276 results about "Variable weight" patented technology

A computer-implemented method performed by a processor for identifying social media posts relevant to a user, the method including the steps of receiving a first plurality of variable weights from a first user and a second plurality of variable weights from a second user, wherein each variable weight corresponds to a variable of a set of variables, receiving, from a social media feed, a social media post of a social media user, calculating, for the social media post, a first relevancy score using a scoring algorithm with the first plurality of variable weights as an input, calculating, for the social media post, a second relevancy score using a scoring algorithm with the second plurality of variable weights as an input, providing, via a user interface, the first relevancy score to the first user, and the second relevancy score to the second user.

The invention discloses a vehicle stability integrated control method based on a variable-weight model prediction algorithm. The method is mainly aimed at yawing motion and side-tipping motion of a vehicle to improve the stability and the riding comfort of the vehicle. The method mainly comprises steps as follows: step one, vehicle driving state information is acquired and subjected to estimation processing; step two, reference state values for keeping the yawing stability and the side-tipping stability of the vehicle are decided respectively; step three, a variable-weight model prediction control algorithm is used, a front wheel rotating angle and tire braking force are taken as control variables, and vehicle yawing and side-tipping stability control are integrated; step four, expected tire braking force is compared with actual pressure of a brake tube, an action instruction of an electromagnetic valve is determined, an additional front wheel rotation angle and steering action of a driver are superposed, and a final front wheel rotation angle is obtained; step five, a brake executer and a steering executer execute the action instruction of the electromagnetic valve and a front wheel rotation angle instruction, so that the vehicle keeps the yawing stability and side-tipping stability.

The invention relates to a hydrological model calibrating method used for small watershed individual flood forecasting, comprising the following steps: collecting and treating data of a typical rainfall flood process; selecting a hydrologic catchment model with a mixed runoff generation mechanism; determining an objective function used for small watershed individual flood simulation; optimally selecting parameters for calibrating a hydrological model; and judging the applicability of the calibrated hydrological model to individual flood simulation. Aiming at defects in calibration of the hydrological model and by combining with the rainfall runoff generation characteristics of small watersheds in the north, a concentrated hydrological model with a mixed runoff generation mechanism is selected; by taking SCE-UA algorithm as basis and comprehensively considering three flood elements including flood peak, flood volume and flood hygrograph, parameters of the hydrological model can be calibrated by constructing a comprehensive objective function with variable weight; and on the basis of evaluating the calibrating effect of the hydrological model, a three-level judgment criteria comprehensively considering rainfall characteristics, drainage area and engineering requirements is provided, so that the calibrated hydrological model can better meet the requirement of flood forecasting ofsmall watersheds in the north.

A vulnerability assessment method of water inrush from an aquifer underlying coal seam includes steps of: collecting main control factors determined by geological data of a target area to be assessed; quantifying relevant data against the main control factors to form thematic maps; performing normalization processing against attribute data corresponding to the respective thematic maps; establishing databases of normalized attribute data corresponding to the normalized thematic maps by utilizing GIS; determining a weight of each main control factor based on a constant weight model; determining a variable weight of each main control factor based on a zonation variable weight model; performing composite superimposition on the normalized thematic maps of the respective single main control factors, and newly building a topological relation of the relevant data among the attribute databases for performing multi-factor fitting analysis; and establishing a vulnerability assessment model based on the zonation variable weight model.

The invention relates to a transformer state evaluation method based on correlation analysis and variable weight coefficients, which includes collecting data of transformer states; classifying and processing the collected data as a basis of the transformer state evaluating; evaluating the transformer states; applying a correlation analysis method to establish a comprehensive state quantity evaluation system of the transformer; utilizing a single state quantity score calculating method and a transformer overall score calculating method to grade the transformer states; extracting constant weight coefficients of each of single state quantities and comprehensive state quantities; calculating constant weight coefficients of each of the comprehensive state quantities; calculating an overall score of the transformer states based on scores of each of the comprehensive state quantities and the constant weight coefficients; and determining a transformer operation state based on the overall score of the transformer states. The transformer state evaluation method has the advantages that evaluation models are simple and easy to program, no abundant state evaluation samples are needed, operation states of transformers can be determined rapidly, and operation states and conditions of transformers are truly reflected.

The invention discloses a compound control method based on a vector control system of a permanent magnet synchronous motor. The method comprises the following steps: converting a three-phase current of the permanent magnet synchronous motor into equivalent currents on a straight shaft and a crossed shaft by utilizing a vector conversion principle; further linearly decoupling the mathematical models of shafts d and q of the permanent magnet synchronous motor by using the method of id=0; and using fractional order PIgammaDmu control and sliding mode variable structure compound control, wherein the fractional order PIgammaDmu control and the sliding mode variable structure compound control can be used for performing joint cross-feedback control on the speed ring through a variable weighting factor alpha. The compound control method based on a vector control system of a permanent magnet synchronous motor, provided by the invention, has the advantages of both the fractional order PIgammaDmu control and the sliding mode variable structure compound control during the control of the speed ring, and the favorable factors are maximized while the unfavorable factors are minimized. Compared with the traditional PID (proportional-integral derivative) control, the fractional order PIgammaDmu control has a widened control scope, thereby more flexibly matching the sliding mode variable structure to realize the compound control to the permanent magnet synchronous motor.

The invention discloses a variable weight type random scheduling method based on real-time working conditions; the scheduling method optimizes the problem of the dynamic random rescheduling in terms of classification of various perturbation, rescheduling driving mechanism, the construction of rescheduling majorized set, the selection rule of the workpieces to be processed and rescheduling optimization algorithm, classifies various perturbation in the production process into two classes of invisible perturbation and dominant perturbation, adopts corresponding rescheduling driving mechanisms according to different types of perturbation, thus quickly and effectively dealing with various uncertain problems which randomly occur in the production process; the scheduling method is suitable for the mode with a plurality of varieties and single-piece small lot production, can rapidly and effectively handle the various uncertain problems which randomly occur in the production scheduling process and has strong coupling capacity with the real-time working conditions, thus being capable of improving the self-adaptability of a workshop production system to the uncertain working conditions and the agility of production scheduling, reducing unnecessary rescheduling, enhancing reaction capacity to the working conditions and lowering the loss of the production system brought by the various uncertain problems.

The invention belongs to the field of maintenance decision-making of hydraulic equipment, and relates to a method for the optimal maintenance decision-making of hydraulic equipment with risk control. The method mainly comprises three steps: 1) judging whether a system is in a status of defect by using a variable-weight association rule algorithm, if so, calculating the probability values of occurrences of latent faults of the system; 2) calculating the comprehensive evaluation value for the consequence of each latent fault by using a BP neural network; and 3) multiplying the probability values obtained in step 1 by the comprehensive evaluation values obtained in step 2 so as to obtain the VaRs (values-at-risk) of the latent faults, judging whether the VaRs are more than a specified threshold, if so, ranking the VaRs in descending order so as to determine the maintenance sequence; otherwise, returning to the step of monitoring. The method can judge whether a device is in a status of defect, judge the type of the latent fault and calculate the probability values of occurrences of latent faults only through a calculation; and compared with traditional risk maintenance methods, the method of the invention improves the accuracy of fault diagnosis, speeds up the diagnosis speed, and provides a better reference for online decision-making.

The invention discloses a prediction method, device and system for the health degree of the operating state of a water-cooling air conditioning system. According to the invention, the operating stateof the water-cooling air conditioning system is predicted through a neural network algorithm, and the future health degree of the water-cooling air conditioning system is given by means of a comprehensive evaluation method based on variable weights, so that preventative regulation of operating faults of the water-cooling air conditioning system in advance is achieved, reliable operation of the water-cooling air conditioning system and safety and stability of a data center are guaranteed, and therefore, the problem that in the prior art, the water-cooling air conditioning system cannot be predicted and regulated in advance is solved effectively.

The invention discloses a method for detecting remote sensing image change based on non-parametric density estimation, which mainly solves the problem that the estimation to the statistic items which relevant to a change type and a non-change type in a differential chart in the prior art has error. The realizing process of the method is that inputting two remote sensing images with different time-phase, removing noise of each channel of each image, obtaining noise-removing images of the two time-phase, and constructing difference images through adopting the change time-vector method, gathering the difference images into change type and a non-change type through applying K-means clustering algorism, obtaining the initial sorting results, and estimating the statistic items relevant to the change type and the non-change type in differential images through adopting non-parameter density estimation, carrying out the self-adapting space restriction combining the variable weight markov random field model, and obtaining the final change detecting results. The experimentation shows that the invention can effectively keeps the structure information of the images, removes insulation noise, improves the change detection processing efficiency, and can be used for the fields of disaster surveillance, land utilization and agriculture investigation.

The invention provides a transformer fuzzy comprehensive evaluation method based on a variable weight. The method includes following steps: collecting state data according to a pre-established transformer state comprehensive evaluation index system, and performing dimensionless standardization processing on evaluation indexes; determining a constant weight by employing an analytic hierarchy process, and performing variable weight processing on a constant weight vector with the combination of an evaluation index set obtained after standardization processing; establishing a power transformer state grade remark set; determining a fuzzy comprehensive evaluation matrix according to the membership degree of the bottom layer in a membership function calculating evaluation model for the state grade, calculating an evaluation result, and obtaining the overall state of the transformer by employing a fuzzy comprehensive evaluation operator; and obtaining the membership degree of each state for the fuzzy comprehensive evaluation, and determining the operation state grade of the transformer by employing a maximum membership degree principle. According to the method, the change of the weight value of the quantity of state is realized according to the practical state index so that the influence of the quantity of state with large deterioration degree on an evaluation target is increased, and the state evaluation is more reasonable.

The invention discloses a variable-weight hydropower unit deterioration evaluation system and an evaluation method. The system comprises an evaluation data layer, an evaluation index layer, an evaluation algorithm layer and a man-machine interaction layer, which are connected in sequence. The method is a variable-weight multi-factor unit deterioration evaluation algorithm and comprises: performing unified processing on various evaluation data by adopting a data integration technology of the evaluation data layer; integrating and inputting evaluation data to the evaluation index layer; calculating deterioration degree of each index; reading a weight parameter of each index at the same time; and finally performing weighted calculation to obtain an overall health state result of a unit and outputting the overall health state result to a man-machine interface. By utilizing the system and the method, the unit can be subjected to deterioration evaluation and online operation monitoring and state repair guidance are provided; and an effective solution can be provided for constructing a state repair and deterioration evaluation system for hydropower units in different hydropower plants, different periods and different states, and efficient and practical decision-making services are provided for device deterioration analysis of the hydropower plants, so that reliable support is provided for implementation of state repair.

A kettlebell having a hollow interior portion, and a substantially flat surface upon which the kettlebell may rest. The interior portion is lined with a water-impervious coating. Additionally, or alternatively, the interior portion may have a water-impervious bladder disposed therein.

A cooperative game method and trapezium-cloud model-based power distribution network operation state fuzzy and comprehensive evaluation method is characterized by comprising the steps of considering the purposiveness, the systematicness, the operability, the independence, the significance and the dynamism, and constructing a multi-dimension hierarchical power distribution network index system based on the safety, the high quality, the economy, the Intelligence, the environmental protection property and the sustainability; utilizing a weight method, an entropy weight method, a anti-entropy weight method and a compatibility matrix analysis method to calculate the power distribution network index weights separately; carrying out the cooperative game on the determined weights to obtain an optimal combined weight; carrying out the variable weight correction on the combined weight to obtain a final weight value; dividing the evaluation grades of a power distribution network to obtain an evaluation set; calculating a trapezium-cloud model parameter that each index corresponds to each evaluation grade, utilizing a trapezium-cloud model to calculate the membership degree values of the indexes of the to-be-evaluated power distribution network, and calculating a membership degree vector and an evaluation result of the whole power distribution network layer by layer and upwards on a fuzzyand comprehensive evaluation frame.

A system for dispensing a viscous material onto a substrate which includes a dispensing element, a viscous material reservoir and a metering device coupled between the reservoir and the dispensing element for metering a variable amount of a viscous material through the dispensing element. The dispensing element and metering device can be moved by a positioner along a predetermined pattern adjacent a surface of a substrate. A weigh scale located adjacent the substrate receives a metered amount of the viscous material and produces signals representative of a variable weight of the material dispensed during a predetermined time interval. A controller adjusts a speed of movement of the positioner along the predetermined pattern to cause the dispensing element to dispense a desired amount of material based on a calculated flow rate. Alternatively, the controller adjusts a rate of delivery of the metering device based on the calculated flow rate to cause the dispensing element to dispense the desired amount of material along the predetermined pattern. Closed loop temperature control may be provided for the dispensing element and/or the substrate to ensure a substantially constant viscosity and a substantially constant flow rate. A prime and purge station may be provided adjacent the substrate for sucking air bubbles from the dispensing element and metering device.

The invention discloses a method for detecting the pollution grade of an insultor, which is characterized by comprising the steps of: 1. obtaining ultraviolet discharge pulse x1<0>, temperature valuex3<0> and humidity value x4<0>, and obtaining weather conditions; 2. determining the value of each parameter after normalization; 3. determining the constant weight value of each index factor; 4. obtaining the variable weight value of each index facor; 5. generating the membership function lists of discharge pulse and running age limit, and the membership function lists of the temperature value, the humidity value and the weather conditions; 6. generating the single factor judgement matrix A and matrix B of the index layer under intrinsic factors and enviromental factors; 7. obtaining the evaluating matrix S of the intrinsic factors; 8. obtaining the evaluating matrix Z of the enviromental facors Z; and 9. obtaining the status evaluation v of the insulator. The method has the obvious effects of: replacing the traditional method of climbing the rod for examination by workers and realizing continuous real-time detection. The method effectively conducts accurate and reliable grade analysis to the current running state of the insulator, and is convenient for monitoring and changing the insulator reasonably by the workers.

A system and method for locating optimal routes between source and destination nodes in a communications network, in particular, a wireless ad-hoc communications network by employing a link reliability algorithm that estimates the reliability of links between nodes using a prediction mechanism and a variable-weight filter. The prediction can be based on signal strength, signal-to-noise ratio or any statistic collected at the physical layer that is deemed representative of the quality of a link, and the weighting filter adjusts the predicted value based on the traffic conditions (e.g., idle, light traffic, moderate traffic or heavy traffic) being experienced by the nodes whose link quality is being estimated.

A computer implemented method, a data processing system, and a computer program product determine carrier selection based on variable volumetric weight and variable completion times. A product is identified for production. The product for production has a variable weight and a variable dimension based on components included in the product for production. A projected volumetric weight of the product for production is determined. A projected completion time of the product for production is determined. A projected carrier assignment of the product for production is then determined in response to determining the projected volumetric weight of the product for production and determining the projected completion time of the product for production.

The present invention discloses a variable weight combined forecasting method-based electric power load short-term forecasting method. According to the present invention, aiming at the disadvantages that a conventional single load forecasting model and a fixed weight combined forecasting model are low in forecasting accuracy, and by comprehensively considering the time correlation of the electricpower loads and the influence of other related factors on the electric power loads, and combining various electric power load forecasting models, a variable weight combined forecasting model of the electric power load short-term forecasting is established. Meanwhile, aiming at the disadvantage that a particle swarm optimization variable weight parameter combined forecasting method traps in a localoptimal solution easily, a parameter dynamic adjusting particle swarm optimization algorithm is established, thereby realizing the optimization solution of the weight parameters of the variable weight combined forecasting model, and finally realizing the short-term forecasting of the electric power loads. The combined forecasting model of the present invention is better than a conventional load forecasting method, a fixed weight combined forecasting method and a particle swarm optimization variable weight parameter combined forecasting method, and has the higher forecasting accuracy.

The invention relates to a composite insulator ageing state comprehensive evaluation method based on multi-characteristic vectors. According to the method, the mathematical theory of fuzzy variable weights is introduced into state evaluation of composite insulators, parameters which comprehensively and accurately reflect the working states of the insulators are separately selected, an improved analytic hierarchy process (IAHP) is adopted, and opinions of an expert group are processed. On the basis of constant weights, data of the insulators is combined, and variable weights of all factors are determined. Before indexes are adopted to conduct state evaluation, all the indexes are subjected to normalization, quantitative data is transformed according to corresponding formulas, a scoring system is adopted for qualitative data, the score ranks from zero to one, the distribution function which combines half trapezoid and triangle is adopted to determine the membership degree, and the influence of all index quality on the insulator state is synthesized by adopting a multilevel fuzzy comprehensive evaluation method. According to the method, related state parameters are organically and comprehensively combined, the accurate and positive evaluation on the state of the insulators in running is made, and the method has the practical value.

The invention belongs to the traffic management technology field and relates to a traffic jam prediction method based on multi-source data and a variable-weight combination model. The research time isdivided into different time segments, vehicle GPS data and weather data of each time segment are collected, the vehicle GPS data is processed, and the average vehicle operation speed of the researchroad segment at the research time segment is acquired; an ARIMA model is trained through historical data, and ARIMA model parameters are calibrated; a BP neural network model is trained through historical data; certain weight values are assigned to the ARIMA model and the BP neural network model to acquire a combined model, and weight value error determination is carried out through the ARIMA model and the BP neural network model; the future traffic flow speed is predicted through the variable-weight combination prediction model, and traffic jam conditions are determined. The method is advantaged in that the GPS data is employed, road detection equipment sot and manpower cost can be reduced, the variable-weight combination prediction model is utilized to enhance model adaptability, prediction accuracy is improved, and a traffic jam problem can be solved in an auxiliary mode.

The invention discloses an OPC correction method based on a photoetching process window. When the margin position error of a pattern is calculated, the method uses different photoetching model weights for different patterns in a photoetching layout according to a photomask error reinforcement factor, a light intensity maximum value, a light intensity minimum value and slope of a pattern measuring point. The method sets variable weights to patterns by determining the pattern characteristics and the pattern environment in the layout, and prevents the OPC correction error caused by the changes of the photoetching pattern.