum electric quantity consumption is selected to serve as the optimal heating current changing curve and optimal battery pack consumption electric quantity; electrical charge conditions of the battery packs are calculated, residual available capacity is calculated, thus residual available energy is calculated, finally a driving range is calculated, and the driving range Range_T0 under the goal temperature Tgoal_0 is calculated; the longest driving range is selected; a battery pack heating system enables the electric automobile to reach the longest driving range. The method aiming at prolonging the driving range of the electric automobile provides the optimal calculation method of the battery pack goal temperature and the heating current changing curve, and has the advantages of being easy and convenient to calculate and achieving optimal configuration of resources.

The invention discloses a system and a method for managing and controlling a water pump based on cloud computing. The system comprises an Internet-of-Things site controller, an Internet-of-Things site data collector and a management and control platform for cloud computing equipment, wherein the Internet-of-Things site controller is used for setting the normal running parameter of the water pump, managing and controlling the running mode of the water pump according to the normal running parameter and sending the normal running parameter of the water pump to the management and control platform for cloud computing equipment; the Internet-of-Things site data collector is used for collecting the actual running parameter of the water pump and sending the actual running parameter to the management and control platform for the cloud computing equipment; and the management and control platform for the cloud computing equipment is used for adjusting the management and control mode of the Internet-of-Things site controller according to the actual running parameter and the normal running parameter of the water pump. The method is realized through the utilization of the system. The system and the method can be compatible with water pump management and control platforms from different factories and can manage and control multiple objects under unified platform in a concentrated way, thereby realizing optimum configuration on the running state of the equipment.

The invention provides a multi-energy complementary rural micro energy network capacity optimization configuration method and device. The method comprises steps: S1, according to a wind-solar-gas-cold-heat-storage energy supply model of the multi-energy complementary rural micro energy network and in combination of the time shifting property of a load capable of time shifting, an objective function and a constraint condition for capacity optimization configuration in the multi-energy complementary rural micro energy network are determined; and S2, in combination of the constraint condition, the objective function is solved by a grey wolf optimization algorithm based on an improved dynamic adjustment convergence factor and an inertia weight, and the capacity optimization configuration result of each micro source in the multi-energy complementary rural micro energy network is acquired. In combination of the actual situation in the western countryside, on the basis of considering the load-side response and the power supply reliability, an optimization configuration model with the lowest annular investment cost is built, the optimization configuration problem is solved by the grey wolfoptimization algorithm based on the dynamic adjustment convergence factor and the inertia weight, and rural micro energy network capacity optimization configuration is realized.

The invention provides a webpage throwing content analyzing method and device and an automatic throwing method and device for webpage throwing content. The throwing content is thrown on a plurality of webpages through a throwing system of the throwing content. The webpage throwing content analyzing method includes recording access behavior data of a visitor accessing the webpage throwing content, wherein the M-level position code of the webpage of the corresponding throwing content and the N-level attribute code of the throwing system are carried and added in the access behavior data, and M and N are positive integers; conducting statistics on the clicking rates of the throwing content at different throwing positions according to the M-level position code and the N-level attribute code of the access behavior data; determining the optimum throwing position of the throwing content according to the clicking rates at different throwing positions. By means of the method and device, the optimum throwing position of the webpage throwing content can be found, the throwing efficiency of the throwing content is improved, and relevant network resource configuration is optimized.

A distributed energy optimizing operation method based on a game theory comprises the following steps: S1, acquiring original data and parameters of each generator; S2, selecting a plurality of generators as game participants to establish a game model; S3, selecting an initial equilibrium point value in a strategy space of each decision variable; S4, according to the initial equilibrium point value, searching the optimal strategy of each game participant in the strategy space by a particle swarm algorithm; S5, sharing optimal strategy information of each game participant to each generator; S6,judging whether a system finds a Nash equilibrium point, and if the system finds the Nash equilibrium point, outputting the equilibrium point, and if the system does not finds the Nash equilibrium point, returning to the step S3. The output dispatching problem of distributed energy is solved in a non-cooperative game way under the premise that the minimum carbon emission is considered; the optimal output of each unit of a power system in each mode is solved so as to obtain the maximum economic benefit and the minimum cost under the same condition.

The invention discloses a cloud computation-based smart grid load prediction management platform. The cloud computation-based smart grid load prediction management platform comprises (1) an infrastructure layer, (2) a load data management, processing and analysis platform layer, (3) a four-type intelligent load service software layer and (4) a cloud interface management layer. By adopting the technical scheme, the cloud computation-based smart grid load prediction management platform has the following advantages and characteristics that 1, by adopting the smart grid load prediction novel technology, the requirement on prediction of the smart grid load can be effectively met; 2, by effectively utilizing the general characteristics of the cloud computation, the resource can be optimally configured, the information such as the load prediction data is shared, and different users can conveniently and effectively acquire the load service at any time; 3, the additional hardware upgrading expense caused by the upgrading of the load prediction platform along the development of the smart grid can be avoided, the device such as different servers is not needed, and the primary development cost and the maintenance upgrading cost can be reduced. By adopting the open-source development environment, the development cost is low.

The invention discloses a multi-dimensional resource pricing method in a mobile cloud computing environment based on a bilateral market. The method runs in the mobile cloud computing environment, the method involves two groups of participants in the mobile cloud computing environment, one group of participants are Cloudlets which have resources, and the other group of participants are VMs which request the resources. The VMs are regarded as a buyer in a bilateral market economic model, the Cloudlets are regarded as a seller, and the two sides complete allocation of the resources through a price interactive mechanism, unloading execution of an application request from the VMs to the Cloudlets is completed, and energy consumption of the mobile equipment is reduced. The price interactive mechanism in the method is based on a bilateral market game and is designed through combination of a punishment pricing mechanism and a balanced utility discount, the multi-dimensional resources of the application request of a mobile user can be reasonably distributed and dispatched on a plurality of Cloudlets, and therefore system benefits of a mobile cloud are maximized.

The invention discloses a method, a device and a system for reporting a buffer status report (BSR). The method comprises steps: user equipment receives the format configuration information of the BSR sent by a base station, wherein the BSR format configuration information comprises the format of a buffer status report specially for super real-time service (S-BSR); and when the user equipment detects the buffer status report specially for the super real-time service needs to be reported, the user equipment reports the buffer status report specially for the super real-time service in the format of the buffer status report specially for the super real-time service. According to the method, the device and the system for the reporting buffer status report, the user equipment in a connected state can report the buffer status report for the super real-time service to the base station.

The invention belongs to the technical field of electric power system simulation testing and particularly relates to a modularization multi-level converter real-time simulation modeling method based on an onsite programmable gate array. According to the invention, the method comprises steps of based on the MMC working mechanism, establishing a Thevenin equivalent model of a bridge arm; using an FPGA to achieve equivalent calculation of an MMC valve group; grouping sub modules of the same bridge arm in the calculation process, wherein calculation processing is performed on each group through an FPGA production line framework; and performing synchronous parallel calculation between groups. Thus, calculation time is greatly reduced and the real-time simulation requirement is met. The beneficial effects are that flexible configuration of MMC primary parameters is achieved under the condition that the FPGA program is not modified; the method is universal to different sub module topologies; and an external controller can be connected to carry out system-level and valve-level hardware-in-the-loop experiments.

The invention discloses a micro-grid economic optimization trading method based on cloud energy storage in an electric power market environment, belonging to the technical field of electric power system automation. The method is based on a small amount of distributed energy storage, the energy storage device originally distributed on the user side is centralized to the cloud end to form a centralized cloud energy storage, the objective function of the benefit of selling and purchasing electricity to cloud energy storage and the constraint of charging and discharging of cloud energy storage areincluded by simultaneous microgrid, cloud energy storage sales and purchase pricing constraints, the constraint condition of power purchase in micro-grid determines the joint optimization model of micro-grid system and cloud energy storage, after each micro-grid is regarded as a stakeholder, the amount of electricity sold and the charging and discharging time of each micro-grid are optimized to maximize the economic benefits of the micro-grid. The participation of cloud energy storage reduces the investment cost of energy storage equipment and improves the utilization rate of resources.

The invention discloses an intelligent conference room management system and method. The system comprises a user end, a management end, a front end and a control unit. The user end provides the conference room real-time reservation and query functions; an intelligent scheduling module in the management end intelligently matches an optimal conference room with the conference room requirements submitted by the user based on a BP neural network and a GA algorithm, and returns the predetermined information to the user through a cloud platform; the conference room front end provides the conferencequery and reservation functions, meanwhile, collects the human face information and calls a human face recognition module of a PCA algorithm based on feature weighting for human face recognition, so that the functions of conference face swiping sign-in and access control are achieved. Meanwhile the Internet of Things equipment in a conference room are turned on according to a control instruction.According to the present invention, the conference room resources are efficiently utilized, and the function of avoiding the conference room conflicts is achieved.

The invention relates to a wide-adaptive novel automatic driller, which comprises an actuating mechanism, a variable-frequency motor and a frequency convertor. The actuating mechanism is driven by a winch; the winch is connected to the variable-frequency motor through a reduction gearbox and a clutch; the frequency convertor is connected to the variable-frequency motor; a three-phase power is communicated with the frequency convertor; a suspending weight sensor is arranged on the actuating mechanism and inputs the detected data into a programmable logic controller (PLC); and the programmable logic controller (PLC) is communicated with the frequency convertor and a touch screen used as a human-computer interface. The programmable logic controller comprises a drilling pressure calculation module, a PID module and a fuzzy setting module. The wide-adaptive novel automatic driller aims at the characteristics of the control targets of automatic drilling, reduces the interference degree of a driller on a PID control system, introduces a fuzzy control algorithm to set the parameters of the PID system and achieves the purpose of optimal setting of the parameters of the PID control system.

The invention relates to an optimal operation method for a multi-energy complementary system, which includes the following steps: S1, carrying out interval description on distributed energy and cooling-heating-power equipment based on the structure of a multi-energy complementary system; S2, establishing a system coupling model according to the interval description result; S3, establishing a multi-objective function considering environmental, economic and energy factors, wherein the multi-objective function includes the operation cost and the pollution emission cost; S4, acquiring constraintsused to ensure interval balance, wherein the constraints include electric power balance, cooling-heating-power equipment balance and grid interaction conversion constraints; and S5, solving the systemcoupling model based on the interval theory and affine operation to obtain a final solution set. Compared with the prior art, coupling modeling is carried out on the energy devices of the system, andthe model is solved based on the interval theory and affine operation, which can reduce the dynamic impact of prediction error and energy fluctuation on the system, realize optimal allocation of resources and improve the energy utilization efficiency of the multi-energy complementary system.

The invention discloses a salesman screening activation method. The salesman screening activation method includes the following steps: 01) acquiring the attribute information of salesmen to be screened, wherein the attribute information includes the unique identifier and the attribute label of each salesman to be screened; 02) according to the attribute label of each salesman to be screened, calculating the attribute value of the corresponding salesman, according to the attribute value, classifying the salesmen, and forming the classification identifier of each salesman, wherein the identifiers of the salesmen to be screened are matched with the classification identifiers to form the data to be activated of the salesmen; and 03) according to the preset distribution strategy, distributing the salesmen in the data to be activated, and according to the preset activation strategy, activating the salesmen after distribution. The salesman screening activation method can improve the pertinency of screening and distribution of salesmen so as to screen the salesmen who are given great attention to realize optimal configuration of seat resources.

The invention provides an optimal configuration method of distributed generations (DG) based on a power moment algorithm and relates to a configuration method for accessing the DGs to a power distribution network, which is utilized to solve the problems that a uniform load distribution characteristic or a constant power factor load condition is considered only, or a configuration result is influenced easily by initial parameters, or a condition of random load distribution in an actual power distribution network is not considered, and existing methods are complicated in the prior art. The optimal configuration method of the DGs provided the invention is utilized to respectively define active second moment and active first moment with the beginning of the minimum target function of network loss, thus a power moment method for optimally configuring the DGs is put forward, which comprises the following steps: determining the installation positions of the DGs in accordance with the active second moment; determining active optimization of the DGs in accordance with the active first moment; and determining reactive optimization or compensated reactive capacity of the DGs in accordance with reactive first moment. The method can be also applied to determining the problems of real-time active output power and reactive output power of each DG in real-time scheduling.

The invention discloses a pair of speckle data gloves based on DSP-PC machine visual system, comprising adopting two CCD cameras to perform real-time image acquisition to gloves worn by user, wherein each camera is equipped with a fixed-focus lens satisfying capture range, tracking capture function of hand movement can be realized by treating the data through DSP and PC machine so as to measure hand posture; furthermore, an embedded real-time image acquisition treating unit is arranged to digitalize the image signal acquired by the CCD camera, a video treatment chip DM 642 is used for detecting, identifying and tracking the gloves speckle; a virtual hand presentation and interaction unit based on PC machine comprises a parametrically adjustable virtual hand module for modifying size of the module according to the measurement result of the physiological parameter of current user hand, and obtaining the information from the image acquisition treating unit to compute the position of the hand and the bending angle of the fingers so as to drive the virtual hand to move to perform movement presentation and man-machine interaction in virtual environment. The invention is low in cost and capable of popularizing in greater user group, which is a new tool for improving more natural and harmonious man-machine interaction way.

The present invention discloses an electric power system electric energy-standby optimization scheduling method considering partition standby and N-1 verification. Therefore, a combined optimization model having maximum electric energy and standby cost and considering the partition standby is established. An initial preconceive accident N-1 safety constraint is added into the optimization model, an initial scheduling scheme is obtained through solution, the transmission lines in each partition is subjected to N-1 verification, if the verification passes, the scheme is the optimization scheduling scheme of the next time, if the verification does not pass, the corresponding N-1 verification format is added into the optimization scheduling model to solve and obtain a new scheduling scheme, and the verification mentioned above is repeatedly performed until all the transmission lines pass the N-1 verification so as to obtain the final optimization scheduling scheme. The electric power system electric energy-standby optimization scheduling method considering the partition standby and the N-1 verification is helpful for ensuring the safety of the electric power and the validity of the standby so as to realize the resource optimization configuration.

The invention discloses an intelligent parking system. The system includes a parking space publishing sub-system module, a parking space searching sub-system module, a parking space reservation management sub-system module, a parking space guiding sub-system module, a parking lot full-automatic recognition sub-system module, a parking space sharing management sub-system module, a parking lot management sub-system module, a reverse car searching sub-system module, an intelligent payment management system module, a handheld inspection and data collecting terminal module, a mobile phone APP client-side module, a smart parking management database module, a parking space information collecting system module, a public parking information comprehensive management and service sub-system module, atraffic analysis and decision sub-system module, an intersecting parking management sub-system module and a parking space detection and recognition device. By utilizing a big data platform of an internet of things to carry out integration and allocation of resource information, the parking efficiency is greatly improved, the problem that it is difficult to park a car can be effectively solved, andtraffic offence behaviors such as disorderly parking can be punished severely.

The invention provides a method for preparing 1,5-pentanediamine. The method comprises the steps of: a, dissolving lysine salt to obtain an aqueous solution of lysine salt; b, adding lysine decarboxylase and vitamin B6 coenzyme to the aqueous solution of lysine salt for a decarboxylation reaction of lysine; c. filtering a 1,5-pentanediamine salt solution obtained in step b by using an ultrafiltration membrane having a interception molecular weight being 3000-6000; d. selectively adsorbing vitamin B6 coenzyme in a 1,5-pentanediamine salt ultrafiltrate obtained in step c by using macroporous adsorption resin; e, sending the enzyme-removed 1,5-pentanediamine salt solution obtained in step d to a two-chamber bipolar membrane electrodialysis device for desalting; and f. performing concentrationand dehydration on the 1,5-pentanediamine aqueous solution obtained in the step e, then performing vacuum distillation, and performing condensation on a light phase to obtain a 1,5-pentanediamine product. The preparation method of the invention has the advantages of low cost, small environmental protection pressure, and high product purity, and is suitable for industrial application.

One or more embodiments of the present specification provide a firewall policy management method and a device thereof, the method comprises the following steps: acquiring policy information of a firewall, wherein the policy information comprises at least one policy; performing policy audit processing on the policy information to obtain a policy audit result; determining a strategy optimization instruction according to the strategy auditing result; and sending the strategy optimization instruction to the firewall so that the firewall executes the strategy optimization instruction to obtain an optimized strategy. According to the invention, unified management of firewall policies can be realized.

The invention discloses a partition optimization method for power system operation reserves of considering an interval support and section constraints. The method comprises the following steps: firstly, determining the types and the requirements of to-be-optimized reserves, partitioning a power grid and converting the partition reserve requirements into the overall reserve requirements of the system, and then carrying out equivalent processing on a power and a reserve support of the external power grid; and aiming at the minimum sum of the power generation cost and the reserve cost, considering a power balance equation, output power constraints of generators, ramp rate constraints of various reserves, capacity constraints of various reserves, transmission line constraints and section power constraints, and determining an allocation scheme for various partition reserves of the power system. The method carries out joint optimization on active outputs of various partitions and various reserves under the premises of fully utilizing the interval support and meeting the section constraints, well achieves optimal allocation of resources and has certain reference value for power grid planning and operating.

The invention provides a 110kV transformer-substation multi-dimension variable-parameter calculation reactive power compensation configuration method. The method comprises the following steps of firstly, selecting characteristic parameters which influence each factor of a power distribution network reactive power configuration requirement; secondly, constructing a 110kV sheet network calculation model and calculating reactive power compensation optimization configuration rates of a 110kV transformer substation under different characteristic states through changing the characteristic parameters; then, through carrying out sensitivity analysis on each characteristic parameter, calculating sensitiveness of the reactive power compensation optimization configuration rates to each characteristic parameter, after comparison, dividing the characteristic parameters into primary parameters and secondary parameters so as to form a method for the 110kV transformer substation to carry out reactive power compensation optimization configuration, wherein the characteristic parameters are taken as reference quantities. Aiming at the 110kV transformer substation with different characteristic states, different reactive power compensation configuration intervals are provided. A traditional sweeping approach or single section optimization reactive power configuration mode is changed and the reactive power compensation configuration of the 110kV transformer substation can be specifically and effectively guided.

The invention discloses a salesman calling incoming line allocation method, comprising the following steps: step 01, acquiring basic information of salesmen and seats, wherein the basic information ofthe salesmen includes service data of the salesmen, and the basic information of the seats includes the service satisfaction degree of the seats; step 02, separately performing level classification on the salesmen and the seats, performing star level classification on the salesmen according to the service data of the salesmen to form star level labels of the salesmen, and performing priority classification on the seats according to the service satisfaction degree of the seats to form priority labels of the seats; and step 03, allocating the salesmen to the corresponding seats according to a preset allocation strategy. A targeted allocation can be performed according to the star level of the salesmen and the priority of the seats, the further improvement of the service level of the salesmen can be facilitated, the effective utilization rate of seat resources can be improved, and the optimized allocation of the seat resources can be realized.

The invention provides a dynamic load balancing method taking user periodical resource demand into account in a cloud environment in order to resolve the technical problem of the load balancing problem in the cloud environment. The dynamic load balancing method includes the steps that each computing node has task reaching information lately recorded by a window, the size of the windows can be changed by analyzing the current window state, the future task intensity can be predicated through the task information of the current window, and the future task intensity predicted by each computing node is taken into account in the task distribution process. According to the scheme, the dynamic load balancing method predicts the future task intensity through the partial characteristic of the task instead of the overall historical task information and can obtain a more accurate and real-time predication result, thereby shortening the response time of the computing task.

The invention discloses a route selection method based on the sense of the network status, which is used in the intelligent self-sensing network. When the traffic transmitted in the network becomes larger and larger, the service category carried becomes more and more, the different types of service have the different characteristics, and the demands on the network also are different. In the self-sensing optical network, the optical network can distinguish the category of the service to be accessed, judge the characteristics and the demands on the optical network according to the service categories, and choose the different transmission route for the different service based on the characteristics and the demand, thereby achieving the optimal allocation of network resource based on the service demand. The invention can solve the transmission guarantee problem of the different services in the network, make full use of the own link resource, meet the personalized demand of the different services on the network, adapt to the high-quality and high-efficient transmission for large quantities of new services.

The invention discloses an HDMI (high-definition multimedia interface)-based hot plug detection circuit and a multimedia data transmission system using the same. The detection circuit comprises a first information channel and a second information channel, wherein the second information channel is connected between multimedia receiving equipment and multimedia output equipment and is used for correspondingly outputting high or low level to the multimedia output equipment according to the change of an electric signal of the multimedia receiving equipment and outputting multimedia data or not in correspondence to the high or low level through the multimedia output equipment. The multimedia data transmission system comprises the multimedia output equipment, the multimedia receiving equipment and the detection circuit connected between the multimedia output equipment and the multimedia receiving equipment. The detection circuit realizes bidirectional communication between the multimedia output equipment and the multimedia receiving equipment; the multimedia data transmission system realizes optimum distribution of resources and reduces resource waste.

A big data decision analysis system based on industrial Internet identifier analysis comprises front-end hardware equipment and an industrial cloud service platform, wherein the front-end hardware equipment comprises an information acquisition terminal; the information acquisition terminal uploads product or equipment information to the industrial cloud service platform through the Internet; the industrial cloud service platform comprises an edge layer, an IAAS layer, a general PAAS layer, an enterprise cloud platform application module, a data access module, a data fusion module, a WEB or mobile phone access module, an application layer, a network access module and a network security firewall. The invention further provides a big data decision analysis method based on industrial Internetidentifier analysis. Product tagging and identifier access are mainly completed on the edge layer, identifier data is rapidly and efficiently brought into a whole industrial Internet identifier analysis system in combination with a 5G network technology, and basic data support is provided for an identifier analysis-based big data decision analysis application service platform.