82 results about "Monthly average" patented technology

The invention discloses an analysis method and device for charging transaction data of charging stations. The method comprises that basic information, which at least includes the number of the charging station, information of charging piles, position information and the type of the station, of each charging station is obtained; transaction data which is generated by the charging station in charging transaction is collected; the transaction data is pre-processed to obtain pre-processing data; and an analysis model is established according to the basic information and the pre-processing data, and operation parameters, which at least comprise the utilization rate of the charging station, the monthly averaged charging load parameter, the charging time parameter of the charging station and the manner of turnover, of the charging station are determined via the analysis model. Tedious operations in traditional table handling is avoided, the working efficiency is improved, the error rate is reduced, and the technical problems that manual analysis on the transaction data of the charging station causes low analysis efficiency and high error rate are solved.

The invention relates to a method for operating cross-basin cascade hydropower station groups under the condition of dynamic commissioning of giant hydropower stations for a long term. The method includes steps of 1, predicting load; 2, deducting power station output procedures not participating in computation from monthly average load; 3, computing natural inflow procedures at different frequencies of basins in whole networks; 4, computing output procedures of various hydropower stations; 5, computing output procedures of thermal power stations. The method has the advantages that actual operation characteristics of Yunnan power grids are combined with one another, the hydropower stations are divided into two categories including a category participating in computation and a category not participating in computation, the power stations participating in computation mainly include the hydropower stations and the thermal power stations which are good in regulation performance and have large installation scales, the power stations not participating in computation mainly include hydropower stations and partial thermal power stations which are low in wind-power, photovoltaic and weekly regulation performance and only change slightly in long-term operation procedures, and the output procedures of the power stations not participating in computation can be given according to actual operation conditions of the power grids.

The invention puts forward an urban tidal river reach ecological water demand prediction method based on a neural network, and belongs to the field of ecological hydrology. The method comprises the following steps that: firstly, carrying out statistics on the monthly seawater salinity and sea-entering water quantity of the estuary of the urban tidal river reach in multiple years to obtain the monthly salt balance water demand of the river reach and establish the monthly salt balance water demand prediction network of the urban tidal river reach; then, independently obtaining the monthly average rain capacity, average sea surface temperature, total sewage discharge amount and ecological water demand of the river reach, and establishing the monthly ecological water demand prediction network of the urban tidal river reach; and independently obtaining the prediction value of the monthly total sewage discharge amount, the monthly sea-entering water quality prediction value and the monthly average rain capacity prediction value of the river reach in certain year in the future, inputting into the ecological water demand prediction network, and outputting the ecological water demand prediction result of the urban tidal river reach under different conditions. By use of the method, the special properties of the urban tidal river reach are comprehensively considered, a practical situation is conformed, the change situation of the river reach ecological water demand in the future is predicted, and a reference is provided for a decision department.

The present invention provides a probability weighting FDC method-based river ecological water demand calculation method. The method comprises the steps of performing frequency analysis on runoff data series, and dividing an annual average runoff series and a monthly average runoff series into a flood season group, an ordinary season group and a dry season group; building a daily flow duration curve for the flood season group, the ordinary season group and the dry season group of each month, selecting flows corresponding to 90% durations as ecological water demand, and calculating monthly ecological water demand of an initial typical year of the flood season, the ordinary season and the dry season; building joint distribution of annual and monthly water probability by using a Copula function, and calculating a probability weight; and calculating monthly ecological water demand of a final typical year of the flood season, the ordinary season and the dry season by using the calculated monthly ecological water demand of the initial typical year of the flood season, the ordinary season and the dry season and the probability weight. A new technological solution is provided for quantitative analysis of the river ecological water demand, the probability weight concept and the calculation method are raised for the first time, and a more reasonable river ecological water demand result is obtained on the basis of a flow duration curve method by calculating condition probabilities of annual and monthly flood seasons, ordinary seasons and dry seasons.

The invention discloses a maximum joint entropy criterion-based least square support vector machine power prediction method. The method comprises the following steps of: 1, constructing an input dataset via same-term electricity consumptions of past three years and corresponding monthly average temperatures, and constructing an electricity sale quantity prediction model for to-be-predicted monthsby using a least square support vector machine method; 2, carrying out data preprocessing; 3, normalizing the input data set; 4, aiming at the history electricity consumptions, carrying out electricity sale quantity prediction by selecting a least square support vector machine model; 5, optimizing key parameters <sigma>0 and <sigma> of the model so as to determine an optimal parameter; 6, optimizing the key parameters <sigma>0 and <sigma>; 7, selecting a monthly relative error and an annual average error as evaluation indexes of the prediction result and calculating prediction precision at the time; and 8, carrying out prediction for at least 3-5 times and taking an average value. The method is capable of carrying out electricity sale quantity prediction on users.

The invention relates to base frame operation and maintenance, and provides a server operation power consumption management method and device and a storage medium, and the method comprises the steps:classifying servers of a data center according to the same brand and configuration; Collecting actual power consumption values of the same type of servers and establishing an actual power consumptionload relation table; calculating the actual power consumption of the same type of servers by adopting the following mode: the estimated value power consumption is equal to the actual power consumptionof the cabinets/the number of the cabinet servers, wherein the same kind of servers are installed on the cabinets, and a cabinet configuration server scheme is formed according to the estimated valuepower consumption or the monthly average actual power consumption or the current season average actual power consumption of the same kind of servers in combination with the rated power consumption ofthe cabinets. According to the invention, the actual power consumption of the server in the cabinet is monitored, and the cabinet is configured based on the actual power consumption of the server, sothat the cabinet utilization rate can be improved, and the cabinet space waste is reduced. The power supply utilization rate of the cabinet is improved, and the PUE value is reduced.

The invention discloses a temperature/ economic growth factor considered monthly total electricity consumption predication method. The method comprises the steps of creating a linear regression technique for the monthly total electricity consumption, the current average temperature and the economic growth index; predicating monthly total electricity consumption, including historic total electricity consumption of the same month as the predicated month and monthly average temperature data; expressing the economic growth factor through the time trend term; building a time trend term included predication model; acquiring the historic above-scale industrial added value growth rate data of the same month as the predicated month and obtaining the economic growth index; building an economic growth index included predication model; calculating the total electricity consumption of the predicated month by two equation methods of the predicated models. The method has the advantages that the temperature/ economic growth factor considered monthly total electricity consumption predication models are utilized to obtain the predicated monthly total electricity consumption, which is beneficial for power planning and the preparation of production schedule and monthly production planning of a power grid.

The invention discloses a method for measuring peak sunshine hours, which comprises the following steps: (1) using calibrated standard solar cells to divide each day into N time periods with a duration of t and measuring instantaneous radiation intensity S of each time period, wherein the daily radiation quantity can be calculated according to an equation that Q is equal to N,S and t and the corresponding daily peak sunshine hours can be calculated according to an equation that Hp is equal to NST/1,000; (2) obtaining daily average peak sunshine hours of each month and yearly average peak sunshine hours by using an averaging method; and (3) storing and exporting the data on the daily peak sunshine hours, monthly average peak sunshine hours and yearly average peak sunshine hours. The method can directly obtain peak sunshine hours and make photovoltaic system design more visual and convenient.

The invention relates to the technical field of photovoltaics, and discloses a photovoltaic annual generating capacity calculation method based on machine learning, which comprises the following steps: S1, applying a time sequence correlation model to predict irradiance: a1, collecting monthly actual measurement meteorological data of all meteorological stations in a region where a power station is located in history of 10 years, averaging the data, and fitting the data by utilizing an ARp-order autoregressive process; a2, calculating parameter items through simulation, and predicting the monthly average radiation value and temperature of the next year; a3, calculating an illumination intensity distribution curve of the photovoltaic power station in the past year, namely the ratio of illumination time to annual illumination time under each illumination intensity; s2, predicting the generating capacity by utilizing a sample plate assembly method: b1, taking ten sample plate assemblies from different matrixes of a power station, and determining an IV curve and a temperature coefficient of the sample plate assemblies in a laboratory; the photovoltaic annual generating capacity calculation method based on machine learning can solve the problem that simulation carried out by existing mainstream photovoltaic power station simulation software is rough at present.

The invention provides a preparation method of a composite potassium monopersulfate disinfectant and antibacterial application thereof in water treatment. The preparation method comprises the steps ofsynthesizing monopersulfuric acid with 30% by mass of hydrogen peroxide and 98% by mass of sulfuric acid, and adding potassium carbonate into the monopersulfuric acid in batch manner to obtain the composite potassium monopersulfate. The composite potassium monopersulfate has excellent performance, with active oxygen content of 3.2-3.4%, monthly average active oxygen loss rate of 0.4% and below, and water content of less than 0.08%; the prepared composite potassium monopersulfate has a wide range of antimicrobial effects, features stability, high efficiency and safety and helps environmentallysolve the problem of disinfection and purification in water treatment.

The invention discloses a production forecasting method. The production forecasting method includes the steps of filtering out sample data; respectively counting output data of the sample data by year, month and day; calculating annual weighted output B and monthly average weighted output T0, wherein T0 is equal to B/12; calculating monthly average weighted output T1 and respectively counting average working day output, average daily output over the weekend and average daily output over holidays; calculating correction factor K, wherein K is equal to T0/T1; Summing up and calculating monthly forecast total output P; comparing the monthly forecast total output P with real production volume to conduct production control. The production forecasting method has the advantages that with the realproduction volume compared with the forecast value by day, month and accumulative value, whether the current day, the current month output and the cumulative output are up to the standard is respectively judged, so that timely corrective measures can be made to correct deviations from expectations in a timely manner and avoid enlargement of deviations; through comparison of correction coefficientK and 1, whether this year's mission target Y0 is high or low can be obtained, so that correction is adopted to increase or reduce the daily forecast output.

The invention relates to an enameled brick for an oven door of a coke oven and belongs to the technical field of fireproofing material preparation. The enameled brick consists of a brick body and a glaze material coated on the surface of the brick body. The enameled brick is characterized in that the glaze material is prepared from the following ingredients in parts by weight: 45 to 55 parts of feldspar, 5 to 15 parts of quartz, 10 to 18 parts of stalactite, 0 to 6 parts of ripe talc, 4 to 10 parts of raw datong, 0 to 4 parts of Suzhou soil, 1 to 8 parts of alumina, 10 to 20 parts of zircon powder and 3 to 8 parts of barium carbonate. The oven door of the coke oven built by the enameled brick for the oven door of the coke oven provided by the invention has the advantages that the low freecarbon granule and tar penetration adhesion phenomenon can be reduced, the surface carbon deposition condition of the oven door is obviously improved in the use process, the average month adhesion deposition-free thickness is 1 to 2mm, the monthly average cleaning times are 2 to 4, the cleaning times and the cleaning difficulty of the carbon deposition of the oven door of the coke oven are effectively reduced, and the mechanical damage to the oven door of the coke oven in the cleaning process is reduced. Through the monitoring on the enameled brick used for one year, the brick body of the enameled brick for the oven door of the coke oven does not have the damage phenomenon, and the brick body surface of the brick for the oven door of the coke oven does not have tar penetration conditions.

The invention discloses a calculation method for the ecological water requirement of an affected plain area river network, and provides a river ecological water requirement calculation method suitable for the affected plain area river network and constructed based on attached diatom indicative characters. The method includes the steps that survey spot positions and survey frequency are determined first; an attached diatom integrality index and a threshold value interval in a river network region are determined secondly; the quantitative analysis relation between the attached diatom integrality index of survey spots and a monthly averaged river flow rate measured actually is set up, and ecological flow rate control values in a river channel for maintaining different target ecological flow rates are determined correspondingly according to the threshold value interval of the attached diatom integrality index; according to flow cross sections determined by the different ecological flow rate control values and the annual average month-by month water level of the river channel, ecological flow rates for maintaining different healthy targets in the river channel, of all months are determined. Key technology support can be provided for determining a corresponding ecological water requirement control target for river ecological health maintenance and water conservancy project regulation and control of the plain river network area greatly affected by human activities.

The invention, which relates to the function algorithm field of automotive power batteries, aims at providing a big-data-based SOH estimation method having high applicability, thereby saving the manpower. The method comprises: step one, the rated capacity of a power battery is measured and the measured rated capacity is uploaded to a bid data platform for storage; step two, when the power batterycarries out direct-current charging each time, related data of the power battery are collected and the collected data are uploaded to the big data platform, and the big data platform calculates a real-time capacity of the power battery and stores the real-time capacity; step three, a monthly average capacity is calculated based on the stored real-time capacity and a relative SOH is calculated based on a ratio of the average capacity to the rated capacity; step four, polynomial fitting is carried out to obtain a fitting curve of the relative SOH; and step five, when new relative SOH data are obtained, the fitting curve obtained by the step four is corrected. Therefore, the manpower is saved. The method has the high applicability.

The embodiment of the invention provides a network load prediction method and device. The method comprises the following steps: after a specific package is popularized, calculating monthly average useflow increment of a single user according to the use proportion of each package user and the use saturation of the package; calculating the daily average total flow of the cell according to the monthly average use flow amplification of the single user; calculating the total flow of the cell during self-busy and the uplink and downlink total flow of the cell during self-busy according to the dailyaverage total flow of the cell; calculating the uplink and downlink PRB utilization rate of the cell when the cell is self-busy according to the uplink and downlink flow growth rate of the cell whenthe cell is self-busy; calculating an effective RRC connection average value when the cell is self-busy according to the increment of the effective RRC connection user number of the cell after the package is popularized; and determining a high-load cell according to the uplink and downlink PRB utilization rate when the cell is self-busy, the effective RRC connection average number when the cell isself-busy and the uplink and downlink total flow when the cell is self-busy. According to the embodiment of the invention, the high-load cell to be expanded can be accurately predicted, so that targeted expansion optimization is carried out.

The invention discloses a BPNN-based NDVI prediction method for the grassland area of northern China, including: a BPNN prediction model of monthly average rainfall in the future annual growth seasonis established; the monthly average rainfall-NDVI mapping model for future growing seasons is established; The monthly average rainfall forecast value of the future growing season generated by the rainfall BPNN forecast model is substituted into the rainfall-NDVI mapping model, the NDVI monthly average forecast value in the future growth season is obtained. The invention can accurately predict theaverage value of the NDVI in the growing season (June to August), thereby realizing the evaluation of the number of grazable livestock (carrying capacity) in the future years according to the predicted value of the NDVI. The method is conducive to realizing the dynamic grazing strategy based on the predictable climatic conditions, so as to avoid the occurrence of overgrazing in the disaster years.

The invention discloses an accurate algorithm for correcting an electric quantity and a power factor under three-phase three-wire electric-energy-meter false wiring and belongs to the power supply technology field. Through analyzing an inner link of an active electric quantity WPX, a reactive electric quantity WQX and expressions of a correct active electric quantity WP0 and a reactive electric quantity WQ0 under false wiring, the correct active electric quantity WP0 and the reactive electric quantity WQ0 are calculated and an actual monthly-average power factor of a load is determined. Through the power factor, a correct active electric quantity and a corrected electric quantity can be accurately calculated. Under the condition of intelligent electric-energy-meter false wiring, a great guiding significance is possessed to work of electric charge recovery. And a blank of an accurate electric quantity correcting calculation method under the three-phase three-wire intelligent electric-energy-meter false wiring in practical work is filled.

The invention discloses a TDNN-based prediction method for NDVI in the grassland area of northern China: establishing a TDNN prediction model of monthly average rainfall in the future year growth seasons; establishing a future year growth season monthly average rainfall-NDVI mapping model; putting the future year growth season rainfall monthly average prediction value generated by the rainfall TDNN prediction model into the rainfall-NDVI mapping model to obtain the future year growth season NDVI monthly average prediction value. The invention can accurately predict the average value of the NDVI in the growing seasons (June to August), thereby realizing the evaluation of the number of grazable livestock (carrying capacity) in the future years according to the prediction value of the NDVI. The method is conducive to realizing the dynamic grazing strategy based on the predictable climatic conditions, so as to avoid the occurrence of overgrazing in the disaster years.

A method for calculating the length of insulated water ditch at tunnel entrance in cold and severe cold area features that the solar radiation at tunnel entrance in cold and severe cold area is analyzed and the solar radiation index at tunnel entrance is calculated. Taking the solar radiation index at the tunnel entrance, the coldest monthly average temperature at the tunnel entrance, the measuredice length of the drainage channel, the corresponding length of the insulating ditch and the ice length of the ditch as the influencing factors, the nonlinear curved surface equation is formulated. Using multiple nonlinear regression, the undetermined parameters of multiple nonlinear curved surface equation are calculated, and the formula for calculating the length of tunnel thermal insulation ditch in cold and severe cold regions is obtained. The invention overcomes the shortcoming that the prior art can not theoretically qualitatively and quantitatively analyze the length of the heat preservation water ditch, puts forward a pertinent calculation method, and improves the accuracy of the calculation of the length of the heat preservation water ditch at the tunnel entrance in cold and severe cold regions.

A fare searching program preferably implemented as a website connected to at least one source (14) of airfare information through a network (16) and one or more user computers (18). The program collects a lowest airfare currently available (LACA) for a plurality of city pairs by performing a daily search of the source (14). The program also stores the LACA for future retrieval, then referred to as lowest airfare historically available (LAHA). The LAHA may be averaged on a monthly and annual basis, thereby creating monthly averages and an annual average for a preceding twelve months. In use, the program retrieves a LACA between a selected city pair for the current day. Then, the program graphs the monthly and annual averages for the selected city pair and displays the LACA for the current day, thereby allowing a user to compare the LACA for the current day with previously stored LAHA.

The invention provides a water meter energy-saving incentive method and an Internet of Things system based on the composite Internet of Things, and relates to the field of the Internet of Things. Based on the water meter energy-saving incentive method and the Internet of Things system based on the composite Internet of Things, by using each management sub-platform to find the family population information associated with the ID information, and calculate the monthly average water consumption based on the monthly water consumption and family population information, and then based on the ID information Sort the monthly per capita water consumption in the pre-set area in ascending order, and send the sorting results to the service platform; then use the service platform to send them to the user sub-platforms corresponding to the top N monthly per capita water consumption according to the ranking results Incentive information, so that users who save water can get rewards, which can promote users to save water, enhance users' awareness of water conservation, and save energy and protect the environment.

The invention discloses a management system and method for having control over a procurement plan according to monthly average consumption of spare parts. The management system for having control over the procurement plan according to the monthly average consumption of the spare parts comprises an enterprise information system, a data acquisition module, a control rule management module, a spare part procurement plan control module and a log management module, wherein the data acquisition module, the control rule management module, the spare part procurement plan control module and the log management module are connected with the enterprise information system in an information mode. The method for using the management system for having control over the procurement plan according to the monthly average consumption of the spare parts comprises the steps that a management department sets spare part procurement plan control rules in the control rule management module, staff in a production operating region fill in the spare part procurement plan, the spare part procurement plan is stored in the enterprise information system, and the management department analyzes the control conditions and user operation behaviors through procurement plan control logs to achieve continuous optimization of spare part procurement plan control. The management system and method for having control over the procurement plan according to the monthly average consumption of the spare parts achieve automatic control over monthly average consumption of the spare parts and the spare part procurement plan, so that reasonability of the spare part procurement plan is achieved, inventory capital occupied by the spare parts is reduced, and the use ratio of business capital is improved.