70results about How to "Fix build issues" patented technology

The invention relates to a modeling method of a gas compressor capable of achieving graded regulation and control over the angles of adjustable vanes. The modeling method of the gas compressor capable of achieving graded regulation and control over the angles of the adjustable vanes is suitable for the gas compressor with two-grade adjustable vanes, wherein adjustable guide vanes serve as one grade, and adjustable static vanes serve as the other grade. The modeling method of the gas compressor capable of achieving graded regulation and control over the angles of the adjustable vanes comprises the steps that firstly, features of the gas compressor with the angle of the adjustable guide vanes and the angle of the adjustable static vanes controlled respectively are established; secondly, gas compressor model calculation is completed with the established features of the gas compressor. The modeling method of the gas compressor capable of achieving graded regulation and control over the angles of the adjustable vanes achieves the purpose of establishing a model of the gas compressor with the angle of the adjustable guide vanes and the angle of the adjustable static vanes of an inlet controlled respectively, or solves the problem that design and testing need to depend on a control system of an engine model.

The invention provides a knowledge base entity normalizing method, a system, a terminal and a computer readable storage medium. The method comprises the following steps: to obtain an entity set in a knowledge base; pre-partitioning the entity set by using multiple partitioning modes; according to a pre-partitioning result, constructing a sample; according to the pre-partitioning result, constructing features; through at least one normalizing model, performing normalized decision on each entity; and performing set partitioning on a normalized decision result. The system comprises an acquisitionmodule for getting the entity set in the knowledge base; a multi-dimensional partitioning module for pre-partitioning the entity set; a sample constructing module for constructing the sample according to the pre-partitioning result; a feature constructing module for constructing the features according to the pre-partitioning result; a normalized decision module for performing normalized decisionon each entity in the pre-partitioning result; and a set partitioning module for performing set partitioning on the normalized decision result. The method is capable of solving an entity normalizing problem of the large-scale knowledge base.

The invention discloses a soft measuring method of product quality of an industrial fluidized bed gas-phase polyethylene device. The method comprises the following steps: selecting a plurality of key variables influencing product quality to set up a process detection variable set; applying the projection principle of multivariate statistics to establish a soft measuring model between product resin melt index and density and process detection variables; adopting a nonlinear partial least square method of embedded Taylor series approximation (used for carrying out process nonlinear characteristic representation) as core technology; and determining the number of optimal pivot elements through cross check technology. The soft measuring method avoids complex process mechanism analysis and has convenient site implementation and high precision of soft measuring; therefore, the method is particularly suitable for nonlinear industrial occasions with high dimension and abundant progress data similar to the industrial fluidized bed gas-phase polyethylene production device. Moreover, the soft measuring method can be used for real-time monitoring or production guidance to improve product quality, increase output and ensure smooth device operation, thereby bringing greater economic benefits.

The invention relates to oil geophysical prospecting and 3D complex geologic body reconstruction technique: constructing an equipotential field-based initial curve; optimizing cell quality of triangular grid of the initial curve and building a topological relation between grid cells, then converting all the other known information into various fuzzy control restriction information according to the requirements of input model of a disperse smooth interpolation algorithm, additionally, converting all control points into restriction information of fuzzy control points, inputting all restriction information into a discrete smooth interpolator, and then calculating coupling relation of these restrictions and the initial grid curve model, thus eliminating the interactive point offsetting process for curve model construction of a multivalued body , making it convenient to implement the curve model construction of a complex multivalued body and interactive curve editing method is flexible and convenient.

The present invention provides one kind of tongue coating and tongue proper color extracting and classifying method based on pixel, and the method has high accuracy and wide application value. The method includes the first selecting typical tongue picture samples from tongue picture database, performing color clustering on each of the tongue picture samples in FCM algorithm, calibrating the color centers of the results and superposing the calibrated clustering color values of all the color sorts; the subsequent purifying treatment of each color sample set and screening samples to obtain color sample set; and final classifying and analyzing the tongue coating color and tongue proper color on each of the tongue picture with the improved KNN classifier. The present invention realizes the quantitative, objective and standardized analysis on tongue coating and tongue proper color and automatic computerized classification of 14 kinds of tongue coating and tongue proper colors.

The invention provides an electrocardiogram classifying method based on fuzzy inference and weighted similarity measurement and relates to an electrocardiogram classification method. The electrocardiogram classifying method aims to solve the problem that by the adoption of an existing fuzzy inference classification method, due to the fact that an electrocardiogram knowledge base cannot be established, the influence of electrocardiogram knowledge and different combinations of different wave band forms on classification is omitted, and as a result, the error rate of classification is high and to solve the problem that by the adoption of the existing fuzzy inference classification method, due to the facts that attribute concepts are not screened and comparison of membership degrees of the attribute concepts is directly used for classification, the error rate of classification is high. The electrocardiogram classifying method comprises the following steps that, firstly, electrocardiosignals are preprocessed; secondly, feature parameter extraction is conducted on all wave bands; thirdly, a classification feature attribute value vector Yi=[yi1, yi2, yi3, yi4 and yi5] and a to-be-detected feature attribute value vector X=[x1, x2, x4, x4 and x5] are established, and an ECG body ecg.owl is established according to electrocardiogram knowledge; fuzzy concept lattices are established; fuzzy attributes are converted into specific membership degree values, and effective screening is conducted on the specific membership degree values; final classification is conducted through a weighted classification method. The electrocardiogram classifying method is suitable for electrocardiosignal classification.

The present invention provides a virtual power plant day-ahead and real-time bidding model, which is used to solve the problem of establishing a virtual power plant (VPP) bidding model when simultaneously participating in a bilateral contract market, a day-ahead market (DAM), a real-time market (RTM) and a balanced market question. The three-stage bidding process of VPP participating in the electricity market is introduced. And based on this, a VPP three-stage bidding model is established that takes into account electric vehicles (EV) and demand response (DR) while participating in the bilateral contract market, DAM, RTM and balanced market conditions. This model considers the charging of each EV. Discharge management, and the complementarity of price-based DR and incentive-based DR. The VPP day-ahead and real-time bidding model provided by the present invention can well describe the situation that VPP participates in multiple power markets at the same time, taking into account the coordinated management of various distributed energy sources in VPP, and realizes effective control of each EV and DR, thereby reducing the Operating costs of the VPP.

The invention discloses a ligand molecular characteristic screening method and device based on multitask learning for drug design. In drug molecular virtual screening based on ligands, few ligand molecules are discovered for important drug targets, and it is very difficult to establish a virtual screening model. A multitask learning method based on Lasso is utilized to acquire ligand molecular related characteristics through inter-task relevancy via robustness selection. The activity of ligand molecules is generally associated with few sub-structures; key factors that determine interactivity of a body and a ligand are quickly found, the problem with model construction when task sample quantity is low is solved, co-acting factors and independent acting factors are discovered; model robustness is improved; sub-structures associated with ligand activity are obtained, and characteristic screening is effectively performed.

The invention discloses a method for searching a similar watershed based on a spatial dimension division theory. The method comprises the following steps: firstly, dividing a drainage basin into a plurality of orthogonal grid units based on DEM data to obtain an elevation in each grid unit, thereby obtaining an elevation grid Raster_Ele of the drainage basin, and calculating to obtain an elevationfractal dimension value Fra_Ele; secondly, calculating the gradient in each grid unit to obtain a gradient grid Raster_Slope of the drainage basin, and calculating to obtain a gradient fractional dimension value Fra_Slope; next, calculating the slope direction in each grid unit to obtain a slope direction grid Raster_Slope Dir of the drainage basin, and calculating to obtain a slope direction sub-dimension value Fra_Slope Dir; and finally, constructing a multi-dimensional feature space, generalizing a drainage basin into data points, labeling the data points in the multi-dimensional feature space, and classifying the data points, so that the drainage basin divided into one class is regarded as a similar drainage basin.

The invention discloses a method for constructing a biomimetic vascular net in a large-volume tissue engineering tissue organ. Firstly, biological information of a large-volume tissue of a human bodyis collected, and inputted into a computer for high biomimetic modeling; then, material separated printing and material-cell mixed printing output are performed with a hydrogel material and a varietyof amplified cells from the tissue by a high-precision biological 3D printer, wherein a hollow part in blood vessels is printed by a controllable degradable hydrogel; after all the hydrogel materialsare solidified, the controllable degradable hydrogel in the blood vessels are removed by means of specific enzymes or chelating reactions or temperature control or illumination and the like, and the vascular net in the large-volume artificial tissue is constructed. The circulation feeding of the vascular net and gas exchange in the large-volume artificial tissue are achieved by connection of mainblood vessels at two ends of the vascular net and a delivery pipe of a culture solution. The central feeding problem of the large-volume tissue is solved, so as to realize the long-term survival and biological function of the large-volume artificial tissue in vitro.

The invention discloses a multi-base station cooperative transmission strategy in energy efficiency drive, and belongs to the technical field of energy efficiency optimization in wireless networks. The transmission strategy adopts the technical means of coalition formation game; the base station cooperative group problem is modeled as the coalition formation game, a merge-split algorithm is used for enabling the base station to always add in a cooperative cluster capable of promoting self energy efficiency, thereby implementing the optimal network clustering. The network clustering is performed based on the energy efficiency index to optimize the trade-off relation between the throughput promotion and energy consumption increment caused by the network cooperation. The technical means of coalition formation game is used for solving the cooperation cluster construction problem based on the energy efficiency so as to fast converge to an equilibrium point. Through the limitation on the base station and the interference on the cooperation of adjacent regions, and the adoption of the historic clustering data in the merge-split operation process, the purposed coalition formation game can obtain the unique stable solution.

The invention discloses a functional magnetic resonance imaging brain connectivity map construction method based on collaborative clustering. Brain functional connectivity mapping is a key link in brain function and brain disease research. How to construct and validate brain functional connectivity mapping has become the focus and frontier of current brain science research. Recent studies show that there are still some shortcomings in the existing methods of constructing brain functional connectivity maps: the hypothesis-driven method based on model is not robust, the correctness of brain functional connectivity maps based on model independent method is difficult to verify, and the brain functional connectivity maps based on data-driven method are not precise enough. In order to overcome the shortcomings of the prior art, the present invention provides a novel and easy-to-verify method, which simultaneously identifies a functional sub-region of a specific brain structure and its connecting brain region by adopting a cooperative clustering algorithm, thereby realizing the construction of a refined brain functional connection map; at the same time, three approaches from different angles are adopted to verify the correctness of the brain functional connectivity map.

The invention discloses a method for determining the influence of vacuum plume on equipment with any configuration, which decouples vacuum plume field calculation and impact calculation of flow on thesurface of the equipment, and comprises the following steps of: firstly, obtaining flow field parameters of an undisturbed state near the wall surface of the equipment; secondly, constructing an equipment surface grid, and obtaining a grid center point flow parameter by adopting an interpolation method; and finally, by correcting the Newton theory and selecting a gas and equipment surface actionmodel suitable for equipment wall surface conditions, obtaining impact pressure intensity, heat flux density and mass flow density distribution of plume acting on equipment wall surface grid points. According to the method, the problems that plume analysis modeling of the vacuum thruster of the complex configuration equipment is difficult and much time is consumed for calculation are solved, plumeinfluence evaluation of the complex configuration equipment can be rapidly carried out, and a design basis is provided for equipment position adjustment and thermal protection design.

The invention discloses a robot system used for wall face environment perception. The robot system is composed of a wall climbing robot and a remote environment map information management platform. The wall climbing robot comprises a robot body, a power unit, a wall face information collection unit and a communication unit. The remote environment map information management platform comprises a data processing computer and management platform software. The power unit comprises a servo motor, a servo driver and a transmission structure. The wall face information collection unit comprises a visual sensor, a laser sensor, a wall face roughness sensor, a humidity sensor and a wall face inclination sensor. The communication unit comprises a 4G communication module, a WIFI communication module, avideo transmission module and a handheld remote controller. By means of the robot system, wall face environment information is collected, analyzed and processed, a wall face environment information map is generated, and therefore global environment information is provided for autonomous work of the wall climbing robot, people can conveniently conduct accurate work tasks remotely or the robot canconveniently conduct the accurate work tasks autonomously, and the application range is very wide.

The invention discloses an abrasive band grinding process simulation method. The method comprises the steps that an abrasive band contact wheel and workpiece simulation model is built; the simulationmodel is subjected to grid division; and part of abrasive particle units are deleted, and a multi-abrasive-particle random distribution model is generated. According to the abrasive band grinding process simulation method, the purpose of building the abrasive band grinding simplification model featuring multi-abrasive-particle random distribution is achieved creatively, accordingly, the problem that an existing grinding simulation method is insufficient in analysis precision can be relieved, and the abrasive band grinding machining process under a multi-abrasive-particle comprehensive effect can be accurately simulated.

The invention discloses a road smoothness predicting method based on a minimum variable coefficient assessment and inference model. According to the method, sample analysis and digging of vehicle-mounted GPS historical data are carried out, a variable coefficient assessment method and a technique for building a road traffic flow characteristic interference model in a sampling cycle are adopted, and road short-time smoothness and future smoothness trends are inferred through floating vehicle data analysis. According to the method, typical sample analysis based on a GPS is adopted, and a statistic cycle is obtained by means of a parameter optimization technique of a road smoothness analysis model, so that the method is supported by a strict mathematical model and has wide adaptability; road situation property types and corresponding rule base relations are quickly obtained by building the road traffic flow characteristic model, road smoothness trend prediction capacity is obtained based on knowledge inference, and statistic efficiency and the service level are greatly improved.

The invention provides a method and a device for establishing a power communication network model, wherein the method and the device relate to the technical field of a power communication system. The method comprises the steps of acquiring data of a network model structure and service distribution condition of the to-be-processed power communication network; determining a link capacity matrix and a service connection matrix, and determining a network service flow matrix according to the link capacity matrix and the service connection matrix; determining a service flow parameter of each power communication network node in each service type according to the link capacity matrix, the service connection matrix and the network service flow matrix; determining the determined value of importance of each power communication network node according to the service importance of each service type and the each service flow parameter; and correspondingly arranging each determined value of importance and each power communication network node in the network model structure of the to-be-processed power communication network, thereby forming the power communication network model in which each power communication network node has the determined value of importance.

The invention discloses a static positioning restoration method for on-board equipment after being powered on. The method comprises the following steps: when the respective on-board equipment at bothends of a train is started, trying to obtain respective corresponding sleep and wake-up beacons; when the on-board equipment at both ends of the train reads the corresponding sleep and wake-up beacons, the number of the sleep and wake-up beacons acquired by the other party is mutually checked, and when the numbers are paired with each other, the on-board equipment establishes the positioning of the train with the acquired sleep and wake-up beacons. The invention also discloses a static positioning restoration system for the on-board equipment after being powered on. The static positioning restoration method and system for the on-board equipment after being powered on solve the problem of no positioning in the next morning after the on-board signal equipment is powered off when the train stops at night at the sleep and wake-up points.

The invention relates to a variance optimization histogram construction method and device based on Spark Streaming. The method comprises the steps that Spark Streaming is utilized to perform online sampling on streaming data; a variance optimization histogram is dynamically constructed according to online sampling data; and the variance optimization histogram is dynamically updated by use of newly added data, and the variance optimization histogram is dynamically constructed again according to the newly added data. Through the technical scheme, the high-precision approximate variance optimization histogram can be constructed by scanning data once within a limited memory space.

The invention relates to a process for preparing a heat-conducting polymer material by utilizing SLS to form a porous ceramic heat-conducting network, the method comprises the following steps: blending ceramic powder and powder; introducing the structure of a designed integrated filler into software, setting the technological parameters of the SLS, and printing and forming mixed powder; spraying an epoxy chloropropane solution on the obtained porous ceramic heat-conducting network and drying; placing the dried porous ceramic heat-conducting network in a muffle furnace, heating, and naturally cooling; filling the cooled porous ceramic heat conduction network into a thermosetting resin matrix, and using a prepreg-vacuum curing process to prepare the heat-conducting polymer material. The process for preparing the heat-conducting polymer material by utilizing the SLS to form the porous ceramic heat-conducting network is simple in process and high in flexibility, and the prepared heat-conducting polymer material has extremely high heat conductivity and ultrahigh strength, simultaneously has good toughness and rigidity, and has wide application prospect.

Aiming at the problem that the requirement of people for mining and recommending content associated websites cannot be met in the prior art, the invention provides a method for mining approximate websites and recommending the similar websites to users by learning example websites. The method comprises the following steps of: learning the example websites, mining other websites associated with thecontents of the example websites according to the theme contents of the websites, and recommending the other websites to the users. Website theme information is learned through the example websites, the example website system intelligently explores new websites associated with the theme contents of the example websites and recommends the new websites to the users, so the information level concerned or browsed by the users is broadened, the users can acquire other information associated with the browsed information more conveniently and quickly, information search time is saved, and informationsearch efficiency is improved. The method has a good promotion effect on information acquisition of the users, has the advantages of high interaction performance, high intelligent degree, high expandability, high recommendation speed, high mining precision and the like, and has huge utilization value and market application space.

The invention belongs to the technical field of reliability statistics. The invention discloses a reliability confidence lower limit construction method based on the Bayesian theory and linear fitting, and the method comprises the steps: calculating the confidence upper limit of the failure probability of each sample product life test data according to the Bayesian theory for each given sample product life test data, namely the failure time of each sample product; converting the Weibull distribution function into a linear function; and finally, constructing a confidence lower limit curve of the Weibull distribution reliability based on linear fitting. Through the steps, the construction problem of the lower confidence limit of the Weibull reliability is well solved. In each step of the method, a determination form of a corresponding mathematical expression is given, and the whole process is convenient to calculate, so that the method is very suitable for application in engineering practice.

The invention discloses a flow injection luminescent detection device, which comprises a base, a reference electrode, an auxiliary electrode and a working electrode. A detection cavity with an opening at the bottom is arranged inside the base, and the reference electrode and the auxiliary electrode are arranged along the base. Axially arranged in the base, one end of the reference electrode and the auxiliary electrode is suspended in the detection cavity, the other end of the reference electrode and the auxiliary electrode protrudes from the upper end surface of the base, and the working electrode is formed by Made of transparent material, the working electrode is fixed on the bottom wall of the base and is in contact with the detection chamber, the working electrode seals the bottom of the detection chamber, and two through holes are opened radially on the peripheral wall of the base, the The through hole communicates with the detection chamber. The invention solves the problem of constructing the bionano sensing interface in the flow injection chemiluminescence / electrochemiluminescence system, and realizes the highly selective and sensitive detection of biomolecules in the automatic flow injection chemiluminescence / electrochemiluminescence system.

The invention discloses a power transmission line defect risk modeling and prediction method based on a support vector machine, and the method comprises the steps: firstly enabling a power transmission line to be subdivided into a plurality of parts, and defining a defect risk value as an evaluation index of a line defect condition under the condition of considering the number of defects and the severity degree of the defects; secondly, screening out important factors influencing the defect risk value of each part through correlation coefficients, introducing a support vector machine machine learning method, and predicting the future defect risk value of the line by utilizing the advantage that the small sample learning problem can be effectively solved. The size of the defect risk prediction value reflects the defect condition of the power transmission line in the future, and an important reference can be provided for the work of related departments.

The invention discloses a method for preparing Eliglustat. The Eliglustat is an effective specific glucosylceramide systhase inhibitor, which can be used for treating type-I Gaucher disease. The invention provides the synthetic method of Eliglustat, which comprises the following steps: 1,4-benzdioxan-6-formaldehyde and a chiral ligand are subjected to an adiastereoselectivity Aldol reaction, and then subjected to a reduction reaction, replacement and a Staudinger reaction, and an amidation reaction to obtain Eliglustat. The method has the advantages of easy acquisition of raw material, simpleoperation, high product yield and purity, and easy industrial large production.

The invention discloses an industrial control system state mechanism construction method. The method starts from a clustering algorithm, adopts the most advanced BLOCK-DBSCAN algorithm, and improves both the speed and the accuracy. Moreover, a self-adaptive method for the clustering algorithm parameters of the DBSCAN is provided, the optimal matching parameters can be effectively and accurately found for the industrial control system, and the efficiency is greatly improved. Then a reward and penalty mechanism is utilized to re-classify clustering results, so that the problem that high-dimensional protocol information cannot be fully separated by a clustering algorithm is solved. Finally, the construction of the industrial control system state machine is achieved through the construction of the APTA tree, and the difficulty of the construction of the state machine is solved. According to the industrial control system state machine construction method, the construction problem of the industrial control system protocol state machine is solved, and a solid foundation is provided for intrusion detection of the industrial control system in the future.

The invention provides a method and system for constructing a semantic knowledge base in an environmental impact evaluation field, and the method comprises the steps: constructing a professional term knowledge base and a non-professional term knowledge base corresponding to an industry category according to the business demands and industry expert knowledge for each industry category, and for each non-professional term keyword in the non-professional term knowledge base, establishing a fuzzy extraction rule through a regular expression; constructing a quaternary relationship among industry categories, terminologies, rules and keywords, and generating a keyword-rule lexicon according to the quaternary relationship; selecting corresponding professional terms from the keyword-rule lexicon according to the industry category of a target environmental assessment file, and locating a target chapter of the target environmental assessment file and a table and text content corresponding to the target chapter; and extracting target chapters and keywords in forms and text contents corresponding to the target chapters according to rules in the keyword-rule lexicon, scoring the extraction result, and evaluating the normalization of the target environmental assessment file according to the scoring result.

The invention discloses a method, a device and apparatus for constructing a file system and a computer storage medium. The method comprises the following steps: acquiring demand data of a target file system; based on the demand data of the target file system, constructing a general file system on the embedded program development system; based on the general file system, combining the type of the target file system to construct the target file system; the construction problem of different types of target file systems in an integrated platform is solved, the integration of an embedded program development platform and a file system construction platform is realized, the development and deployment of service programs are accelerated, meanwhile, the production of different types of target file systems is completed, the expandability and reusability of the file system are improved. Therefore, the working efficiency of embedded system developers is improved, and the program development cycle is shortened.