40results about How to "Scientific data support" patented technology

The invention discloses a device and a method for testing a gas-liquid sulfur phase permeation curve of a high-temperature high-pressure high-sulfur-content gas reservoir. The testing device comprises a displacement system, a stratum condition simulation system, a back-pressure system, a data testing system and a data acquisition system. The testing method comprises the following steps: selecting and treating a rock core; preparing rock core saturated stratum water and liquid sulfur; simulating a high-temperature and high-pressure environment of the stratum; determining the condition of liquid sulfur phase permeability under irreducible water saturation; performing a phase permeation test on filling of gas-liquid sulfur according to a set ratio; recording the amount VSi of liquid sulfur and the gas amount Vgi generated totally; correcting the stratum condition; calculating the relative permeability Krs of the liquid sulfur phase, the relative permeability Krg of the gas phase and the gas saturation Sg of a rock sample at each moment and the like. The device and the method disclosed by the invention can be used for safely, conveniently, rapidly, accurately and efficiently measuring the high-temperature high-pressure gas-liquid sulfur phase permeation data and providing scientific data support for making a reasonable development scheme for the high-sulfur-content gas reservoir.

The invention discloses a mine area vegetation carbon sink remote sensing inversion method for a fine land utilization type, and the method comprises the following steps: A, obtaining high-resolution image data, and carrying out the land utilization type classification through combining ground feature spectral curve features obtained by a high-spectral-resolution sensor; B, performing vegetation parameter inversion on the mining area image data by adopting a wave band operation mode, wherein vegetation parameters comprise a normalized vegetation index, a specific value vegetation index and vegetation coverage; C, dividing into a carbon sequestration area type by combining a land utilization type and a critical threshold value NDVIlim; and D, constructing a vegetation carbon sequestration parameter inversion model to perform inversion on the vegetation carbon sequestration area, and respectively obtaining the vegetation net primary productivity. According to the method, the land utilization types of the mining area are finely classified, the vegetation carbon sequestration capacity is partitioned, the light energy utilization rate model is constructed in combination with the remote sensing image and the ground actual measurement data, the precision degree of calculation of the vegetation carbon sequestration of the mining area is improved, and scientific data support can be provided for coal clean mining transformation and land reclamation decision making.

The present application provides an agricultural product traceability method, which includes: storing basic information of a target agricultural product, inspection task information of each stage in aplanting plan, inspection task execution result information of each stage in the planting plan, transportation trajectory information of the target agricultural product, and processing information ofthe target agricultural product into a block chain; generating a unique graphic code for each independent product of the target agricultural product, wherein the graphic code includes the traceability address of the target agricultural product, and the consumer accesses the relevant information of the target agricultural product stored in the block chain by scanning the graphic code. The invention realizes that the whole process data of agricultural products from the seed stage to the final sale to the consumers is stored in the block chain. By utilizing the tamper-proof property of the blockchain, the manager and the consumers can only access the data in the block chain, but can not tamper with the data, thus ensuring the safety and reliability of the data.

The invention relates to an intelligent base station energy saving management system, which is characterized in that the system comprises all base stations in a certain area, and an acquisition server, a data analysis server, a database server and a management server; the acquisition server performs statistics and acquisition to the operation data of the main apparatus in each base station; the analysis server analyzes and determines all data acquired by the acquisition server and preserves the analyzed data to the database server; and then the management server performs classification monitor and management based on the called analyzed data. According to the intelligent base station energy saving management system, a uniform and intelligent energy consumption pipe controlled system can be established, refinement for energy consumption cost budget pipe control can be raised; meter reading work efficiency and data accuracy can be raised, and stable work of the base stations can be ensured. The management platform can be improved, optimized and upgraded continuously, and the system combines technology innovation, maintainer's experience and wisdom perfectly.

The invention provides a case workload evaluation method, a judge performance evaluation method, a modeling method, a computation device and a computer-readable storage medium. The case workload evaluation method comprises the following steps of: aiming at each index in a process of handling a specific case by a judge, obtaining data corresponding to the index; obtaining a weighted value corresponding to each index; and computing a workload assessed value of the specific case according to the data and weighted value corresponding to each index. According to the case workload evaluation method, the workload of the specific case is assessed according to each link and the weight of each link in the process; and compared with the traditional method for carrying out subjective evaluation by workload evaluation committees, the case workload evaluation method considers problems more comprehensively, has data support and is more objective and persuasive.

The invention discloses a power grid operation and maintenance cost prediction method and prediction system. The method comprises the following steps: acquiring basic data related to the power grid operation and maintenance cost, wherein the basic data comprises the electricity consumption of the whole society, the GDP, the power consumption structure, the power grid valid asset net value, power transformation capacity, the line length, and the operation and maintenance cost; inputting the basic data acquired in the above step into a pre-established power grid operation and maintenance cost prediction model to compute, and outputting the expected power grid operation and maintenance cost. The power grid operation and maintenance cost prediction method and prediction system are used for predicting the operation and maintenance cost of the regional power grid, and can provide scientific data support for the power transmission and distribution cost checking, the power grid project feasibility research and post project evaluation and like works.

The invention relates to the geological disaster monitoring field based on Beidou, and especially relates to a high-voltage electric tower Beidou deformation monitoring and early warning system on anunstable slope. The system comprises a slope where a power transmission tower to be measured is located, a geological disaster safety data acquisition Beidou terminal, a local monitoring Beidou terminal and a geological disaster early warning terminal. The geological disaster safety data acquisition Beidou terminal is composed of a power supply device, a high-precision Beidou positioning sensor, alocal deformation data acquisition device and a data processing box. The local deformation data acquisition device is composed of a plurality of resistance-type semiconductor strain gauges. An acquisition device array is arranged on the unstable slope. The geological disaster safety data acquisition Beidou terminal carries out standardization processing on image signals and then transmits information to the local monitoring Beidou terminal through a Beidou satellite. The local monitoring Beidou terminal transmits the information to the geological disaster early warning terminal through judgment, and therefore monitoring and early warning are performed timely before geological disasters happen.

The invention provides an urban underground drainage pipe network data supplementing and perfecting method and system, and the method comprises the steps: marking a pipe type, and also comprises the following steps: filling pipe diameter or section shape data according to topology; setting a pipeline reference DEM; filling elevation according to the topological relation; and filling the elevationaccording to the default burial depth. The invention provides an urban underground drainage pipe network data supplementing and perfecting method and system. A scheme for automatically supplementing and perfecting urban pipe network data attributes is provided, and data of an urban underground water pipe network can be automatically and quickly supplemented and perfected by utilizing a method forrealizing data supplementing based on a spatial relationship and a method for filling an elevation value based on pipeline gradient.

The invention provides an organization personnel structure evaluation method, device and equipment, and a computer storage medium. The method comprises the steps of obtaining organization data and personnel data of each team in an organization from a database; generating team features of each team according to the total number of personnel and the personnel structure of each team; establishing anoptimization target; evaluating and calculating the team characteristics of the team to be optimized according to the optimization target, and outputting optimization parameters. According to the embodiment of the invention, the organization personnel structure is evaluated based on the organization data and the personnel data in the organization, the traditional low-efficiency subjective evaluation is solved, and the manpower and material resource investment caused by evaluation difficulty is reduced. Meanwhile, the embodiment of the invention can also be used for detecting an abnormal organization structure in an enterprise, and scientific data support is provided for subsequent talent inventory and other businesses.

The invention relates to the technical field of water purification plants, and discloses a modular intelligent water plant which comprises integrated water purification equipment, a modular adjusting water tank, a modular equipment room and a modular dosing room. The integrated water purification equipment comprises a flocculation unit, a precipitation unit and a filtering unit; the modularized equipment room comprises a backwashing water pump, a backwashing fan, a raw water turbidity monitoring instrument, factory water multi-parameter online water quality monitoring equipment, a plant water pump group, an automatic control system, a large-screen display system, a container type equipment room and the like; the modularized dosing room comprises an intelligent flocculant dosing device, a disinfectant preparation and dosing unit and a container type equipment room; the modularized adjusting water tank comprises a backwashing water tank and a clear water tank. The modularized intelligent water plant can realize modularization, informatization and automation of a plant area in a real sense.

The invention provides a layered optical measuring method of a fruit tree vertical structure and a device. Firstly, the ratio of photon flux densities of the fruit trees to environmental photon flux densities can be calculated by photon sensors arranged at different horizontal layers and aiming to different incident directions of sunlight and arranged at equal intervals in a line on different positions on the same horizontal layers, and therefore the incident light transmission rates on any photon positions can be acquired respectively; and then the incident light transmission rates and leaf angle distribution extinction coefficient are input in a light distribution model, and the leaf area indexes of the fruit trees on any photon positions are output; and finally by using a spatial interpolation method, based on the leaf area indexes, the leaf area distribution results on different horizontal layers are acquired, and therefore the leaf area distribution result of the fruit tree vertical structure can be acquired. The invention is advantageous in that based on the leaf area distribution result of the fruit tree vertical structure, the optimized assessment of the optical distribution and the optical utilization rate of the fruit tree structure is carried out, and therefore the scientific data support can be provided for fruit tree trimming or the fruit tree shape optimization.

The embodiment of the invention discloses an expressway roadside sensing equipment layout scheme evaluation method and system, and the method comprises the steps: determining a layout scheme evaluation index, and constructing a comprehensive evaluation index system; and based on the comprehensive evaluation index system, evaluating different layout schemes to obtain an optimal roadside sensing equipment layout scheme. Compared with an existing intelligent high-speed design which mainly focuses on historical experience and manufacturer opinions, the method has the advantages that the accuracy of the layout scheme of the highway roadside sensing equipment can be improved, and the roadside sensing equipment can play a huge role under limited configuration, so that the cost performance is relatively high; resource waste is avoided on the basis of meeting traffic perception requirements; in addition, the method can assist intelligent high-speed designers in improving work efficiency, reducing redundant workload, providing scientific data support for intelligent high-speed design and providing basis for compilation of related standard specifications.

The invention discloses a traffic travel mode recognition method based on wireless signals, and comprises the following steps: S1, collecting RSSI data, and positioning a moving target; S2, performing smoothing processing on the travel trajectory by using Kalman filtering; S3, determining a travel trajectory formed by travel of a single user, and extracting feature vectors about the average speedand the travel distance in the travel trajectory to obtain travel features of travelers; S4, identifying a rough identification travel mode based on the feature vector, wherein the rough identification travel mode comprises a walking mode, a bicycle mode and a motor vehicle mode; and S5, identifying a fine identification travel mode based on the parking point, wherein the fine identification travel mode comprises a bus mode and a car mode. The method has the advantages of high real-time dynamic property, wide identification types and high precision, and can provide accurate basic data supportfor urban traffic planning, design, control, management, monitoring and the like.

The invention provides a method and device for detecting the stacking degree of express cargos. The method comprises the steps: obtaining a cargo stacking image of a target station, taking the cargo stacking image as a prediction sample, inputting the prediction sample into a preset deep learning detection model, and using output of the deep learning detection model as a stacking degree detectionresult corresponding to the cargo stacking image of the target station, wherein the deep learning detection model is used for representing the corresponding relationship between the stacking type of the cargo stacking image and the stacking degree detection result. The detection algorithm is based on the principle of deep learning, can achieve automatic detection of the stacking degree of expresscargos, is efficient in detection process, and is accurate in detection result; and further a manager is helped to know the stacking condition of each cargo stacking region of a current express dispatching center in real time, and corresponding measures can be taken in time in a targeted manner.

The invention discloses an impact inclination electronic tag for cargo transportation monitoring and a monitoring method thereof, and the electronic tag comprises a housing, a PCB disposed in the housing, and an operation and indication panel pasted on the housing. An MCU, a low-power-consumption three-axis acceleration sensor, a button battery, a key switch, an LED impact event indicating lamp and an LED inclination event indicating lamp are welded to the PCB. The operation and indication panel is provided with indication windows of the LED impact event indication lamp and the LED inclination event indication lamp, a start button, an electronic tag serial number two-dimensional code and acceleration sensor three-axis direction identification. The impact inclination electronic tag can replace all functions of five existing mechanical warning tags, can be repeatedly used, is simpler and more convenient to install and detect, and can realize efficient digital management of transportation detection business by being matched with a corresponding software system.

The invention provides a method and a device for evaluating a forecast effect of power transmission line icing. The method comprises the following steps: determining evaluation parameters; and evaluating the forecast effect of power transmission line icing. The evaluation parameters comprise a skill score for the forecast effect of icing thickness, an optimal horizontal dimension, and a change trend of the skill score. The evaluation is objective, the phenomena of empty reporting and missing reporting is avoided, the evaluation result is reasonable, and the evaluation difficulty is reduced. According to the method and the device for evaluating the forecast effect of power transmission line icing, the forecast effect of power transmission line icing can be objectively and scientifically evaluated, and the availability and the applicability of the icing thickness forecast data are further improved, so that the operation and maintenance of the power grid are served. In addition, the availability of the forecast data can be maximized, scientific data support can be provided for maintenance personnel, and safe and stable operation of the power grid is guaranteed. Key parameters can be automatically set according to the factors such as icing time, icing thickness, icing type and other factors in different regions, so that the method and the device is closer to actual production of electric power, thereby maximally reducing labor cost and reducing resource waste.

The invention provides a method and a device for establishing a geomechanical model of a salt-cavern gas storage group, which are used for providing scientific and effective data support for evaluation of a to-be-established salt-cavern gas storage such as an ultra-deep salt-cavern gas storage group and ensuring reasonable selection of the to-be-established salt-cavern gas storage such as the ultra-deep salt-cavern gas storage group.