153results about How to "Achieve automatic optimization" patented technology

The invention relates to a method for network coverage optimization processing, which comprises the steps: in step S102, collecting first coverage optimization data related to a local party and secondcoverage optimization data related to other base stations by a base station, judging whether coverage optimization is carried out or not in the local party according to a predetermined decision rule,if so, carrying out step S104, or else, carrying out step S106 and step S108, in step S104, if so, carrying out adjustment by the base station according to a first predetermined coverage optimizationrule, in step S106, or else processing the first coverage optimization data and the second coverage optimization data, reporting the data to a network administration node, determining an adjusting result by the network administration node according to local configuration data, the first coverage optimization data, the second coverage optimization data and a second predetermined coverage optimization rule, informing the base station and/or other base stations of the adjusting result, and in step S108, carrying out corresponding adjustment by the base station and/or other stations according tothe adjusting result. In addition, the invention also discloses a system for network coverage optimization processing.

The invention discloses an electronic file storage structure of mobile terminal equipment and a management method, belonging to a field for wireless mode management file of mobile terminal equipment. Currently file managing and storing mode of computers are not suitable for mobile terminal equipment and not compatible. So the invention adopts a series of software and hardware technology, converts through material format, fills memory area block, fills data bits, produces catalogue and label, fills copyright data, compresses file data and encrypts electronic content before encrypted target file UMD file comprising original data, index structure and copyright information compression is finally generated; the file is copied to the mobile terminal and edit interface is arranged at terminal of users. The invention has the advantages of simple structure, less operative steps, high compatibility, flexibility, safety and expansibility.

Embodiments of the invention provide neighbor relation optimization methods and a device. One of the neighbor relation optimization methods comprises determing neighbor regions to be processed through centralized equipment according to a default rule, generating optimization suggestion according to the determined neighbors, and issuing the optimization suggestion to a radio network controller (RNC) so that the RNC performs optimization on the processed neighbors according to the optimization suggestion. The embodiments of the invention realize an automatic neighbor relation.

The invention provides a vehicle gear shift control method and device. A gear shift parameter corresponding to each gear shift mode is taken as a character value, a membership degree value of each gear shift mode is calculated with a neural network algorithm, weight occupied by each gear shift mode in a current work condition is calculated, and after each gear shift speed in each gear shift mode under the current work condition is determined, the optimal gear shift speed under the current work condition is calculated according to the weight occupied by each gear shift mode in the current work condition and each gear shift speed in each gear shift mode under the current work condition, so that the gear shift speed is automatically optimized. The invention provides a flexible and variable gear shift strategy. The gear shift strategy can be timely adjusted according to the current vehicle condition, the driving state and the road condition change, so that a gear shift wire of a vehicle is more reasonable, and the driving experience of a driver is enhanced.

The invention discloses a method, a system and equipment for optimizing cell reference symbols. The method comprises the following steps that: a network node receives a measurement event from UE; the network node determines the information of the UE according to the measurement event; and the network node optimizes the cell reference symbols of the UE according to the information of the UE. The coverage condition of the cell reference symbols is acquired by using the measurement event of the UE, and the cell reference symbols are optimized and the transmitting power of the cell reference symbols is adjusted according to the coverage condition so as to fulfill the purpose of automatically optimizing the cell reference symbols; and the cell reference symbols can be accurately optimized without modifying a protocol.

The application provides a method and system for sorting search. The method comprises following steps: obtaining a search word and obtaining texts matched with the search word by means of static sorting index, wherein the obtained texts are used as mass-selection recall texts; obtaining rough sorting feature weight by fitting the pre-counted fine sorting score of the mass-selection recall texts by means of the machine learning method, and calculating the rough sorting score of the mass-selection recall texts by means of the rough sorting feature weight; selecting first M texts which are sorted at front according to the rough sorting score, wherein the selected texts are used as rough sorting texts; calculating the user behavior probability of the rough sorting texts corresponding to the search word and calculating the fine sorting score of the rough sorting texts by means of the machine learning method using the user behavior probability; sorting the rough sorting texts according to the fine sorting score. The application can increase search quality and improve the user search experience.

The invention relates to a breakout prediction method for continuous casting, belongs to the technical field of metallurgical continuous casting, and in particular relates to a breakout prediction method in plate blank continuous casting process. In terms of temperature monitoring-based breakout prediction algorithm, the self-adapting genetic algorithm is introduced into the BP (Back Propagation) neural network to achieve automatic optimization of the network structure and improve identification accuracy of a temperature monitoring model. In terms of friction monitoring-based breakout prediction algorithm, a friction monitoring model based on logical decision and neural network is established. Based on the prediction results of the two models, the method achieves combination of temperature monitoring accuracy and friction monitoring sensitivity, provides the prediction mechanism based on temperature monitoring in addition with friction monitoring and couples the temperature monitoring model to the friction monitoring model, so as to ensure the accuracy of final prediction and effectively reduce the false prediction rate.

The invention discloses a method and a device for optimizing a multidimensional cube model. The method for optimizing a multidimensional cube model comprises the following steps: building an all-dimension multidimensional cube model based on a dimension set, wherein the dimension set includes all data dimensions in a service model; updating the dimension set based on acquired user behavior data and according to preset updating rules; and regenerating a multidimensional cube model according to the updated dimension set. According to the technical scheme of the invention, the dimension set is updated based on the acquired user behavior data, and then, a multidimensional cube is regenerated. The problem that the updating of a multidimensional cube at present requires a large amount of calculation and depends on the experience of the designer is solved. A multidimensional cube can be updated automatically. Updating of the dimension set based on the operation data in a database is closer to the actual need of users. Thus, the updated multidimensional cube model is smarter and more practical.

The invention discloses a machine vision cutting method applied to a laser cutting machine. The machine vision cutting method comprises an image distortion correction module, an image contour recognition module, a parameter optimization module based on supervised machine learning and a cutting path generation module; the image distortion correction module processes an acquired image to obtain an original image; the image contour recognition module performs contour recognition on the original image; the cutting path generation module generates a cutting path of the laser cutting machine according to a contour recognition result; and the parameter optimization module based on the supervised machine learning optimizes the image contour recognition module, so that the recognition contour extraction of the image contour recognition module is more accurate. The method of the invention has the advantages of being easy to operate, high in recognition precision, high in recognition speed and the like, can be adapted to a complex production environment, and improves the generality of the laser cutting machine.

The present invention relates to the mobile communication field, and provides a mobile terminal mode switching method. The method comprises accessing into a wireless fidelity WIFI network through an access point AP, acquiring a media access control MAC address of the AP, and switching a scene mode of a mobile terminal to a scene mode corresponding to the MAC address according to the acquired MAC address. A mobile terminal used for realizing the above method is also provided. According to the method, according to the MAC address of the current network access point AP of the mobile terminal, an application environment of the mobile terminal is judged, and corresponding scene mode switching is performed, thereby adapting to the current environment, realizing automatic optimization of user parameters, and improving user experience.

The invention provides an automatic and moderate orthographic projection correction method of a satellite remote sensing image. The method is formed by the organic combination of control point automatic match, control point automatic optimization, control point gross error automatic detection, correction model moderate solving and the like. The method solves the problem that the control points in the control point automatic selection are not uniformly distributed and the problems of detecting control point observed value gross error and improving model solving precision. As the method has the advantages of moderation, precision and high degree of automation, the method is suitable for the production of orthographic projection correction products of the satellite remote sensing image on a large scale.

The invention relates to a cold load prediction method based on support vector machine parameters optimized with the cat swarm algorithm. The method includes the following steps: (1) selecting prediction features of a cold load, (2) pre-processing historical data of the cold load, (3) analyzing the historical data of the cold load, (4) automatically optimizing the support vector machine parameters with the cat swarm algorithm, and (5) performing cold load prediction with an optimized support vector machine. The parameters of the support vector machine are optimized through the local searching capability and the global searching capability possessed by the cat swarm algorithm, so that the prediction capability of the support vector machine is promoted, and the effect of promoting prediction accuracy is achieved. Due to the cat swarm algorithm is applied to the optimization process of the support vector machine parameters, automatic optimization of the support vector machine parameters is achieved, and finally the prediction accuracy of the cold load prediction is promoted. The cold load prediction method based on the support vector machine parameters optimized with the cat swarm algorithm is high in practicality and strong in popularization capacity.

The invention provides a RACH self-optimization method, a device, a system and a base station for a LTE system. Access parameter configuration is checked during the starting procedure of the base station; conflict checking and processing are performed on access parameter configuration of adjacent base stations during the operation process of the base station; adaptive adjusting is performed on each PRACH configuration parameter based on the start-up status of an optimization switch which performs adaptive adjusting corresponding to each PRACH configuration parameter during the process of normal access to user terminals; and therefore RACH automatic optimization is realized according to continuously changing network situation.

The invention relates to a data processing method and device and a computer readable storage medium, and relates to the technical field of computers. The method comprises the steps of determining a to-be-trained machine learning model and a corresponding first hyper-parameter search space according to-be-processed data; sampling candidate hyper-parameters in the first hyper-parameter search space;training a to-be-trained machine learning model by utilizing the first training data set according to the candidate hyper-parameters; re-sampling the candidate hyper-parameters, and repeating the training process according to the re-sampled candidate hyper-parameters until the trained to-be-trained machine learning model meets an iterative stop condition, so as to obtain a trained machine learning model; and processing the to-be-processed data by utilizing the trained machine learning model and the corresponding candidate hyper-parameters.

The invention discloses an evolutionary digital twinborn drainage basin construction method, which comprises the following steps of S1, constructing an initial digital twinborn drainage basin based on related parameters of a drainage basin, meteorological data, hydrological data, soil data, topographic data and hydraulic engineering data; and S2, optimizing and verifying the model in the initial digital twinborn drainage basin, and performing digital twinborn integration when an iterative optimization condition is met to obtain a final digital twinborn drainage basin. The method has the advantages that the twinborn technology is applied to drainage basin construction, the targets of intelligent management, perceptual analysis, analogue simulation, automatic optimization, real-time updating and reasonable prediction are achieved, and meanwhile the requirement for combination of digitization and intelligentization is met. Technical support can be provided for follow-up high-precision hydrological forecasting, flood control dispatching and simulation prediction.