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272results about How to "Shorten study time" patented technology

Method for improved repeatable runout learning in a disk drive

A method is disclosed for adaptive learning of fundamental-frequency repeatable runout (1FRRO) compensation information in a disk drive. The disk drive includes a transducer head, a magnetic disk having a plurality of concentric data tracks defined by embedded servo wedges that provide position information, and a control system. In the method, 1FRRO compensation information is learned over a predetermined minimum number of disk revolutions. After the predetermined minimum number of disk revolutions, the 1FRRO compensation information is monitored for convergence while learning of the 1FRRO compensation information continues. Learning is terminated upon detection of convergence of the 1FRRO compensation information.
Owner:WESTERN DIGITAL TECH INC

Device and method for carrying out subject training based on virtual reality

The invention provides a device and method for carrying out subject training based on virtual reality. The device is realized through the following components: a virtual reality driving module for simulating a real car for a user to carry out simulated driving and subject training, a subject training module for splitting the subject training into a certain quantity of single trainings, a point position teaching module for teaching a student through a passing method of each subject and calling a pre-stored key operating instruction at a key point, and a scoring module for scoring a driving process of the user according to a subject examination scoring rule and judging whether a subject examination passes or not. The device and method, provided by the invention, have the beneficial effects that point positions are clear and the method is clear; the burdens of the students and trainers are reduced through a plurality of types of repeated learning, and contradictions between the students and the trainers are avoided; the learning time of the students in real cars on site is shortened and the operation cost of driver training schools and the trainers is greatly reduced; the subject is split into a plurality of single courses and each single course is split into a plurality of courses, so that the school effect of the students is improved.
Owner:珠海超凡视界科技有限公司

Real-time limit learning machine short-time traffic flow prediction method based on fusion

The invention discloses a real-time limit learning machine short-time traffic flow prediction method based on fusion. The method, for prediction technology in short-time unstable traffic flow scene, predicts short-time traffic flow on the basis of the realtimeness, the accuracy, and the reliability of short-time traffic flow and a fused real-time limit learning machine. The short-time traffic flow prediction method is based on a simplified single-implicit-strata feedforward neural network structure, may fast train historical data at a traffic flow peak value and updates reached data in an increment way, and saves learning time while guaranteeing certain prediction precision. Further, the method guarantees the stability and the robustness of short-time traffic flow prediction by using a fusing mechanism, performs reconstruction during a data missing and violent fluctuation period, and is short in training time. The root mean square error and the standard error percentage of a prediction result are both in a confidence region.
Owner:湖南湘江智慧科技股份有限公司

Path planning obstacle avoidance control method for autonomous underwater vehicle in large-scale continuous obstacle environment

ActiveCN112241176AFast convergenceReal-time obstacle avoidance capabilityAltitude or depth controlComputer control systemModular design
The invention relates to a path planning obstacle avoidance control method for an autonomous underwater vehicle in a large-scale continuous obstacle environment. The invention relates to the technicalfield of underwater robot path obstacle avoidance planning, and the method comprises the steps: building a large-scale continuous obstacle simulation training environment, building the state and action of a deep reinforcement learning neural network through employing obstacle avoidance sensor information as the input and the navigation speed and yaw angular speed as the output, for a multi-targetstructure of a motion planning obstacle avoidance control process, performing modular design on a reward function, and in order to avoid system instability caused by sparse rewards, setting continuous rewards are set in combination with an artificial potential field method. According to the method, obstacle avoidance training is carried out on the autonomous underwater vehicle by utilizing an improved depth deterministic strategy gradient algorithm, and an obstacle avoidance strategy obtained by training is written into a robot lower computer control system; when the autonomous underwater vehicle runs in an underwater canyon, obstacle avoidance is carried out by using an obstacle avoidance strategy learned by training, and the autonomous underwater vehicle safely reaches a target area.
Owner:HARBIN ENG UNIV

Deformation prediction method and apparatus based on Kalman filtering and BP neural network

The invention provides a deformation prediction method and apparatus based on Kalman filtering and a BP neural network, wherein the deformation prediction method based on the Kalman filtering and the BP neural network comprises: obtaining the deformation monitoring data of a monitored object in a project as a training sample; establishing a BP neural network topology model according to the training sample; learning the BP neural network topology model by using a Kalman filtering algorithm according to preset training parameters to adjust the weights of the neurons in the BP neural network topology model; and performing deformation prediction according to the BP neural network topology model with adjusted weights. The deformation prediction method based on Kalman filtering and a BP neural network can shorten the learning time of the BP neural network and improve the establishment efficiency of deformation prediction model in a deformation prediction process.
Owner:PETROCHINA CO LTD

Machine room environmental data management and real-time analyzing and processing system

The invention belongs to the technical field of computer automation application, and particularly provides a machine room environmental data management and real-time analyzing and processing system. The system comprises a browser side OCX control and a server side. The system is a multilevel distributed computer monitoring network structurally. The whole monitoring system is composed of three parts: a monitoring center, a monitoring unit and a remote IE browsing station. The monitoring objects are power equipment and machine room environment in a communication machine room, and functions of real-time remote measurement, remote signaling, remote control and remote regulation of the machine room-power and machine room environment can be realized. Meanwhile, functions of automatic prompt alarm, display and printing of alarm information, alarm or fault classified statistics, fault repair dispatching and fault sheet management, automatic repair assistance and automatic repetition measurement and fault elimination can also be provided. The monitoring system has positive promotion effect in fully utilization of manpower resource, strengthening and maintenance of construction of support means, guaranteeing of equipment stable operation and machine room safety, enhancement of labor productivity and network maintenance level, realization of unattended operation from attended operation of the machine room and promotion of modernization of power supply equipment maintenance.
Owner:上海卓佑计算机技术有限公司

Automatic three-dimensional model component category tagging method

The invention discloses an automatic three-dimensional model component category tagging method. The method comprises the following steps that in the training process, quick training is conducted according to a three-dimensional model tagging training set, and a quick tagging model used for classifying and tagging surface patches and mesh edges of an unknown three-dimensional model is obtained through training; in the tagging process, the quick tagging model, obtained through training, of the surface patches and mesh edges is utilized for classifying surface patches and mesh edges of a target model, classification probability distribution of the surface patches and mesh edges is obtained, a graph model is constructed, smoothing and optimizing of segmentation boundaries are conducted through multi-tag graph cut optimization, and therefore rapid automatic target three-dimensional model component category tagging is achieved.
Owner:NANJING UNIV

Three-decision unbalanced data oversampling method based on Spark big data platform

The invention discloses a three-decision unbalanced data oversampling method based on a Spark big data platform, and relates to a Spark big data technology in the field of data excavation. The method comprises the following steps: firstly, carrying out data transformation with an RDD (Resilient Distributed Dataset) of Spark to obtain a normalized sample set with the LabeledPoint format <label: [features]>, and dividing the sample set into a training set and a test set; secondly, carrying out data variation by adopting the RDD of Spark, calculating a distance between samples, determining the radius of a domain, and classifying the samples in the whole training set into positive domain samples, boundary domain samples and negative domain samples according to a neighborhood three-decision model; then respectively oversampling the boundary domain samples and the negative domain samples; and finally, calling a Spark Mllib machine learning algorithm to verify a sampling result. According to the three-decision unbalanced data oversampling method based on the Spark big data platform, the problem of classification of a large-scale unbalanced data set in the field of machine learning and mode recognition is effectively solved.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

Intelligent key learning method and intelligent key learning system

The embodiments of the present invention provide an intelligent key learning method and an intelligent key learning system, and relate to the technical field of vehicle keys. The intelligent key learning method is used for the intelligent key learning system. The intelligent key learning system comprises an offline diagnosis electric inspection device and a vehicle to be learned, wherein the offline diagnosis electric inspection device and the vehicle to be learned form communication connection. The intelligent key learning method comprises that the offline diagnosis electric inspection deviceacquires an identification code corresponding to a target intelligent key according to a learning starting command; the identification code is identified so as to acquire the feature data of the target intelligent key; and the feature data of the target intelligent key is stored in a vehicle to be learned so as to complete the learning on the target intelligent key by the vehicle to be learned. According to the present invention, with the method and the system, the activation of the intelligent key is not required during the intelligent key learning, such that the learning time is reduced, the radio interference during the learning is avoided, and the learning efficiency is improved.
Owner:NINGBO YUANJING AUTO PARTS +1

Intelligent teaching analogue system for acupuncture and moxibustion

The intelligent teaching system for simulative acupuncture and moxibustion consists of body's acupoint model, acupoint sensors, signal amplifying follower circuit, acupoint matrix keyboard circuit, matrix keyboard expanding circuit, CPU, terminal PC and control software. It features that each of the acupoint sensors is provided with three layers of conducting film corresponding to three states of 'contact acupoint', 'Diqi' and 'offsetting acupoint' separately, and that matrix keyboard circuit and CPU scanning matrix keyboard circuit are constituted to detect the state signal of the sensors, judge which acupoint to have acupuncture and moxibustion and control the terminal PC. The present invention makes the teaching of acupuncture and moxibustion intuitive and may be used widely in the teaching.
Owner:JIANGSU YUYUE MEDICAL EQUIP&SUPPLY CO LTD

Short-term photovoltaic power generation prediction method considering correlation degree of weather and meteorological factors

The invention discloses a short-term photovoltaic power generation prediction method considering the correlation degree of weather and meteorological factors. The method comprises the following steps:1, rejecting bad data through an iForest algorithm; 2, respectively calculating Pearson correlation coefficients R of the photovoltaic power generation power and the five meteorological factors underfour weather types, and normalizing the Pearson correlation coefficients R; 3, performing fuzzy clustering on the five meteorological factors of the to-be-measured day, and obtaining a correlation coefficient of the historical day and the to-be-measured day; 4, a correlation coefficient normalization value is introduced, and the correlation degree between a historical day and a to-be-measured dayis solved; and 5, taking the historical day with high correlation degree as historical data, inputting the historical data and the meteorological factors of the day to be measured into the improved ACO-BP neural network, and finally obtaining a predicted value of the solar photovoltaic power generation to be measured; and 6, determining a neural network correlation coefficient, and performing simulation. The method aims to improve the photovoltaic power generation prediction precision, improves the practicality of a prediction model, and plays a great role in the combination of scheduling andprediction.
Owner:YANSHAN UNIV
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