36results about How to "Computational objective" patented technology

The invention discloses a method for calculating the power grid restoring capacity after power blackout. The method comprises the steps that related parameter information of black-start units, units to be restored and power transmission lines in a system is obtained; a weighting network connection matrix corresponding to the system is built; the sum of weighting capacities and corresponding per unit values of all the usable black-start units in power generation plants of all the usable black-start units are calculated; a generalized black-start unit node serves as the root node, and a minimal spanning tree T1 containing all the plant-station nodes is searched and generated; the average shortest distance D1 from the generalized black-start unit node in the tree T1 to nodes of all the units to be restored is calculated; the average shortest distance D2 from the generalized unit node in the tree T1 to rest load nodes is calculated; the average value of the D1 and the D2 is calculated; the power grid restoring capacity is calculated. The method for calculating the power grid restoring capacity after the power blackout has the advantages that contributions of the black-start units which are different in preferred sequence are distinguished, so that calculation of the power grid restoring capacity is more objective.

The invention discloses a comprehensive analysis method for maintainability of the radar structure. The comprehensive analysis method includes the following steps of firstly, determining types and the number of maintenance events and maintenance operation; secondly, determining maintenance schemes and fault rate of a component module; thirdly, virtually simulating during maintenance, and computing a quantized value of a single influencing factor of the maintenance events; fourthly, computing a quantized value of a single influencing factor of the radar structure; fifthly, determining a comment set and computing factor fuzzy evaluation matrix of a mechanism system/component module of the radar structure; and sixthly, computing maintainability fuzzy evaluation matrix of the mechanism system/component module of the radar structure. The comprehensive analysis method has the advantages that by simulating maintenance and determining maintainability influencing fact quantizing method, maintainability design of the radar structure is qualitatively and quantitatively analyzed and evaluated, weak links of the maintainability design are analyzed to instruct improvement of the design, and an accurate and objective maintainability evaluation method is provided for research stage of construction schemes of the ground elevation maneuvering radar structure.

The invention relates to a method for determining the theoretic porosity of a fabric through an image method, and in particular relates to a method for determining the theoretic porosity of a latticed sparse fabric through an image method. The method comprises the following steps of analyzing and processing a sparse fabric image through a digital image processing technology to obtain a theoretic porosity index; converting a gray image into a binary image according to a gray histogram two-peak method threshold of the fabric image, setting the pixel of a yarn region in a binary matrix corresponding to the binary image as 1, respectively projecting the binary matrix in the warp yarn direction and the weft yarn direction, and analyzing the central line positions of warp yarns and weft yarns; analyzing a cut image peripheral region according to the central positions of side yarns, wherein the quantity of the warp yarns and the quantity of the weft yarns in a new image are integers; acquiring the diameters of the yarns according to analysis on a wavy curve formed by projection of the binary matrix; calculating warp tightness and weft tightness so as to obtain the theoretic porosity index. By the adoption of the method, the theoretic porosity index can be objectively, accurately and quickly calculated.

The invention discloses an eyelid topology morphological feature extraction method based on deep learning. The method specifically comprises the following steps: collecting an electronic digital photo of a normal person, processing the electronic digital photo, constructing an ROI image training set, and inputting the ROI image training set into a to-be-trained convolutional neural network to obtain a trained convolutional neural network; positioning an eye region-of-interest (ROI) position by using a facial recognition method for a to-be-detected electronic digital photo to obtain a to-be-detected ROI image; inputting the to-be-detected ROI image into the trained convolutional neural network to output an image with an eyelid contour line and a cornea contour line, determining a circular scale and a pupil center of the to-be-detected electronic digital photo, and extracting eyelid topology morphological characteristics of a single eye. According to the method, the eyelid and cornea structures are segmented by using the convolutional neural network; after the center of the pupil is determined by using Mean Shift clustering, the parameters of the related structure of the eyelid are automatically calculated, so that the accuracy equivalent to that of manual measurement is obtained.

The invention provides a cycle division method and apparatus of a sedimentary stratum. The method comprises: pretreatment is carried out on obtained data reflecting an original stratum sedimentary environment and a lithological change to obtain pretreatment data; empirical mode decomposition is carried out on the pretreatment data to obtain a plurality of intrinsic modal functions; conversion is carried out on each intrinsic modal function to obtain an instantaneous frequency curve corresponding to the intrinsic modal function; according to the instantaneous frequency curve, a Milankovitch cycle curve is obtained; on the basis of the Milankovitch cycle curve, an accommodating space changing curve is obtained; and according to the accommodating space changing curve, an accommodating spatialascending half cycle and an accommodating spatial descending half cycle are obtained. According to the division method, the calculation process is objective and the influence on the process by the human factor is low. And the division method has high operability.

The invention provides a domain name reputation assessment method and apparatus. The method comprises the steps of obtaining a target domain name; performing feature extraction on the target domain name to obtain target domain name features; and inputting the target domain name features to a pre-trained domain name reputation grading model, thereby obtaining a domain name reputation score output by the domain name reputation grading model, wherein the domain name reputation grading model is obtained by pre-training domain name training sample features obtained by performing feature extractionon domain name training samples marked with objective reputation scores. Therefore, the objectivity of domain name reputation assessment can be improved.

A method and system for evaluating, charging, selecting, and publishing advertising effects is disclosed which are capable of accurately evaluating the effectiveness of the advertisement on the movable advertisement bearing object. The evaluation method comprises the following steps: a plurality of geographic regions are preset, and each geographic region corresponds to different advertising effect coefficients; Receiving a moving trajectory of the advertisement bearing object, and determining a geographical area through which the advertisement bearing object passes and a length of stay in thegeographical area according to position information and time information of each positioning point in the moving trajectory; The advertisement effect of the advertisement bearing object is calculatedaccording to the advertisement effect coefficient corresponding to each geographical area and the length of stay in these geographical areas.

The invention provides a transformer area line loss data processing method and device based on a Canopy-Kmedoids algorithm, and a medium, and the method comprises the steps: collecting basic data information of a power distribution network transformer area, wherein the basic data information comprises static parameters of the transformer area, and screening a transformer area sample set with a stable line loss rate based on the static parameters; and analyzing transformer area line loss rate influence factors based on the basic data information, selecting transformer area static parameters with a large influence degree, adopting a Canpoy algorithm to carry out coarse clustering on a data set, taking a central point of a Canpoy subset as an initial central point of a K-medoids algorithm to carry out fine clustering, calculating the sum of squared errors (SSE) of each clustering scheme, making an elbow diagram according to the sum of squares of errors of each clustering scheme, selecting a K value at an inflection point of the elbow diagram as an optimal K value as an optimal result, performing line loss calculation of the transformer area by using the optimal result, and controlling a power grid according to a line loss calculation result. The method improves the clustering effect, and enables the line loss calculation to be accurate and objective.

The invention provides a sensitive equipment fault rate calculation method and device. The method comprises the following steps of obtaining sample data of a voltage tolerance curve corresponding to sensitive equipment; calculating an uncertain region boundary of the voltage tolerance curve and a probability density function corresponding to a severity index according to the sample data; obtaininga practical voltage magnitude value and the practical voltage sag duration time when the sensitive equipment generates the voltage sag; and calculating the fault rate of the sensitive equipment afterthe occurrence of the voltage sag according to the practical voltage magnitude value, the practical voltage sag duration time, the probability density function and the uncertain region boundary. By implementing the sensitive equipment fault rate calculation method and device, the fault rate of the sensitive equipment can be objectively calculated; the artificial objective influence is avoided; the calculation accuracy is high; and effective reference can be further provided for timely use of measures to reduce the influence due to the voltage sag.

The invention discloses a technical resource productivity analysis method, device and equipment, and a storage medium. The method comprises the following steps: firstly, obtaining basic parameters ofto-be-analyzed technical resources, wherein the basic parameters comprise a self-owned personnel operation rate, an outsourcing personnel operation rate and a task execution rate; and then, substituting the basic parameters into a pre-constructed capacity gap calculation formula to obtain a capacity gap calculation result of the to-be-analyzed technical resource; and further, carrying out capacityanalysis on the to-be-analyzed technical resource according to the capacity gap calculation result to obtain an analysis result. Visibly, based on the productivity gap calculation formula, whether the technical resource gap exists or not or whether the technical resource is excessive or not can be quickly, accurately and objectively calculated, so that whether the outsiders are introduced or released can be determined according to the calculation result of the capacity gap, and the efficiency and the accuracy of judging whether the capacity of the technical resource is enough or not can be improved.

The invention discloses an electric quantity supplementing method based on clustering and a PQUI recognition algorithm, and relates to the field of power grid operation and maintenance. At present, the electricity stealing amount cannot be accurately calculated, the difference between the calculated electricity stealing amount and the actual electricity stealing amount is too large, and users andelectric power companies are difficult to keep fair. According to the invention, the electricity stealing time of the user is judged according to the load data of the user, then the electricity stealing manipulation is determined according to the relationship between the load data, the correction coefficient is determined according to the electricity stealing behavior, and finally the compensationelectric quantity is calculated according to the correction coefficient. And a clustering algorithm and/or a PQUI algorithm are/is adopted during calculation of the number of electricity stealing days. According to the technical scheme, the clustering algorithm and the PQUI recognition algorithm are adopted to calculate the corresponding electricity stealing amount, the calculation matching performance is good, the accuracy is high, the collected data can meet the requirements, the supplementary electricity amount of the electricity stealing user can be accurately, objectively and quickly calculated, the supplementary electricity amount is made to be consistent with the actual electricity amount, and the fairness of electricity utilization is improved.

The invention provides a Tibetan language paper plagiarism detection method and system, and relates to the technical field of modern education. Aiming at three different plagiarism phenomena of continuous text plagiarism, semantic rewriting plagiarism and translation plagiarism, the invention provides a longest common subsequence algorithm and an improved twin long-short-term memory network methodrespectively. Academic paper pre-detection based on abstract document vectors and a weight distribution strategy based on chapter positions are adopted to improve retrieval efficiency.

The present invention relates to the technical field of economic operation monitoring system, especially to a trade friction early warning model based on a big data classification algorithm. The method of the model comprises the steps of: the step 1: constructing data mark and trade friction system index and trade friction system index groups; the step 2: constructing an expert scoring model; thestep 3: constructing an SVM classifier; the step 4: training a classification model; the step 5: arranging a trade friction early warning interval; and the step 6: determining an application model prediction result and an application model prediction result interval. The method provided by the invention is based on the statistics theory, combines the newest data excavation theory enforcement method, employs the expert scoring assessment model and an analytic hierarchy process and takes historical data as a basis of model construction to achieve rapid, scientific and objective calculation of atrade friction index result; and moreover, an interval classification algorithm is provided by the model to calculate a trade friction risk grade interval to provide a trade friction risk prediction for the calculated trade friction result.

The invention discloses a financial market risk early warning method in an internet environment, which comprises the following steps: 1, preprocessing data; 2, selecting emotion seed words by using aTF algorithm, expanding an emotion dictionary by using Word2vec, defining a degree adverb weight, and calculating a text emotion intensity index; and 3, using an MF-DCCA model to calculate a cross multi-fractal spectrum; 4, constructing a characteristic index which influences the stock abnormal income; and 5 constructing a stock abnormal income prediction analysis model. According to the method,a more accurate risk early warning model can be constructed, so that more accurate risk prediction is realized, a basis is provided for financial market supervision, and a reference is provided for investor investment decision making.

The invention relates to the field of rock mass slope stability evaluation, and aims to provide a method for evaluating the slope stability of a bent toppled rock mass with a large bending degree. The method comprises the steps of (1) acquiring rock stratum parameters of a stratified rock slope; (2) dividing a free bending area and a coordinated bending area; (3) testing the stability of the free bending area; (4) calculating the interaction force between rock stratums of the coordinated bending area; and (5) judging the stability of the slope toe rock stratum and the whole slope. Due to the fact that the bending degree of the rock stratum of the large-deformation toppled slope is close to the arc shape, on the basis of a traditional linear cantilever beam method, the rock stratum is assumed to be in the arc shape, the limitation of the cantilever beam method is improved, and the large-bending-degree toppled slope can be evaluated. Due to the fact that the formula is simple and clear and the number of required rock parameters is small, the method is short in time consumption and low in cost; the calculation is objective, and manual parameter setting is not needed; and the stability of the bent toppled slope with a large bending degree can be accurately calculated.