36 results about "Analytical problem" patented technology

The invention discloses an Android malicious application detection method and system based on multi-feature fusion. The method comprises the following steps that: carrying out decompilation on an Android application sample to obtain a decompilation file; extracting static features from the decompilation file; operating the Android application sample in an Android simulator to extract dynamic features; carrying out feature mapping on the static features and the dynamic features by the text Hash mapping part of a locality sensitive Hash algorithm, mapping to a low-dimensional feature space to obtain a fused feature vector; and on the basis of the fused feature vector, utilizing a machine learning classification algorithm to train to obtain a classifier, and utilizing the classifier to carry out classification detection. By use of the method, the high-dimensional feature analysis problem of a malicious code rare sample family can be solved, and detection accuracy is improved.

The invention relates to a pneumatic elastic analytical method, and provides a pneumatic elastic mechanical characteristic analytical method of a hypersonic speed aircraft in thermal environment. According to the method, the piston theory is used for carrying out frequency domain nonsteady aerodynamic calculation on a full-aircraft finite element model of the hypersonic speed aircraft; on the basis, the pneumatic thermal effect on the model in the hypersonic speed thermal environment is considered; the weak coupling effect of pneumatic thermal input in aerodynamic input and elastic force input is ignored; only the structure temperature steady-state characteristics under the pneumatic thermal load effect are considered; after the steady aerodynamic calculation, the thermal flux density on the surface of the aircraft is obtained by adopting a reference enthalpy method; further, the steady temperature distribution on the surface of the aircraft is calculated; the practical equivalent rigidity matrix of the structure at the moment is obtained; and the critical flutter speed is calculated by an engineering method. The pneumatic elastic mechanical characteristic analytical method has the advantages that the pneumatic elastic analytical problem of the hypersonic speed aircraft in the pneumatic thermal environment is solved, and the pneumatic elastic performance of the hypersonic speed aircraft is improved through flutter speed analysis.

The invention discloses a method for multiscale calculation of equivalent stiffness matrixes of complex composite material structures. The method comprises the following steps of: separating a macro-meso-micro three-scale structure by adoption of a scale separation method, and respectively establishing each scale analysis model according to geometric features of different scale models; and converting a three-scale problem into two multiscale problems: a macro-meso multiscale problem and a meso-micro multiscale problem, analyzing the two multiscale problems in sequence, and finally returning an equivalent modulus obtained by a micro multiscale problem to a macro multiscale problem. According to the method, the disadvantages such as low calculation efficiency and bad precision of the traditional structure analysis are overcome and the efficiency and precision of predicting performance of composite material structures are effectively enhanced; and the method can be used for instructing the work such as production, research and development of composite materials. The method can be applied to design and analysis of complex composite material structures in the field of aerospace, and can be applied to thermal and mechanical analysis problems of structure design in the engineering field of other composite materials.

The invention provides an ionized layer incoherent scattering radar simulation system, which is characterized in that a modular design idea is adopted, the system is divided into a signal simulation module, an incoherent scattering spectrum simulation module, an ionized layer parameter analysis module, a radar power simulation module and an antenna array simulation module according to a radar actual system structure and functions of each extension set, module functions are basically the same as completing functions of each system extension set, transmission and sharing of data and information among the modules can be realized, and dynamic demonstration is carried out by using an MATLAB graphical user interface function. The ionized layer incoherent scattering radar simulation system well solves a problem that the incoherent scattering radar is small in number of research platform and difficult in test, and can help the technicists to improve abilities of analyzing and solving problems and an ability of carrying out radar equipment technical research.

The invention provides a method for evaluating vacuum plume effect on basis of mutual coupling of experiment and simulation and aims to quickly and accurately evaluating the vacuum plume effect in rocket engines. The method includes: performing simulation aided experimental design, to be specific, performing initial simulation to determine typical experimental conditions and key measurement parameters; confirming experimental effectiveness, to be specific, comparing experimental data of an experimental process with initial simulation results, and judging the effectiveness; confirming method effectiveness, to be specific, after confirming experimental effectiveness, subjecting a simulation method to verification and correction to allow sufficient precision; computing popularization of the simulation method, to be specific, subjecting all conditions of a plume effect task to be analyzed to simulation computation by the simulation method verified. The method has the advantages that various specific analytical problems about the engine vacuum plume effect can be studied and evaluated quickly, efficiently and accurately, reasonableness of experimental design can be effectively guaranteed, fewer experiment times are required, and experiment cost is lowered.

An intelligent data processing method includes following steps: collecting and storing operation data of product operation equipment, and analyzing and classifying; finding and providing a product solution according to the operation data after being analyzed and classified; according to the product solution, modifying a product or displaying content of the solution. The invention further providesan intelligent data processing system. A lot of time and manpower are not needed to analyze and solve problems, and the system intelligently analyzes problems from massive data and is combined with anartificial intelligence system to constantly improve solution screening ability and select an optimal solution to finally solve the problems, so that a problem solving system is formed; once restoration fails, related personnel is notified timely for solution, so that the system can constantly improve screening programs and improve problem solving level.

The invention discloses a three-dimensional slope safety factor solving method based on lower bound limit analysis. According to the method, the magnitude, direction and action point of block body interface acting force serve as main variables, static balance (meeting force and torque balance at the same time) and yield criteria required by the lower bound limit analysis for permitting a static field serve as constraint conditions, and the slope stability analysis problem is converted into a nonlinear optimization problem for solving the maximum safety coefficient value; meanwhile, the accuracy and reliability of the calculation result of the method disclosed by the invention are verified through a representative example, and satisfactory results are obtained. The invention provides a newmeans for the three-dimensional stability analysis of the actual slope engineering.

A substation operation risk evaluation method based on a graph theory comprises the following concrete steps: carrying out data input and constructing an input data module for substation operation risk evaluation; using an element outage model module to calculate the outage probability of substation elements; using a Monte Carlo module to simulate the randomness for the substation elements to exit operation so as to form a substation system state; identifying connectivity of the system state of the substation by a graph theory method and judging whether a load point is communicated with a power supply point; and evaluating a substation operation risk and calculating a corresponding substation operation risk index. According to the substation operation risk evaluation method of the invention, consideration is given to the randomness of substation events, the system state of the substation is extracted by a Monte Carlo method, the method of identifying the connectivity through the use of the graph theory is proposed, substation main wiring risk evaluation is converted into a problem of identification of connectivity between the load point and the power supply point inside the substation, the complexity of problem analysis is simplified, and the purpose of substation operation risk evaluation is achieved.

The present application provides an insurance problem processing method, comprising: generating a prototype problem based on an insurance problem reported; according to the preset classification rules, the embryonic problem is classified and processed to obtain the item problem; according to the preset classification rules, the project problems are classified into grades; according to the preset assignment rules, different levels of project problems are assigned to the corresponding level of case personnel to deal with. Take this method, by classifying and ranking the insurance problems reported, automatically assign project issues to individual cases for processing, from business escalation issues to development process management and control of the issues, will escalate issues, record issues, analysis issues through standardized rules and achieve the interface of each link, to achieve the purpose of automatic distribution and processing of the entire process.

The invention discloses a nonlinear system state deviation evolution method based on differential algebra and Gaussian sum. The method includes forecasting the terminal state of a nonlinear system according to a differential algebra method, and representing it as a high-order Taylor expansion polynomial related to original-state deviation; determining a sub Gaussian distribution covariance matrix, and fitting a Gaussian sum model for each sub Gaussian distribution through shooting; calculating the high-order central moment of the sub Gaussian distributions; determining the mean value and the covariance matrix of each sub Gaussian distribution at the terminal moment, and providing a terminal-state deviation distribution probability density function in the form of the Gaussian sum. The method can be extended to any designated-order deviation evolution accuracy automatically, manual derivation of high-order partial derivatives of kinetic equations is not needed, the method is applicable to long-term forecasted nonlinear system deviation evolution analysis problems with high nonlinearity, the remarkable efficiency advantages of the method can be still maintained as compared to the Monte Carlo simulation method while deviation distribution and non-Gaussianity thereof are described accurately, and accordingly, the method has the advantages of convenience in use and high calculation accuracy.

The invention discloses a problem data full-life-cycle data quality management method and system. After a unique fingerprint code is established based on problem data, a problem data fingerprint database is established, and full-life-cycle supervision and monitoring of problem data are realized; and lean management of problem data is effectively improved; problem data full-flow closed-loop controlcan be realized, and multi-dimensional angle analysis statistics of the problem data can be realized. The data quality lean management of the problem data in the full life cycle is improved, the renewal time, stock and increment problem data change conditions of the problem data and the type and rule of the problem data can be analyzed, the data quality management and control capacity of an information center is enhanced through multi-dimensional analysis of indexes and the problem data, and data management is persuasive, visible and manageable.

The invention provides an on-line bidding probability model generation method, historical victorious request records are divided into a plurality of intervals according to predicted KPIs, mixed beta distribution is adopted to perform fitting for each interval, a function of KPIs of each interval and victorious price is fitted, a model is corrected, finally a probability model is obtained, simulation of on-line bidding can be performed through the probability model, thus analyzable problems can be discovered, optimal business configuration can be explored, and a bidding strategy of a competitor can be analyzed and simulated.

The invention discloses a gait cycle detection method through layering and coding for depth information. According to the method, depth sequence information is transformed into depth features of single frames to analyze problems, that is, the gait cycle is analyzed according to layer feature change conditions of depths of images in each frame. The detection method comprises the steps of extracting gray values of single frame depth images after background removal; subjecting the gray value information of single frame depth images after background removal to layering according to a set threshold; performing uniform quantization coding on each layer of information; calculating the sum of pixel codes of each frame to form new signals; and separating the gait cycle according to minimal value points of the new signals. According to the detection method, the gray features of the depth images are fully used, the accuracy of the separated gait cycle is high, a certain foundation is laid for accurate gait recognition.

The invention discloses a charging and swapping facility operation analysis system based on the Ramsey pricing principle, comprising: an input module for inputting revenue data and cost data of the charging and swapping facility; Calculate the annual income of charging and swapping facilities based on the revenue data of the facilities; the cost calculation module of charging and swapping facilities calculates the annual cost of charging and swapping facilities based on the cost data of charging and swapping facilities; the net present value calculation module of charging and swapping facilities calculates the Calculate the annual net present value of the charging and swapping facility based on the annual income and annual cost of the swapping facility; the output module outputs the annual net present value of the charging and swapping facility based on the calculation results of the net present value calculation module of the charging and swapping facility. The invention is used for analyzing the investment profit and loss of charging and swapping facilities, and provides an analysis basis for enterprises to build charging and swapping stations and plan charging piles.

The invention belongs to the technical field of language analysis, and discloses a maximum-entropy model and TF-IDF (Term Frequency-Inverse Document Frequency) feature-based emotion analysis method. Amaximum-entropy model is used as a basic classification model; and a training document set is utilized to train the maximum-entropy model, training ends when the model converges or the number of iterations reaches a set threshold value, and an obtained maximum-entropy model is used for prediction of emotion classification. According to the method, classification information in a large-scale corpus can be deeply mined, and the maximum-entropy classification model is combined to realize fine-grained emotion analysis of textual text. Through testing, an F value of the method in the invention onthe fine-grained emotion analysis problem of 5-classification reaches 62.9%, and is increased by more than 10% as compared with F values of traditional methods of combining feature engineering and machine learning.

The invention discloses a water resource optimum dispatching method based on mixed shaping plan and decomposition. The problem is decomposed through analyzing the special structure of the problem, a local solution after the decomposition is obtained, and then, the special structure of the problem is utilized to obtain the optimum scheme of the special problem. The water resource optimum dispatching method has the advantages that a geographical module is divided through clustering, a mixed shaping plan mathematical model is built, the special structure of the problem is developed, and in addition, the problem is decomposed into small independent problems, next, the decomposed local solution is obtained, then, the local solution is recombined by using the special structure of the problem, the optimum scheme of the specific problem is obtained, and in addition, the optimality of the scheme is proved.

The invention discloses a problem target feature automatic identification and extraction method. The method comprises the following steps: generating at least one dependency relationship chain sampleaccording to a preset generation rule; according to a preset matching rule, matching a candidate dependency relationship chain matched with the to-be-analyzed question text from the at least one dependency relationship sample; and according to a preset screening rule, screening problem target words of the to-be-analyzed problem text from the candidate dependency relationship chain. The question target word recognition method has the advantages that the words related to the question intention of the user are recognized from the to-be-analyzed text through the question target word recognition method, and therefore the intention of the user can be recognized more accurately.

Disclosed are a performance object aggregation path interface display method and apparatus in integrated network management. The method comprises: configuring an aggregation path construction policy library and an aggregation path display interface object that uses a time dimension and a resource dimension as a coordinate system; and acquiring aggregation path data by using at least one computer interface that is initialized to be capable of receiving performance object aggregation path data, selecting a corresponding aggregation path construction policy from the aggregation path construction policy library according to the aggregation path data, performing aggregation path construction processing on the current aggregation path data according to the policy, and displaying the data on the aggregation path display interface object. The present invention can clearly display an aggregation relationship between performance objects and enable a user to clearly learn an aggregation process. Besides, when an error occurs on aggregation data, a user can quickly find the error by means of the present invention, to definitely trace, quickly locate, and analyze a problem.

The invention provides a nonlinear regression tuning method for synchronous motor model parameters based on penalty factors. The nonlinear regression tuning method for motor model parameters comprisesthe following steps: establishing a mathematical model, extracting key data points of peak and valley points, and obtaining nonlinear regression problem and nonlinear parameter regression solutions under large residual error. The LM algorithm can be used to solve the nonlinear regression parameter problem without residual error. If there is residual error, the LM algorithm can not find the idealsolution. The invention aims at the parameter regression analysis of the sudden short circuit of the synchronous motor with residual error, the nonlinear parameter regression analysis of the sudden short circuit test of the synchronous machine is solved, the nonlinear parameter regression analysis is insensitive to the initial value when the nonlinear regression analysis is made when there is residual error, and a better fitting effect can be obtained. The method has the universality of solving all nonlinear parameter regression. Through the present invention, an engineering solution is provided to the problem of residual nonlinear parameter regression analysis.

Provided is special teaching tool for early enlightened education of mathematics for children. The special teaching tool is mainly formed by mutually connecting and combining a module, a demonstration plate, a connection structure and member and matched pictures. The module includes elements like graphs, images and patterns related to basic knowledge contents included in primary school mathematic books. By combining the basic knowledge contents included in primary school mathematic book, teaching and training are performed, so firsthand experience is improved, perceptual understanding is improved, mathematic calculation ability training is strengthened and various kinds of mathematic thinking methods like the inductive method, the trail-and-error method, the exclusion method, the comparison method and the rounding method are gradually grasped. Problem observation, analysis and solving abilities are cultivated; perceptional understanding about mathematics basic knowledge and concepts is enhanced; and mathematics operation capability is improved. The special teaching tool is not only a teaching tool but also a toy, practice and thought ability is cultivated, elements included in the module are updated and replaced timely according to requirements of learning schedules and teaching and training requirements are met.

The invention provides a big data-based panic group emergency evacuation analysis method, which comprises the following steps of: simulating a shopping mall emergency evacuation scene through a big data platform, and processing shopping mall emergency evacuation big data by using a parallelized ant colony algorithm to obtain evacuation path selection of escape crowds with different panic degrees;therefore, the big data technology and the group panic theory are combined, the problems of large-scale, diverse-structure and low-value-density storage and analysis of the mall emergency evacuation related data are solved through the big data technology, the mall emergency evacuation related data are processed through the MapReduce-based parallelization ant colony algorithm. The influence of panic group behaviors on the evacuation efficiency is quantified, evacuation efficiency changes of different panic groups under the escape condition are obtained, the processing time is shortened, the processing cost and difficulty are reduced, and therefore the purposes of reasonably utilizing evacuation road sections and effectively evacuating the panic groups are achieved, and finally serious trampling accidents are prevented.

The invention discloses a complex electromechanical system reliability modeling method based on a probability behavior tree. The method comprises the following steps that: 1) combining the function execution logic of a complex electromechanical system with the hierarchy of an analyzed problem to determine the composition unit and the state transition of the system; 2) for each composition unit ofthe electromechanical system, establishing the sub-behavior tree model of each composition unit; and 3) utilizing a synchronous event expressed by an input/ output node in the behavior tree model to link the sub-behavior tree model of each unit, and forming a complex electromechanical system reliability model based on the probability behavior tree. By use of the method, the state transition in a complex electromechanical system behavior process can be visually and clearly expressed, a modeling process has good hierarchical characteristics and can be easily maintained, and the method is especially suitable for the complex electromechanical system reliability modeling. On the basis of the model, a probability model detection tool can be used for automatically calculating a reliability index,and the efficiency and the accuracy of the complex electromechanical system reliability evaluation can be improved.