149results about How to "Improve enforceability" patented technology

An autonomous mission planning method for earth remote sensing satellites with multiple planning modes. First, the Earth observation targets to be planned are selected, so that a task set to be plan is obtained, and the Earth observation targets included in the planning task set are preprocessed, and then according to the task set to be planned after preprocessing, a long-period pre-coarse missionplan scheme sequence is obtained by carrying out long-period pre-coarse mission planning, and finally, short-period local window rolling planning is carried out on the long-period pre-coarse missionplanning scheme sequence according to the real-time updated environmental information and satellite maneuverability, and the emergency mission dynamic planning is carried out according to the high-priority ground emergency observation mission. The long-period pre-coarse mission planning scheme sequence is obtained by carrying out long-period pre-coarse mission planning.

The invention discloses a system and a method for realizing OTA upgrade of embedded hardware based on a block chain. The method comprises the following steps: constructing a P2P network topological structure comprising a plurality of service nodes downloaded by firmware; taking one service node as a first block node, and converting other service nodes in the P2P network into one block node on theblock chain one by one through a block chain consensus verification mechanism; storing the latest firmware software on the service node, and calculating the node content by using a Hash algorithm to obtain a Hash value of the service node; wherein the node content comprises feature information of the service node and firmware software stored on the service node; and the intelligent terminal downloads the corresponding hash value from the service node of the P2P network, carries out firmware version security verification according to the hash value, downloads and stores the verified firmware software, and upgrades the firmware software. The safe and credible P2P network topological structure is established by using the block chain technology, and the OTA upgrading reliability and safety ofthe intelligent terminal are improved.

The invention provides a plan optimization method used for a supply chain of a chemical enterprise. The plan optimization method belongs to the field of optimization methods, and comprises the steps of: acquiring initial parameters of the supply chain, and storing the initial parameters of the supply chain in a data warehouse; determining anticipated market requirements corresponding to the chemical enterprise through adopting a self-matching requirement forecasting algorithm by combining with sales data of the chemical company over the years, constructing a supply chain plan optimization model, setting a plan optimization objective function and constraint conditions in the supply chain plan optimization model, and calculating to obtain an optimal solution of the plan optimization objective function under the constraint conditions; and setting parameter step lengths, automatically constructing different plan optimization production scheduling schemes, calculating a profit correspondingto each plan scheme, and selecting the plan scheme corresponding to the highest profit for optimizing relevant parameters of the enterprise supply chain. The plan optimization method can provide theplan scheme for economical optimization solution when balancing supply and demand, so as to achieve dynamic adjustment of product structure, improve the precision, performability and working efficiency of the plan, and provide information support for production management.

When connection of the host and the peripheral device is detected, it is searched whether or not the driver is installed in the host. When the search result shows that the driver is not installed in the host, the driver stored in the storage of the peripheral device is read out and installed in the host. Upon detection of connection of the host and the peripheral device, the storage mode bringing the storage into active state is initialized. Upon detection that the driver has already been installed in the host in the search processing step, or when installation of the driver has been completed in the installation processing; step, the mode is switched over into the peripheral device mode which brings the peripheral device except for the storage into active state.

The invention discloses an intelligent vehicle driving decision method based on a generating countermeasure network, which comprises establishing a driving decision model and driving decision control.The invention processes the driving image based on the generated antagonistic network, can process the vehicle driving path planning under the non-ideal road condition, and improves the executabilityof the end-to-end neural network. The invention extracts the most essential characteristics of driving images through the generated antagonistic network processing, maps the driving data of differentsources into a unified virtual domain, realizes the application of reinforcement learning to a real vehicle, improves the generalization of the network and adapts to the ability of different samples.For the input of the driving image, the input image used each time is the first several frames of the current time stamp video image. The predicted images obtained by this method can be used to judgethe driving decision-making planning to a greater extent. As the basis for predicting the optimal decision of the vehicle, the invention builds a bridge from the reinforcement learning to the real vehicle application.

The invention discloses a smart cooking system including a kitchen range, cooking utensils, an electronic control module and a weighing module. The weighing module is used for weighing food material.The electronic control module is used for controlling the magnitude of heat power of the kitchen range in different phases of a cooking process according to the food material types in a preset recipeand food material cooking temperature range corresponding to the food material types. The electronic control module is also used for controlling the heat power lasting time of the kitchen range in different phases of a cooking process according to the food material types in the preset recipe and food material cooking time durations corresponding to food weights. The preset recipe includes the foodmaterial types and the cooking process. According to the invention, a traditional recipe is made into a functional cooking process recipe; the corresponding heat power and the heat power lasting timeof the kitchen range according to the different food materials in the recipe and the food material weights, so that requirements for cooking temperature and cooking time range of the food material inthe recipe can be met and a cooking effect meeting the target of a user can be achieved.

The invention discloses a vehicle path scheduling method and a vehicle path scheduling device. The vehicle path scheduling method comprises the following steps: acquiring a starting point and a destination of a vehicle, and positioning the starting point in a map, wherein the map comprises a road attribute; acquiring vehicle information of the vehicle; scheduling the global path from the startingpoint to the destination according to the vehicle information and the road attribute. According to the vehicle path scheduling method and the vehicle path scheduling device, the vehicle path scheduling enforceability is improved by the generated optimal global path when an intelligent vehicle travels.

The invention provides a bilayer planning method for intelligent scheduling for steelmaking-continuous welding production. The method comprises the following specific steps: describing a problem of solving a production lot plan and a production time plan as a system optimizing problem with a bilayer hierarchical structure by combining with the hierarchy characteristics of steelmaking-continuous welding production scheduling; simultaneously researching two classes of plans in the same model; and carrying out global consideration on two classes of plans while an optimization target is set and an optimization variable is selected. In the built bilayer planning model for the intelligent scheduling for steelmaking-continuous welding production, an upper-layer scheduling is a problem of combining, sorting and distributing cast; and low-layer scheduling is a problem of searching optimized production time on the premise of known cast plan. By utilizing the bilayer planning method, the defect existing in the traditional compilation mode of the steelmaking-continuous welding production plan can be avoided, and the plan enforceability as well as the authenticity and the practicality of a plan optimization result can be improved. A sulphur removal station and an LF (Ladle furance) furnace serve as a buffer link in the whole-factory production scheduling, and the flexibility of the plan is enhanced.

The invention discloses an intelligent energy consumption service cooperative control system and method. The system comprises an energy controller, an edge computing terminal and a cloud service platform. The energy controller captures equipment operation characteristics, identifies equipment operation conditions and elastically sends a control instruction to the equipment; the edge computing terminal configures a user energy system in a self-adaptive manner, identifies user energy consumption behavior characteristics, and generates an equipment operation control strategy in a self-adaptive manner through cooperative interaction with each energy controller in the user energy system; and the cloud service platform customizes a top-layer operation control strategy for different users according to the demand elements, pushes the top-layer operation control strategy to the user side edge computing terminal, and completes user interaction and background maintenance. The problems that a traditional energy monitoring terminal is insufficient in control capacity, a user side self-adaptive control strategy generation capacity is insufficient, and an intelligent energy consumption cloud service platform cannot control energy consumption equipment in real time are solved, and a cloud-side-end system framework is innovatively provided for an intelligent energy consumption system.

The invention discloses a method for automatically installing an RAID card FW and a KUX operating system. The method includes the concrete steps that a series of operations including command lines and restart needing to be executed are connected in series to be made into an executable file; mirror images of the executable file, a refreshing tool, a refreshing file and the operating system are all copied into a U disk; then the executable file is run in a K-UX rescue mode to achieve U disk mounting, folder building, uncompressing, copying, duplicating, refreshing command executing, RAID making, automatic mirror image mounting and operating system installing step by step. Compared with the prior art, all items operated through a command line can be edited into the executable file, production staff or unprofessional customers can complete the complex process by running the executable file simply, and therefore trouble and labor are saved.

The invention discloses an unmanned vehicle control method based on over-the-horizon synergetic cognition and an unmanned vehicle control system based on over-the-horizon synergetic cognition, and belongs to the field of intelligent traffic. The control system comprises an unmanned vehicle and an unmanned driving network supporting platform. The unmanned vehicle comprises an individual situation cognition system and a driving decision generation system. The unmanned driving network supporting platform comprises a global situation cognition system, a local situation cognition system and a driving decision generation system. The control method applying the control system comprises the steps that firstly the individual situation cognition system forms micro driving situation cognition; then the driving decision generation system receives information and processes the information and then issues the information to the driving decision generation system, and the driving decision generationsystem generates the final driving operation; and finally the unmanned vehicle receives and performs the final driving operation through the driving actuator. Real-time cognition of the traffic environmental situation is performed on the network terminal so that safe, efficient and reliable unmanned driving can be realized and the operability and the effectiveness of the unmanned vehicle controlsservice can be enhanced.

The invention provides a monthly power generating plan optimization and safety checking method based on load characteristic periods. The method includes the steps of I collecting basic data, II extracting characteristic periods of a load curve, III modeling monthly set combination, IV modeling electric quantity safety checking, V solving the monthly set combination and the safety checking, and VI displaying and outputting the results. In order to solve the problem of high dimension and large scale optimization of monthly plan compiling, a period reduction method based on load curve characteristic extraction is provided. The calculating efficiency is improved under the prerequisite of ensuring calculating precision, and the transaction (plan) execution and safety constraint of a power grid are considered directly from electric quantity perspective, the trend of electric power and electric quantity conversion is not needed, and safety checking of electric power and electric quantity decoupling is realized. The assessment of transmitting demand and capability of a power transmission channel is realized, and integrated modeling and solving of monthly set combination and the electric power and electric quantity safety checking are realized.

The invention provides a power grid power transmission margin control method suitable for large-scale wind power access. The method includes the steps that (1), security constraint unit commitment optimal computation is carried out by adopting a mixed integer planning method to obtain starting and stopping states and power output plans of a conventional power generation unit meeting an objective function and constraint conditions; (2), the influence on power transmission margin by multi-period wind power randomness is quantized by adopting a probability power flow method to obtain a power flow probability distribution range of a power grid branch or a power transmission fracture surface; (3), whether the power flow probability distribution range meets the requirement of a confidence interval or not is judged, if not, the step (1) is executed again, unit commitment optimal computation is carried out again, and the power output plans are adjusted. Compared with the prior art, the power grid power transmission margin control method suitable for large-scale wind power access fully considers randomness of wind power, improves the using effect of short-period security constraint dispatching plans in a wind power access area and enhances performability of the short-period plans.

The invention discloses a method for optimizing a bogie procedure in an advanced repair task of a motor train unit and an advanced repair planning and scheduling method and system for the motor train unit. The advanced repair planning and scheduling method for the motor train unit includes the steps of receiving a scheduling time period and an advanced repair task in the time period, determining space overhaul capacity of a motor train with the advanced repair task, determining total time and work load in a unit time in the bogie procedure in advanced repair programs corresponding to vehicle types in the advanced repair task, determining the time when the motor train unit enters a warehouse in the advanced repair task, building a mixed integer programming model of the advanced repair program of the motor train set on the basis of the scheduling time period, the advanced repair task, the total time and the work load in a unit time in the bogie procedure and the time when the motor train unit enters the warehouse, and calculating a feasible solution of an output model. The plan of the advanced repair of the motor train unit can be efficiently made, and existing overhaul spaces and equipment can be made use of to the largest extent by means of the advanced repair task of the motor train unit.

The embodiment of the invention discloses a method and device for controlling budget information. The method includes: obtaining reimbursement application information uploaded by a reimbursement user,and providing the reimbursement application information for a corresponding approval user; acquiring, according to the user attribute of the reimbursement user and/or the reimbursement attribute of the reimbursement application information, a currently unlocked first target budget amount; if it is determined that the reimbursement amount in the reimbursement application information is less than or equal to the first target budget amount, locking the reimbursement amount in the first target budget amount; and if successful approval information corresponding to the reimbursement application information and returned from the approval user is received, releasing a locking amount corresponding to the reimbursement application information to the first target budget amount; deducting a successful reimbursement amount corresponding to the successful approval information from the first target budget amount, and recording a corresponding reimbursement processing result. The method organically links the budget and the reimbursement and enhances the operability of cost budget variance analysis.

The invention provides a semanteme service combination method based on dynamic planning. The semanteme service combination method based on the dynamic planning comprises firstly, decomposing a manufacturing service process model through a workflow engine, extracting requirements of each active node, and then obtaining all services which satisfy the active node through a service find matching process, and at last, selecting an appropriate candidate service from the services to generate a service combined scheme according to a certain strategy, achieving mapping a specific semanteme onto a task, and using a manufacturing service process which is described in a workflow model to translate a generating process of the semanteme service combined scheme into a dynamic evolution multistage decision process by combining characteristics of a networked manufacturing mode, using a data semanteme relationship between services as restraint, using comprehensive quality of the combined scheme as an optimization target, and using a dynamic planning method to generate a combined scheme which is globally optimum. The semanteme service combination method based on the dynamic planning has the advantages of enabling confirmation of a globally optimum solution to be easy, saving computing amount, being beneficial for providing abundant combined scheme results for a user, and improving performability of the combined scheme and automation degree of a combining process.

The invention discloses a test case processing method and device. The method comprises the following steps of under the condition that a mind map file case is received, analyzing the mind map file case to generate a test case; determining whether the test case is an incomplete case or not by performing integrity detection on the test case; when it is determined that the test case is the incompletecase, determining that the test case is a complete case, wherein the incomplete use case at least comprises a use case which does not meet the format requirement of the test case, and the format of the test case at least comprises one of a use case module, a use case name, a use case condition, a use case step and an expected result. The technical problems that an existing test case processing method is low in readability and executive property of the test case, are solved.

The invention provides a crude oil dispatching and production scheduling method and a crude oil dispatching and production scheduling system. The crude oil dispatching and production scheduling method comprises the steps of acquiring crude oil blending ratio parameters and crude oil dispatching and production scheduling parameters; establishing a crude oil blending ratio calculation model, and acquiring a crude oil blending ratio according to the crude oil blending ratio calculation model and the crude oil blending ratio parameters, thereby completing optimal setting of a limited configurable crude oil blending ratio, and reducing production cost of oil refining enterprises; establishing a crude oil dispatching and production scheduling optimization model, and generating a crude oil dispatching and production scheduling scheme according to the crude oil dispatching and production scheduling optimization model, the crude oil blending ratio and the crude oil dispatching and production scheduling parameters; and finally generating a crude oil dispatching and production scheduling plan report according to the crude oil blending ratio and the crude oil dispatching and production scheduling scheme, and issuing the crude oil dispatching and production scheduling plan report to workshops for execution. Therefore, the accuracy, executability and working efficiency of crude oil dispatching and production scheduling are improved.

A calibration method for a digital-to-analog converter (DAC) is disclosed. The DAC is applied to a successive approximation analog-to-digital converter (SA ADC) and includes a first capacitor, multiple second capacitors and a bridge capacitor. The method includes the steps of: (a) controlling voltages at two input terminals of a comparator of the SA ADC to be equal; (b) changing a voltage at a first terminal of the first capacitor; (b) obtaining a first output of the SA ADC; (d) after obtaining the first output, controlling voltages at the two input terminals of the comparator to be equal; (e) changing voltages at multiple first terminals of the second capacitors; (f) obtaining a second output of the SA ADC; and (g) calibrating the DAC according to the first output and the second output.

The invention relates to a system and a method of fused magnesium production energy management based on BOM (Bill of Materials) and MRP (Material Requirement Planning) algorithms. The system comprises a sales management module, an inventory management module, a procurement management module, a product BOM module, an MRP computing module, a production planning module, an electric energy planning module, a production dispatching module, an electric energy counting module and an electric energy monitoring module; the fused magnesium production energy management method comprises the steps: performing MRP computation according to fused magnesium BOM, sales order quantity demand of the fused magnesium, delivery date of the fused magnesium, available inventory quantity information of the fused magnesium, available inventory quantity information of magnesite ores and available inventory quantity information of graphite electrodes; and generating electrical energy requirement planning, procurement planning of raw materials and production planning. According to the system and the method of fused magnesium production energy management based on BOM and MRP algorithms, the formulating efficiency and accuracy and the operability of the production planning, the procurement planning and the electric energy requirement planning of fused magnesium enterprises can be improved greatly; the plans match with the sales order requirement, so that the production can be organized as planned and the just-in-time delivery of the order is guaranteed.

The invention provides a snoring sound signal identification method. The method comprises the following steps of acquiring audio information of a preset sleep time period, and extracting Mel-frequencycepstral coefficients of the audio information as training samples; classifying the training samples into snoring sounds and non snoring sounds by utilizing a k-means clustering algorithm, and then removing the non snoring sounds according to a clustering result, so that a snoring sound training set is obtained; performing training by a Gaussian mixture model to obtain an identification model; calculating the generation probabilities of the snoring sounds in the training set by utilizing the identification model, arranging the generation probabilities in an ascending order, and taking front preset percentage data as a snoring sound generation probability threshold of an experiment object; and acquiring an audio segment by an audio acquisition device, extracting a Mel-frequency cepstral coefficient of the audio segment, then using the model to calculate the generation probability of the audio segment, and judging whether the audio segment is the snoring sound of the experiment object or not. According to the method, preprocessing operation is carried out on an original snoring sound signal, so that the processing amount of the data can be effectively reduced, and the distinguishingdegree of the snoring sound and non-snoring sound signals can be increased.

The invention discloses a progress plan quick compilation method based on BIM and big data. The method comprises the following steps: 1) hierarchical naming management of project components; 2) project working day quota and component construction process standardization; 3) automatic generation of a progress plan based on BIM; 4) collection and analysis of actual construction progress; and 5) automatic updating of a progress plan automatic compilation quota database. The progress plan quick compilation method based on BIM and big data improves project progress plan compilation efficiency, improves project progress plan compilation scientificity and feasibility and ensures traceability of the whole process of the construction process information.