52results about How to "Reduce iteration time" patented technology

The invention discloses a post-disaster repair decision-making method and device for power distribution network. The method comprises the steps of collecting fault information distribution transformerlevel disaster damage information,first-aid repair teams and material transport vehicle information under disaster conditions; on the premise of meeting the distribution network operation constraintand the path planning constraint,using distribution network fault point selection and first-aid repair teams and material scheduling as decision variables,establishing a power distribution network frame reconstruction and material personnel allocation auxiliary decision-making model,wherein the model comprises a lower tie line action scheme determination model taking the maximum recovery load as atarget and an upper construction team and material scheduling scheme determination model taking the minimum total power loss in the rush-repair process as a target; and solving the dispatching auxiliary decision-making model by adopting an upper-lower layer iterative solving method,and finally determining a post-disaster repair decision-making scheme of the power distribution network. According to the method,the problem that the target of minimum economic loss cannot be achieved due to the cooperative action of a construction team and a material vehicle is fully considered,and decomposition codes of all parts are simplified.

The invention discloses a Cam-shift-based prediction tracking method. A Kalman filtering and Cam-shift algorithm combination method is proposed; and a linear prediction and Cam-shift algorithm combination-based target prediction tracking method is proposed, namely, a linear prediction method replaces Kalman filtering to finish prediction estimation, and a prediction estimation result is substituted into a Cam-shift algorithm to perform tracking. In order to well finish position prediction tracking of a moving target in a complex background with interference of factors such as shielding and the like, the Kalman filtering and Cam-shift algorithm combination method is researched. The Kalman filtering can finish position prediction of the moving target more accurately; and the tracking can be well finished by combining the Kalman filtering with the Cam-shift algorithm. Based on this, the linear prediction and Cam-shift algorithm combination-based target prediction tracking method is proposed, namely, the linear prediction method replaces the Kalman filtering to finish the prediction estimation, and the prediction estimation result is substituted into the Cam-shift algorithm to perform the tracking. An experiment shows that the method can not only ensure the accuracy of tracking in a shielding process but also shorten the iterative time, and can better meet the requirement of timeliness.

The invention discloses a detection system based on a QT platform and a use method thereof. The invention relates to a detection system based on a QT platform, in particular to a detection system based on the QT platform and used for detecting an airplane. According to the invention, the system and the method are convenient to operate, clear in logic and high in modification speed, an operator ofthe detection system can directly modify the detection system conveniently and efficiently according to micro modification of control/output data in a subsystem of the detection system, so that a designer of the detection system does not need to repeatedly update the detection system for multiple times. The system comprises an interface layer, a data layer and a communication layer, the communication layer comprises a packing module, an unpacking module and a communication module and is used for completing encoding and decoding of communication data frames and setting of necessary communication parameters, so that the detection system can communicate with an underlying system. According to the invention, the research and development and test cost of a detection system is saved, the use difficulty is reduced, and the use effect is excellent.

The invention discloses a pit detection method based on improved YOLOv3, and the method comprises the steps: S1, collecting a pit image through a visual collection system, and obtaining a pit data set after preprocessing, wherein the pit data set comprises a preprocessed pit image; S2, constructing an improved YOLOv3 pit detection network model; S3, inputting a training data set of the pit data set into the improved YOLOv3 pothole detection network model for training, and when the improved loss function approaches zero, obtaining a parameter optimal solution of the improved YOLOv3 pothole detection network model; and S4, inputting the pit data set into the improved YOLOv3 pit detection network model into which the parameter optimal solution is substituted to obtain a pit detection result. According to the invention, the problems that the real-time performance of pit detection needs to be guaranteed, and the accuracy needs to be further improved are solved.

The invention discloses a hardware-in-the-loop simulation test system for a vehicle-mounted computing unit of an automatic driving vehicle, which can shorten the debugging and iteration time of a real vehicle vehicle-mounted computing unit and solve the problems of low efficiency and high consumption of direct real vehicle test. The simulation test system can test a real vehicle-mounted computing unit suitable for a structured road driving environment, simulate all hardware equipment in an automatic driving system including sensor hardware, the vehicle-mounted computing unit, a drive-by-wire system and the like, and provide a whole set of automatic driving test environment for developers; manual/automatic driving switching and actual application effect evaluation of the vehicle-mounted calculation unit can be realized, the response capability of the real vehicle-mounted calculation unit to various conditions can be comprehensively tested, the problems of the real vehicle-mounted calculation unit can be positioned, and the development time of a vehicle automatic driving system is saved; and the feasibility and the stability of a data transmission format and a communication mode used in a real vehicle automatic driving system can be tested.

Using a vector-based emulation technique, a hardware-based prototyping system reduces time-consuming recompilation and reduces the iteration time for a verification run. The vector-based emulation technique takes advantage of information derived from user-defined probe points, automatically generated probe points and low-latency snapshots. Using a bounded-cycle simulation technique, the hardware-based prototyping system can provide complete or partial simulation traces covering interested signals and can efficiently evaluates assertions. A user is therefore able to debug in a real system test and to identify causes of fault conditions interactively under a controlled vector debugging environment.

The invention relates to a decision level prediction method, a storage device and a storage medium, and the method comprises the steps: determining a storage unit where storage data is located under the condition that the storage data is read from a memory; acquiring the state information of the storage unit at the current moment; and determining a read judgment level of the storage unit at the current moment according to a corresponding relation between historical state information and a historical optimal judgment level and the state information of the storage unit at the current moment. According to the method, the current read decision level is predicted by querying the historical information of the storage particles and combining the state information of the storage unit, and the RBER of read data is effectively reduced, so that the iteration time and the corresponding power consumption of an ECC decoder are reduced, and the service life of the whole SSD equipment is correspondingly prolonged. Furthermore, according to the method, the physical characteristics of the read judgment level of the storage unit are obtained in an online learning mode, offline testing of particles is not needed, the testing workload is saved, and the adaptability is better.

The invention provides a decision level prediction method, a storage medium and SSD (Solid State Disk) equipment. The method comprises the steps: when data reading is carried out, acquiring the use state information, the read data temperature and the write data temperature of a storage unit, wherein the read data temperature is the current temperature of the storage unit, and the write data temperature is the temperature of the storage unit when data is written; predicting a decision level of the storage unit according to the use state information; and determining a decision level compensation value according to the read data temperature and the write data temperature, and correcting the predicted decision level according to the decision level compensation value. According to the invention, the use state information of the storage unit in the temperature-crossing scene is calculated, and the optimal decision level is predicted based on the use state information, so an optimal judgment level is adopted for data reading during data reading, the RBER of read data caused by temperature-crossing reading and writing is effectively reduced, the iteration time and the corresponding power consumption of an ECC decoder are reduced, and the service life of the whole SSD equipment is prolonged.

The invention relates to a laser coherent array distributed phase control system and control method. The system comprises a laser coherent array output module and a distributed phase control module, wherein the distributed phase control module comprises a lenslet array, a plurality of secondary phase modulators, a plurality of optical fiber couplers, an optical fiber end cap, a plurality of photoelectric detectors, a primary phase control system and a secondary phase control system; a two-stage phase controller can effectively control wavefront information of array laser, and real-time control over the coherent combination effect of the array laser is achieved; and the optical fiber couplers perform pairwise coupling detection on the phase information of the array light beams without performing unified detection on the phase information of the whole array light beams, so that the phase control bandwidth of the system is improved. The laser coherent array distributed phase control system has the all-fiber feature, the pressure in the aspect of thermal management is reduced, and the compactness and operability of the system structure are improved.

The invention discloses a transformer fault diagnosis method based on CQFPA-WNN, and the method specifically comprises the steps: 1, collecting oil fault feature gas concentration data of an oil-immersed transformer, enabling the fault feature gas concentration data to serve as a total sample set, and dividing the total sample set into a training sample and a test sample; 2, performing normalization processing on the collected total sample set; 3, initializing a wavelet neural network and a cloud quantum flower pollination algorithm, and preparing for inputting wavelet neural network optimization parameters into a training sample; 4, optimizing wavelet neural network parameters by using the training sample and applying a flower pollination algorithm, and training the optimized wavelet neural network to obtain a diagnosis model; and 5, applying the test samples to a wavelet neural network transformer fault diagnosis model optimized based on a cloud operator flower pollination algorithm,and classifying the test samples to complete fault diagnosis. According to the method, the fault diagnosis speed and accuracy can be effectively improved.

A leaping iterative composition method of a complicated graphic and a storage medium having a computer program executing the same are described. First, an initiator and generators are set. After several times of iterating, a transitional object is formed. Then, a leaping recursion is performed based on this transitional object. When performing the leaping recursion, a generator of each of the iterations is designed by a single pattern converted from a structural result of a previous iteration added with a base object. Since the result of each of the iterations keeps the original structure, the structure is used as the input initiator. The initiator of the first iteration can be a feature of different iteration objects. Since the input structure of iterations are the same, the advantage of reducing computing resources and avoid system overload are reachable.

The invention provides a data iteration method and device. The method comprises the steps that when iteration of a data unit in a data file is conducted, meta information corresponding to the data unit is accessed, and a version number of the meta information is obtained; a name of the data unit and the version number of the meta information are combined, and based on the combination, a traversalquery is conducted on the data unit in the data file, wherein the version number of the data unit is included in a name field of the data unit in the data file. According to the data iteration method,a needed data unit can be rapidly found without needing to firstly conduct traversal query on data units with the highest ranking, data iteration time is saved, and rapid iteration can be conducted even after instant deleting.

The invention discloses a module rapid placement and adjustment method. The method comprises the steps of S1, obtaining input data; Wherein the input data comprises basic data of each storage unit aswell as interval height and interval width required to be spaced by each storage unit; Wherein the basic data of the storage unit comprises storage unit position coordinates, a storage unit height anda storage unit width; S2, obtaining the positions corresponding to the modules through calculation; And S3, according to the position information of the modules obtained through calculation, placingthe modules. According to the module rapid placement and adjustment method provided by the invention, the distance between the storage units can be rapidly adjusted, the adjustment speed of hundreds of storage units is within the second magnitude, the speed is greatly increased, and the iteration time of a project is reduced.

The invention relates to the field of system performance monitoring, and discloses an application performance monitoring tool based on pinpoint so as to intelligently analyze performance data and automatically position a performance bottleneck. According to the invention, secondary development is carried out on the basis of a third-party open source tool pinpoint; data reported by a probe program are received through a collector program in a manner of injecting, for a Java application program, bytecode into a probe, affairs, application topographies, JVMs and other types of data are analyzed and stored, and finally a corresponding performance monitoring report is generated through the performance bottleneck analysis module, so that research personnel, test personnel and operation and maintenance personnel can know and solve system performance problems and bottlenecks in time. The method is suitable for application performance monitoring.

The embodiment of the invention discloses an online detection method for the surface shape of a reflector. On the basis of the principle of stripe reflection, a stripe image with ideal periodic changeis displayed through a display, a stripe image formed by the reflection of a reflector machined by an ultra-precision cutting machine is collected through an aperture camera, the surface shape of thereflector is judged and reconstructed according to the curvature of the stripe image, and thus, online detection of the surface shape of the reflector is completed. By using the online detection method for the surface shape of a reflector provided by the embodiment of the invention, a reflector with any smooth continuous surface shape can be detected without optical compensation device or precision position adjustment. The method has a greater dynamic range than the existing online detection method based on a laser interference detector, and takes shorter time and is less affected by the precision of the machine tool and the environmental conditions than the existing online detection method based on point-by-point ranging and scanning by a contact or non-contact sensor.

The invention discloses a moving target tracking and positioning method based on a single camera, and the method comprises the following steps: S1, carrying out the extraction of a moving target, carrying out the image collection of the moving target through the single camera, and the color space of a collected image being an RGB space; S2, identifying a moving object, specifically realizing the identification of the moving object through a digital image processing method; and S3, tracking and positioning the moving target, detecting the edge of the moving target through a Camshift algorithm and a neighborhood linear search method, and determining the relationship with the surrounding environment so as to carry out positioning processing. Compared with a traditional target tracking and positioning method, the iteration time of the tracking operation is reduced in the tracking time, the phenomena of frame loss and sudden change of the position of the moving target between two adjacent frames of collected images caused by the precision of the camera are effectively solved, and the method has the advantages of accurate tracking and positioning, high applicability, time saving and simple and convenient process.

The invention discloses an optical flow field calculation method. According to the method, current new iteration values of light streams in a lower neighborhood and a left neighborhood of a pixel point are already obtained when a light stream mean value of the pixel point is calculated through a four-neighborhood template, so that current iteration light streams of the pixel point can be obtained with the new value according to the calculated light stream mean value during calculation of the light stream mean value of the point. Through adoption of the method, errors are small, and the convergence speed of an algorithm is increased. The method is particularly suitable for situations with a large quantity of boundaries and large boundary gray scale gradients; the iteration times can be reduced greatly; and the iteration time is shortened. Compared with a conventional differential method, the method has the advantages of very high robustness, great shortening of the optical flow field calculation time, and high efficiency.