39results about How to "Help formulate" patented technology

The invention discloses a projection pursuit-based method for evaluating flooding risk of a drainage pipe network, which relates to the technical field of system comprehensive evaluation. The method integrates multi-aspect flooding risk effect factors from a drainage pipe network model, a geographic information system and a database system and uses a projection pursuit evaluation method for evaluating the flooding risk of the drainage pipe network. In the method, linear projection is conducted on each evaluation indicator sample; an optimal projection direction vector is searched in accordancewith a certain principle and the optimal projection direction vector reflects the important level of each evaluation indicator, namely objective weight, and based on the objective weight, a comprehensive evaluation number is established for conducting evaluation grading on the flooding risk of the drainage pipe network, thus providing technical support for emergency rescue in flood season. The method avoids one-sidedness of human analysis in evaluation process, has more scientific evaluation result, and can vividly and directly represent disaster risk degree and distribution due to an obtained flooding disaster risk map, thus providing excellent decision platform for rescue dispose.

A per capital air conditioner energy consumption calculating method in a public building relates to the energy-saving technical field and aims to solve the technical problem of improving the calculating accuracy. The method is that an air conditioner load curve, an indoor temperature curve, an outdoor temperature curve and a curve of the number of people in the building of one day in the previous year in the public building are firstly acquired; secondly, all continuous curve sections that meet 5 conditions are found out on the indoor temperature curve in the day of the previous year; thirdly, the per capital air conditioner energy consumption in per unit of time of each curve section is calculated; and finally, the average valve of the air conditioner per capital energy consumption in per unit of time of all the curve sections is used as the per capital air conditioner energy consumption in per unit of time in the building. Thus, the method provided herein is suitable for air conditioner systems in office buildings.

The invention discloses an anisotropic rotor holographic dynamic balancing method based on equivalent initial phase vector. According to the method, the holographic spectrum principle is taken as the basis, vibration data in two directions are taken into account and are subjected to data fusion, so the anisotropic characteristic can be completely formulated, and the balance fault diagnosis is facilitated; furthermore, the rule of angular momentum conservation is utilized, a holographic spectrum ellipse is converted into an equivalent rotating frequency circle, the equivalent initial phase vector is taken as the characteristic for unbalanced vibration, and the requirement on fine balance is met. Through the equivalent initial phase vector, the defects of traditional initial phase vector on describing the amplitude of unbalance and phase position caused by anisotropy can be eliminated, the unbalance characteristic can be accurately characterized, and the spatial dynamic property of a rotor can be truly indicated. Therefore, the anisotropic rotor holographic dynamic balancing method based on the equivalent initial phase vector, provided by the invention, facilitates improving the accuracy and efficiency of on-site dynamic balance, so that the operating precision and service life of a rotary machine can be effectively improved and prolonged.

An air conditioner cooling quantity dissipation calculation method in an office building relates to the energy-saving technical field and aims to solve the technical problem of improving the calculation accuracy. The method is that an air conditioner load curve, an indoor temperature curve and an outdoor temperature curve of one day in the previous year in an office building are firstly acquired; secondly, all continuous curve sections that meet 5 conditions are found out on the indoor temperature curve in the day of the previous year; thirdly, the cooling quantity dissipation rate of the air condition in per unit of time of each curve section is calculated; and finally, the average valve of the cooling quantity dissipation rate of the air conditioner in per unit of time of all the curve sections is used as the cooling quantity dissipation rate of the air conditioner in per unit of time in the office building. Thus, the method provided herein is suitable for air conditioner systems in office buildings.

The invention provides an urban education service facility evaluation optimization method. The method comprises the steps of extracting and integrating basic data and traffic big data of geographicalnational condition elements, calculating and determining a basic evaluation index system of urban education service facilities, performing service capability analysis, accessibility analysis and education equalization analysis, and quantitatively measuring the supply degree of the education facilities in multiple dimensions. Based on the traffic big data, according to the distribution condition ofschools and communities in a city, identifying blind areas of education service facilities; comprehensively evaluating the reasonability of the school zoning by utilizing the consistency index, the school space dominance index, the service blind area, the school district service scale, the service population quantity and the characteristic population quantity; and optimally configuring schools towhich the planning unit belongs according to a majority principle based on the blind area and the traffic big data and the conditions of schools to which all the communities belong in the planning unit. According to the invention, the current situation of urban education service configuration can be automatically evaluated and predicted, and an optimal configuration scheme is provided.

The invention relates to the technical field of electric power system management, in particular to an electric power larceny accurate identification method based on big data and an electric power larceny prevention system. Comprising the following steps: constructing an electricity management and control mechanism; based on video monitoring and AI identification technology, the electricity stealing behavior is identified and evidence is obtained; gPS positioning of an electricity stealing position is carried out; electricity utilization data are intelligently collected; electricity consumption analysis control is performed by constructing an electricity larceny and electricity larceny prevention diagnosis model; on-line analysis, research and judgment and intelligent early warning are carried out on the electricity stealing behavior; establishing an electricity stealing user behavior feature library; and establishing an electricity safety big data analysis library. According to the design of the invention, intelligent acquisition of power consumption data can be realized, and the accuracy of studying, judging and positioning of electricity stealing behaviors is improved; based on mass data, a state estimation method and a detection method are used, the scientificity and reliability of research and judgment are improved, the detection accuracy is high, and the application cost is low; the efficiency of power utilization inspection and inspection is improved; the whole-process and panoramic management and control of electricity utilization inspection can be realized; and later evidence obtaining is facilitated.

The invention belongs to the technical field of environmental pollutant prevention and control, and particularly relates to a method for diagnosing the concentration level of environmental medium pollutants. The method comprises the following steps: S1, determining an environmental medium; S2, selecting pollutants to be diagnosed; S3, analyzing and diagnosing the concentration of pollutants in theenvironmental medium; S4, concluding: analyzing and summarizing the result of the concentration level of the pollutants in the environmental medium. S3 specifically comprises the following operations: S3.1, setting a data acquisition range; S3.2, determining a data acquisition rule; S3.3, sorting, merging and calculating data; S3.4, sampling data; S3.5 performing pollution level evaluation. According to the method, data with the same investigation range and the same investigation purpose are summarized, the investigation frequency and the number of investigation samples are indirectly increased, sampling errors caused by the small number of investigation samples are avoided, the accuracy of environmental pollution concentration level analysis is improved, and a manager can make a pollution prevention and control strategy easily.

The embodiment of the invention provides a delay duration prediction method and device. According to the invention, the delay duration of the target flight can be predicted; wherein the delay durationof the target flight is predicted by combining delay parameters of multiple dimensions of the target flight; wherein the delay parameters at least comprise weather parameters of the target flight ata predetermined takeoff moment, air traffic control parameters of the target flight, delay duration of a previous flight of the target flight, minimum station passing duration of the target flight, mechanical fault parameters of the target flight and the like; the delay duration of the target flight is predicted by combining a plurality of types of delay parameters and the target prediction model.Therefore, the accuracy of the predicted delay duration is high, flight scheduling, maintenance ground service scheduling and emergency plan making of airlines are facilitated, and the method has important practical significance for improving the service quality of the airlines and improving the competitiveness of the airlines.

The invention discloses an intelligent health examination diagnostic apparatus and belongs to the field of medical diagnostic equipment. The intelligent health examination diagnostic apparatus comprises an information data detecting and collecting system, a data processing system, a transmission system and a palmtop computer. The intelligent health examination diagnostic apparatus is characterized in that the information data detecting and collecting system is composed of a high-definition camera, an infrared detecting device, a blood oxygen detector, a sound image collecting and converting device, an ultrasound generating, accepting and converting device, an electrocardio remote sensing and accepting device and a blood pressure detecting gauge. The in-vivo and in-vitro states are detected through camera shooting/photographing, sounds, sound waves and electrocardio sensing accepting, and the detection information is transmitted to a computer software system of the data processing system through the transmission system to be processed or directly referenced by a doctor or directly transmitted to an electronic medical record platform of the palmtop computer. The intelligent health examination diagnostic apparatus has the advantages of being light, simple, practical, easy and convenient to operate, accurate in diagnosis, standard, efficient and the like.

The invention discloses oligonucleotides, a method and a kit for detecting a BAALC gene in a sample, upstream and downstream primers and a probe for BAALC are included, and upstream and downstream primers and a probe for an ABL internal reference gene are also included. The method can quickly detect whether the BAALC gene exists in the sample and the expression amount of the BAALC gene. The detection result is accurate and sensitive, and an individualized treatment scheme and disease prognosis judgment can be used for treating human acute myeloid leukemia (AML).

The invention discloses an output quantity and input quantity recording method, a system, a device and a storage medium. The output quantity and input quantity recording method comprises the followingsteps: performing image recognition processing on a first image and a second image, recognizing types and quantities of excrement and food, determining water contents of the food and the excrement, determining the output quantity and input quantity, and the like. According to the invention, an intelligent terminal is used for recording the output quantity and input quantity of a patient, so thatthe situations of excessive recording, missing recording, disordered recording and the like can be effectively avoided, medical data can be systematically managed by institutions such as hospitals andthe like conveniently, and medical measures for the patient can be formulated. The method is executed through a computer system, part of work of hospital staff in the prior art can be replaced, the workload of medical staff is reduced, and the high error rate caused by much manual participation is avoided. The method provided by the embodiment of the invention can be executed through terminals such as a mobile phone, so that the implementation cost of the output quantity and input quantity recording method provided by the embodiment of the invention is lower. The method is widely applied to the technical field of intelligent terminals.

The invention relates to an epidemic disease propagation network reconstruction method and system based on node similarity, and belongs to the field of epidemic disease data reconstruction analysis. The method comprises the following steps: firstly, integrating a flow regulation report to preliminarily establish a local epidemic disease propagation network, then defining node similarity indexes of three types of epidemic disease propagation networks based on a network structure and node attributes, then adding possible missing edges to the local epidemic propagation network by calculating similarity indexes of node pairs to reconstruct the epidemic propagation network, and finally, comparing the network reconstruction accuracy under different indexes. The problems that in existing epidemic disease analysis, a propagation chain is difficult to mine, propagation characteristics are difficult to analyze accurately, and the utilization rate of a large number of flow regulation reports is low are solved, the epidemic disease propagation network capable of truly reflecting a virus propagation path is constructed, the epidemic disease propagation chain can be effectively mined based on the constructed epidemic disease propagation network, the virus propagation speed is analyzed, and the space-time propagation range of the virus is predicted.

The invention discloses a method for predicting the total energy consumption on the basis of a fixed base energy consumption elasticity coefficient. According to the method, the research limitation caused by fluctuations and incomparability of traditional energy consumption elasticity coefficients is overcome, the fixed base energy consumption elasticity coefficient is adopted, the relation between the fixed base energy elasticity coefficient and an industrial structure is considered, a prediction model for the fixed base energy consumption elasticity coefficient is built, and then the total energy consumption in the future years can be predicted. The method comprises the steps of obtaining GDP, CPI and total energy consumption data of historical years, defining the fixed base energy consumption elasticity coefficient, and calculating the fixed base energy consumption elasticity coefficient value and the tertiary industrial added value proportion of the historical years; building the prediction model of the fixed base energy consumption elasticity coefficient; calculating the total energy consumption of a predictive period. According to the method, the fixed base energy consumption elasticity coefficient is predicted, then the total energy consumption in the future years is predicted, medium and long energy planning is facilitated, and the energy-saving policy is reasonably formulated.

The invention discloses an Alzheimer's disease pre-diagnosis method based on a 3D convolutional neural network. The method comprises the following steps: S1, selecting a data set: selecting MRI and DTI image data through adopting an ADNI database; S2, performing data preprocessing: preprocessing the selected MRI and DTI image data; S3, adopting a DL method based on the CNN comprising the specific steps: performing 3D convolution; adopting a batch regularization technology, and adopting a linear rectification function as an activation function; and performing 3D pooling; S4, establishing a network system structure; and S5, realizing performance evaluation, adding DTI data to improve diagnosis accuracy, and acquiring the DTI image data by scanning the same parameter from the same system as an MRI image. Therefore, the method also has the characteristics of low cost, no trauma and easiness in obtaining, and is easy to popularize in clinical application.

The invention provides a method for testing creditability of a chronic disease multi-gene risk evaluating product. The method comprises the following steps of S1, determining whether the chronic disease multi-gene risk evaluating product satisfies the following conditions, 1), whether a multi-gene risk evaluating predicated value is consistent with an actual predicting risk value; and S2, obtaining a testing result, if the chronic disease multi-gene risk evaluating product satisfies all conditions in the step S1, determining high credibility of the chronic disease multi-gene risk evaluating product. The method according to the invention has advantages of quantification, high objectiveness, and high strictness.

The invention provides a power load prediction method and device, electronic equipment and a storage medium, and relates to the technical field of micro-grid management, and the method comprises the steps: obtaining the user feature information of a first user in a micro-grid, the power load of the first user at a current date, and the environment information of the first user, wherein the environment information comprises a geographic position, climate information and/or a date type of a current date; and taking the user feature information of the first user, the power consumption load of thefirst user on the current date and the environment information of the first user as a trained power load prediction model to obtain a predicted power consumption load of a specified day output by thepower load prediction model. The problems that in the prior art, the load law is difficult to grasp, and prediction is inaccurate and easy can be solved, and the safety and stability of a microgrid system can be improved.

The invention provides a method for performing quantitative evaluation on a device operation mode. The method comprises the steps of collecting historical operation data which comprise device defect data and production plan data; according to the device defect data and the production plan data, generating an operation work effectiveness basic score and an operation work adjusting coefficient, andobtaining a percentage value of the operation work effectiveness through multiplying the operation work effectiveness basic score by the operation work adjusting coefficient; analyzing production operation plan data, generating operation work manpower cost and an operation work cost adjusting coefficient, and obtaining a total cost number of the operation work through multiplying the manpower costby the operation work cost adjusting coefficient; and obtaining a benefit quantification result of the particular operation work mode of an individual device through dividing the percentage value ofthe operation work effectiveness by the total cost number of the operation work and multiplying by an individual device age coefficient. The method according to the invention can be used for visuallycalculating the effectiveness of the operation work.

The invention relates to the technical field of safety engineering and information, and provides an accident reconstruction system and method for a chemical device. The system comprises a data acquisition module used for acquiring process data, accident data, disaster field data and emergency disposal data of a chemical engineering device; a modeling module used for constructing a risk device model of the chemical engineering device based on the process data, the accident data and the disaster field data, constructing an emergency disposal model for simulating an emergency disposal process aiming at the accident phenomenon based on the emergency disposal data, and constructing a three-dimensional scene of the chemical engineering device, so that all the constructed models can be simulated in a three-dimensional scene; and an evaluation module used for obtaining a simulation result of reproducing the accident analysis conclusion to be verified through each model, and evaluating the accident analysis conclusion to be verified. The accident development process and the emergency disposal process are accurately reproduced by using the simulation model, so that the accident analysis conclusion is verified.

The invention belongs to the field of gene engineering, and particularly relates to an application of NDUFA4L2 in preparation of medicines for reversing breast cancer herceptin resistance. By constructing a breast cancer stable cell strain resistant to herceptin, NDUFA4L2 can play a role in reversing the drug resistance of HER-2 positive breast cancer cells to herceptin at the cellular level. According to the invention, firstly, whole genome analysis is carried out on herceptin sensitive or drug-resistant cells, 487 probes are adopted in total, FDR correction is carried out, 453 differentially expressed genes are found, NDUFA4L2 is the gene with the most significant difference, and the sensitivity to herceptin is regulated and controlled through energy metabolism and oxidative stress level of NDUFA4L2. When being applied clinically, the herceptin gene can contribute to formulation of a treatment scheme of a clinician, prognosis judgment and become a target for research and development of related drugs in the future, the curative effect of herceptin is improved, and the herceptin has a good clinical popularization value.

The invention provides an intersection traffic state identification method based on a PSO-ELM algorithm. The method comprises the following steps: acquiring a historical traffic flow data set of a labeled intersection connection road section; learning the historical traffic flow data set by using an extreme learning machine (ELM) algorithm, optimizing parameters of the ELM by using a particle swarm optimization (PSO) algorithm, setting a fitness function of the PSO as a mean square error (MSE) of an ELM predicted value and an actual value, taking a parameter at the optimal fitness value as a final parameter of the ELM, and taking a final ELM model as an intersection traffic state recognition model; and identifying the traffic state of the intersection to be identified by using the intersection traffic state identification model. According to the method, the PSO-ELM algorithm is applied to the field of traffic state recognition, and the traffic state of the intersection is recognized by using the traffic state of the intersection connecting road, so that the formulation of traffic control measures of the intersection connecting road is facilitated.