47 results about "Complexity index" patented technology

The invention relates to a method for improving the complexity index of a deep shale gas fracture. The method is characterized in that when a fracturing design of the a deep shale gas well is performed, selection and an injection manner of a fracturing fluid, selection of a supporting agent, and the number of perforations are optimized and controlled, and an artificial main fracture can be opened and communicate with a natural fracture as much as possible in an extending process; extension of a single fracture is longer, expansion of the single fracture is wider, and finally the complexity of the deep shale gas fracture can be improved to the greatest extent. The method can be used for deep shale gas reservoirs having the depth of more than 3500 meters and in which the natural fractures containing carbonate minerals are distributed in a reconstruction range of the artificial main fracture, and a certain included angle is formed between the fracturing main fracture and the natural fractures. The method is reasonable in design, is simple in process, is easy to operate, is high in fracturing construction successful rate, can effectively increase the volume of deep shale gas segment fracturing fractures, can remarkably improve the fracturing construction effect, and can acquire more economic benefits.

The invention discloses a coma degree evaluating method based on multiple indexes of non-linearity and complexity, which is used for monitoring the brain state of a patient in a coma, and can realize continuous coma depth monitoring, and coma phase grading and early warning. Multiple complexity indexes such as complexity, Lyapunov exponent, approximate entropy, related dimensions, and the like are extracted from coma electroencephalographic signals by adopting a nonlinear dynamics analytical method, and a comprehensive coma state exponent is obtained by combining a traditional GOS (Glasgow Outcome Scale) evaluation system and a traditional GCS (Glasgow Coma Scale) evaluation system; the coefficients of the correlation between the parameters are obtained by clinical experiments; a coma state grading database is founded and a parameter fusion coefficient is determined on the basis of clinical effects; and finally, complete conscious state grading evaluation exponents are founded to guide the treatment of a patient and make prognosis.

The invention discloses a C0 complexity and correlation coefficient-based milling chatter detection method. The C0 complexity and correlation coefficient-based milling chatter detection method includes the following steps that: state information of a milling process is obtained through a vibration acceleration sensor; obtained signals are preprocessed through using a comb filter, so that periodic components can be filtered out; the complexity of residual signals is calculated through utilizing C0 complexity indexes, so that the degree of nonlinearity of chatter can be reflected; and the correlation coefficient of original signals and filtered signals is calculated, and therefore, the proportion of chatter components in the signals can be reflected, and chatter degree in the machining process can be described. Compared with a traditional chatter detection method, and according to the C0 complexity and correlation coefficient-based milling chatter detection method of the invention, characteristic information reflecting chatter and characteristic information irrelevant to chatter are separated out from each other, and various kinds of indexes are fused, and physical characteristics of milling chatter can be essentially characterized. With the C0 complexity and correlation coefficient-based milling chatter detection method adopted, the sensitivity, accuracy and reliability of chatter detection can be effectively improved, and misdiagnosis rate and missed diagnosis rate can be decreased.

The invention relates to a logistics vehicle scheduling area optimization method for a mixed model assembly line with an uncertain demand, and is used to obtain a region division program of logisticsdistribution in a mixed model assembly line. The method comprises the following steps of: 1) defining the full load ratio of logistics distribution vehicles and the complexity of distribution tasks; 2) obtaining the constraint conditions of a multi-objective optimization model, and establishing a multi-objective optimization model with a goal of maximization of the average full load ratio of the logistics distribution vehicles and minimization of complexity indexes of the distribution tasks; and 3) using a genetic algorithm to solve the multi-objective optimization model to obtain an optimal allocation program. Compared with the methods in the prior art, the method in the invention has the advantages of ensuring the full load ratio of the delivery vehicles, reducing the complexity of the delivery tasks, avoiding the unstable state of the delivery vehicles caused by the accumulation of the demand uncertainty factors and improving the robustness of the logistics scheduling of the mixed model assembly line.

A method and system for analyzing software to estimate the cost of production, development and maintenance of computer applications are disclosed. Unlike previous proposals for such analysis, where the primary measured parameters are the numbers of lines of code and function points, the inventive method identifies high complexity software segments arising from specific discontinuities in execution of the program, ie points at which the program has to, in effect, make decisions. These items are assigned complexity indices which may be summed to give an overall complexity value for the program or the indices may be displayed as a histogram showing the complexity distribution of the program.

The invention discloses a method and a system for detecting sector operation performance integration indexes based on principle component analysis. The method comprises steps of inputting sector zone operation performance indexes, comprising a sector zone trafficability index, a sector zone complexity index, a sector zone safety index, a sector zone economic index and a control staff workload index, using principle component analysis to determine the principle component of the sector zone operation performance, and calculating comprehensive indexes of the sector zone according to the principle component of the sector zone operation performance. The method disclosed by the invention performs comprehensive consideration on the multi-dimension indexes affecting the sector zone performance detection index data of the sector zone performance comprehensive index detection. Furthermore, the principle component analysis is applied in the invention and the processing is performed on the inputted sector zone operation performance indexes. All in all, the invention improves the detection efficiency, satisfies the requirement for real-time detection and alarming on the sector zone performance comprehensive index by the air traffic control unit, improves the control operation management level, optimizes management control air domain structure and provides data support.

The invention provides a myoelectricity signal identification method based on complexity, a fractal dimension and a fractal length, and aims to realize that a main operator can synchronously control a remote manipulator in a teleoperation robot system. A mode recognition characteristic uses an L-Z complexity index and fractal dimension index of a myoelectricity signal; a classifier uses an improved KNN model method which uses a clustering method as a data processing method; and an algorithm is equipped with an incremental learning capability. A hand movement speed of the operator depends on an activity intensity of arm muscles; and muscle activity intensity is represented by a maximum fractal length of the myoelectricity signal. In a certain range, the maximum fractal length of the myoelectricity signal and the hand movement speed of the operator form a monotone increasing function. The maximum fractal length of the myoelectricity signal serves as the input control amount, so as to realize the grasping speed control of the manipulator, and the good result is achieved.

The invention discloses a method for predicting the workload of a controller approaching a controlled sector. The method comprises: a sector complexity index for evaluating the workload of a controller approaching a controlled sector is established; sector complexity index data and a controller workload self-evaluation value are collected; and then a controller workload model based on a BP neuralnetwork algorithm of PA and PCA is established and a prediction result is obtained. With the method disclosed by the invention, the workload level of the controller can be evaluated timely; the powerful support is provided for the safe, high-efficiency and ordered operation of the aircraft in the sector; and the prediction accuracy is improved.

The embodiment of the application discloses a method for evaluating the complexity of cracks. The method comprises the following steps: obtaining the volume of a fracturing fluid, which is used in fracturing of a fracturing well, the volume of a horizontal crack generated through fracturing and the volume of a vertical crack generated through fracturing; calculating a multi-crack coefficient and a crack complexity index through formulas according to the volume of the fracturing fluid, the volume of the horizontal crack and the volume of the vertical crack, wherein R represents the multi-crack coefficient, Ve represents the sum of the volumes of the horizontal crack and the vertical crack, Vi represents the volume of the fracturing fluid, beta represents the crack complexity index, Vh represents the volume of the horizontal crack, and Vv represents the volume of the vertical crack; and evaluating the complexity of the cracks generated through fracturing of the fracturing well. The method, disclosed by the embodiment of the application, can be used for evaluating the complexity of the cracks.

An embodiment of the invention provides a low-power coding method and a low-power coding device. The low-power coding method includes receiving the quantities of skip macro blocks and the quantities of macro blocks with motion vectors MV which are default values; acquiring coding complexity indexes according to the quantities of the skip macro blocks and the quantities of the macro blocks with the motion vectors MV which are the default values, and judging scene types corresponding to target frames; utilizing slave coders as target coders if the quantities of first preset scenes in the scene types respectively corresponding to the multiple continuous target frames are larger than threshold values, and starting the slave coders for coding. The skip macro blocks correspond to the target frames transmitted by original target coders. The low-power coding method and the low-power coding device in the embodiment of the invention have the advantages that the slave coders are used as the target coders to code follow-up target frames, power consumed by the slave coders is lower than power consumed by main coders, the target frames corresponding to the simple motion scenes are coded by the slave coders instead of the main coders, and accordingly coding power can be effectively reduced as compared with a mode in which all target frames are coded by the aid of main coders.

Main parameters of domestic and overseas shale gas compressibility evaluation methods are analyzed and summarized, the high-temperature, high-pressure and high-plasticity characteristics of a deep shale gas layer are combined, and deep shale gas compressibility comprehensive evaluation parameters are optimized mainly from the aspects of geology and engineering factors; the influence of formation confining pressure and rock anisotropy on parameters is fully considered, and a calculation method of compressibility evaluation parameters is formed; a fuzzy grey correlation analysis method is used; analyzing the correlation between the compressibility index curve and the crack complexity index curve of different weight combinations; the weight combination is optimized according to the maximum principle of the correlation coefficient, a compressibility comprehensive evaluation mathematical model is established, a deep shale gas compressibility comprehensive evaluation method is formed, and the method has guiding significance for the fracturing parameter optimization design of the deep shale gas for improving the crack complexity.

The invention provides a fracturing method of a normal-pressure shale gas reservoir. The fracturing method comprises the following steps that firstly, reservoir evaluation parameters are obtained; secondly, fracturing construction parameters are determined, specifically, the viscosity, the displacement and the using amount of fracturing liquid and the particle size and the using amount of proppingagents are determined; and thirdly, fracturing construction is conducted, specifically, the reservoir is subjected to segment-by-segment fracturing construction through a spiral-slug-type mixed particle size sand-adding mode. According to the fracturing method of the normal-pressure shale gas reservoir, the complexity index of cracks of the normal-pressure shale gas reservoir can be effectively increased, and the fracturing transformation effect of the normal-pressure shale reservoir is improved accordingly.

A scientific complexity quantification system calculates a specific percent complexity index rating for each manufactured product that can be graphed and compared to other products and that is based on mathematical quantifications of each product's key attributes. The complexity index takes into consideration differences in design and manufacturing complexity, financial considerations, product solution complexity and customer experience. The attribute scoring of individual products are then sorted into potential sourcing categories, such as “outsource,”“in house fulfillment,” or “further evaluation needed.”

The invention discloses a method for identifying operational risks of vehicular equipment in consideration of the complexity of traffic environments, relates to methods for identifying operational risks of vehicular equipment, and is applied to the field of traffic engineering. The method includes firstly, mounting driving recorders, lane trackers, eye tracker cameras, rear position cameras, leftcameras, right cameras and control panel cameras inside vehicles; secondly, weighting operational durations of the vehicular equipment and lane deviation durations of gazing points of drivers to obtain total operational durations of the drivers on the vehicular equipment; thirdly, dividing the complexity of the traffic environments into four grades; fourthly, determining grades of traffic environment complexity indexes, namely values of the traffic environment complexity indexes; fifthly, acquiring score values of the operational risks of the vehicular equipment according to the total operational durations of the drivers on the vehicular equipment and the values of the traffic environment complexity indexes. The method has the advantage that the problem of low risk identification degrees due to the fact that complex traffic environments in which existing vehicles are located are not taken into consideration in the prior art can be solved by the aid of the method.

The invention discloses a method for evaluating formation conditions of complex fracturing fractures in tight reservoirs. This method takes the calculated fracture complexity index as a threshold value, and evaluates the effects of geo-stress difference, elastic parameters of target bed and interlayer, target bed thickness, porosity and permeability characteristics of target bed, operation displacement and fracturing fluid properties on the formation conditions of complex fracturing fractures. The method can clearly and intuitively give the three-dimensional spatial morphology of the whole process of the complex fracturing fracture from initiation to extension, the key influencing factors of fracturing complexity are analyzed one by one, good repeatability and high evaluation efficiency are exhibited, accurate identification of natural geomechanical conditions and artificial operation conditions in fracturing process are realized, and the method can effectively guide in-situ fracturingdesign, especially suitable for evaluation of complex fracture formation conditions in fracturing reconstruction of tight reservoirs with poor physical properties, low permeability and low natural productivity.

The invention provides an exploration potential planar partitioning method and device for lacustrine facies shale oil. The exploration potential planar partitioning method comprises the steps that thecontent of hydrocarbon generation components in a target shale oil formation, the hydrocarbon yield of the hydrocarbon generation components at all evolution stages, the organic matter abundance, crude oil density, shale porosity and shale invalid porosity of the target shale oil formation, the age of deposition of oil groups in the target shale oil formation and structure contour data, corresponding to the age of deposition, of the target shale oil formation are obtained; the oil production volume of shale in unit mass is calculated; maturity partitions of the target shale oil formation aredetermined; the diagenesis index, the horizontal stress index and the vertical stress index are calculated; then the cumulative structure complexity index is calculated; structure partitions of the target shale oil formation are determined; and exploration potential planar partitions of the target shale oil formation are determined according to the maturity partitions and the structure partitions.According to the exploration potential planar partitioning method, the exploration potential evaluating precision of the lacustrine facies shale oil is improved, and an evaluation result is closer tothe underground real state.

The embodiment of the invention provides a visual search method, a device and a device, wherein, the method comprises the following steps: acquiring a plurality of images to be retrieved; For each image to be retrieved, extracting the global feature information of the image to be retrieved. Calculating a complexity index corresponding to the image to be retrieved according to the global characteristic information of the image to be retrieved; Determining a code rate matching the complexity index; Based on the code rate, extracting and saving the image features of the image to be retrieved areextracted and saved, wherein The image features are used for visual search. The visual search method, the device and the device provided by the embodiment of the invention can reduce the waste of thestorage resources.

The invention relates to an automatic generation method for the active safety system test scene of an automobile, and belongs to the field of the active safety system test of the automobile. The method comprises the following steps that: S1: calculating two evaluation indexes for measuring the effectiveness of a test scene, wherein the two evaluation indexes are a scene complexity index and the importance degree index of an influence factor in the scene; S2: using two evaluation indexes for guiding the test scene generation process of an improved combined test algorithm; S3: obtaining a test scene set, and utilizing the evaluation indexes to evaluate the effectiveness of a generated scene; and S4: using the test scene set to the testing and the evaluation of the active safety system to betested. By use of the method, the integral effectiveness of the test scene in the set can be greatly improved while the finally generated test scene set has the advantages that a traditional combinedtest algorithm utilizes a small-scale test scene set to realize a high fault coverage rate, so that test cost is effectively lowered, and test efficiency is obviously improved.

The invention discloses a fault severity evaluation method based on a variable-step size multi-scale complexity fusion index. According to the method, firstly, a variable step size multi-scale strategy is put forward, fault features are mined more comprehensively by optimizing a coarse graining process, and the strategy solves a problem that deep information is difficult to mine due to single-scale analysis of a traditional complexity index (LZC); a problem that the calculation result is inaccurate due to the fact that the sequence length of a traditional multi-scale complexity index (MLZC) is shortened along with the increase of the scale is solved, and a variable step size multi-scale complexity index (VSMLZC) is constructed. Compared with a traditional complexity index, the method is advantaged in that fault features can be mined more accurately and comprehensively, and early fault diagnosis and damage degree evaluation of the rotating equipment are achieved.

The invention discloses a method for measuring a complex structure of an old city block form. The method is suitable for the field of city design. In an existing method, a black and white graph base method cannot describe human behaviors and activity modes, attention to parcels and buildings is lacked in a street structure analysis method, and integration analysis can be carried out on topologicalconnection relations among streets, the parcels and the buildings at the same time. Firstly, the basic type of a block and the cognitive basis of three complex structure types of interlocking, combining and nesting are determined; secondly, describing different types of drift diameter structures by using a 'point 'and 'line' graph theory tool; and finally, proposing a complexity index system anda calculation method thereof, and realizing visual comparison and analysis of complexity characteristics among different types of structures. The invention provides a scientific quantitative analysismethod for cognizing the internal organization logic of the form of the old city block of China.

The invention discloses a hydraulic fracture complexity prediction method based on the residual stress levels of rock cores. The method is characterized by comprising the following steps: performing physical simulation tests on static rock mechanical parameters of sampled rock cores of an implemented well; performing numerical simulation tests on rock mechanical parameters based on numerical valuerock cores to obtain fine residual strength characteristics of reservoir rock masses; establishing different finite element analytical models for different reservoirs with different residual stress,and calculating hydraulic fracture complexity indexes for predicting hydraulic fracture complexity. The method can be used for catching the whole process of crack production and extension of complex fracture networks in real time, can realize advanced assessment of fracture complexity and guide fracturing construction design and has great significance in improving fracturing design and increasingcomplex fracture network volumes.

The invention relates to the technical field of artificial intelligence, in particular to a bus passing time prediction method based on big data and artificial intelligence. The method comprises the following steps of: segmenting a bus road section into a plurality of sub-road sections, and acquiring driving data of a bus and vehicle optical flow information in the sub-road sections; according to the driving data and the vehicle optical flow information, obtaining road condition features, road section feature vectors, complexity indexes and driving habit indexes of each sub-road section; inputting the road condition features, the road segment feature vectors and the driving habit indexes into a passing time prediction network to output predicted passing time of the corresponding sub-road sections; a loss function of the passing time prediction network is constructed by a complexity index, predicted passing time and real passing time; and obtaining the passing time of the bus road section according to the sum of the predicted passing time of the plurality of sub-road sections, the waiting time of traffic lights and the stopping time of the bus road station. According to the bus passing time prediction method based on the big data and artificial intelligence of the invention, the traffic time of each sub-road section is predicted, so that accumulated error is reduced, and the accuracy of passage time is improved.

The invention discloses a recovery performance analysis method for car products. The recovery performance analysis method is characterized by including firstly calculating the integral disassembly difficulty index D; then calculating the comprehensive recovery index R of an integral car; and sequentially calculating material complexity index U, integral car recovery economic index E and an integral recovery performance VR. The recovery performance analysis method is used for quantitatively analyzing disassembly of the car, so that people can analyze recovery performances of the car products in the process of sample car trial-manufacturing of the car products.

The invention discloses a civil case complexity index evaluation method and system. The method comprises the steps that the relevant data of each civil case under the specific computing domain are acquired; multiple indexes used for computing the complexity are selected; the index value of the jth secondary index of the ith case is obtained according to the relevant data; the index value is normalized; and the case complexity is computed. All the indexes of the case from the process of case registration to case settlement and the correlation between the indexes are extracted, and the degree ofcomplexity of the civil case is reflected by the quantified indexes by using the algorithm so that the degree of complexity of the civil case meeting the local condition can be accurately computed and accurate quantification of the degree of complexity of the civil case can be realized. Therefore, the workload of the judge can be evaluated and the degree of complexity of judgment can be greatly reduced.

The embodiment of the invention provides an unmanned vehicle reaction agility evaluation method, which comprises the following steps: evaluating the traffic environment complexity of the unmanned vehicle, obtaining an environment complexity index M1; Evaluating driving behavior of unmanned vehicles and obtaining driving behavior index Bk; obtaining a real-time performance index M2; a weighted sumof M1, Bk and M2 is obtained to obtain an unmanned vehicle agility score M, and a reaction agility level grade of the unmanned vehicle is determined according to the unmanned vehicle agility score M.In accordance with that above manner, the method to evaluate the response agility of unmanned vehicle can be provided. The method analyzes the response agility of unmanned vehicle from three dimensions: environmental complexity, driving behavior and real-time operation, and can obtain scientific and effective evaluation results, so as to ensure the stable, safe and reliable driving of unmanned vehicle in the real environment. The embodiment of the invention also provides an unmanned vehicle reaction agility evaluation device.

The invention provides a connected graph processing method and device, and the method comprises the steps: obtaining the number of authorized paths in a predetermined connected graph; Determining thestructure complexity corresponding to the predetermined connected graph based on the authorization path number; And adjusting resource configuration corresponding to the predetermined connected graphbased on the structural complexity. The method is mainly used for researching the complexity caused by the structural difference of the authorization relation graph, a metering method is provided, thestructural complexity index is calculated, a user can conveniently adjust the authorization relation graph according to the index, the complexity of the authorization relation graph is reduced, the intuitiveness of the authorization relation graph is improved, and the visual effect is improved.

The embodiment of the invention provides a software code complexity detection method and device and electronic equipment, and the method comprises the steps: obtaining code complexity indexes of a plurality of code segments of to-be-evaluated software; performing step-by-step longitudinal aggregation on the code complexity indexes of the plurality of code snippets to obtain a first aggregation score; and transversely aggregating the first aggregation score to obtain a second aggregation score, and outputting the second aggregation score as the code complexity. According to the embodiment of the invention, the code complexity of the to-be-evaluated software is detected and evaluated in a step-by-step longitudinal aggregation manner; a comprehensive and deep complexity detection result can be formed, and in addition, a developer can conveniently locate code fragments with problems in the aspect of code complexity through backtracking the complexity detection process of step-by-step aggregation.