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838results about How to "Reduce memory consumption" patented technology

Multi-scale seismic full-waveform inversion method based on local adaptive convexification method

The invention relates to a multi-scale seismic full-waveform inversion method based on a local adaptive convexification method. The method comprises steps: pre-processing is carried out, a zero value sequence serves as an initial value, and an initial speed model serves as a starting value; direct wave information is intercepted; forward modeling direct waves are obtained; an objective function inverted by a seismic source function is built; a direct wave residual and a direct wave residual back propagation wave field are obtained; an updating gradient and an updating direction of the seismic source function are calculated, and a step length is searched; the high-precision seismic source function obtained through inversion is outputted; attenuation time window processing is carried out; seismic data in the time window are simulated; local convexification processing and separation processing are carried out; a high-frequency component in an observation record is removed; a least square objective function is built, and a wave field residual is obtained; a residual back propagation wave field of the model space is obtained; the model updated gradient is obtained; the model updated direction is calculated, and the step length is searched; a multi-scale seismic full-waveform inversion result is outputted; and a final inversion result is outputted. The method is widely applied in the technical field of seismic exploration.
Owner:CHINA NAT OFFSHORE OIL CORP +1

Novel INS (inertial navigation system)/ GPS (global position system) combined position and orientation method

The invention provides a novel INS (inertial navigation system) / GPS (global position system) combined position and orientation method. The novel INS / GPS combined position and orientation method includes adopting a linear Kalman filter to perform filtering estimation to GPS original measurement data, and outputting optimal GPS navigation estimation value; according to the optimal position estimation value, providing initial position information to the INS, according to the optimal speed estimation value, providing initial speed information to the INS and solving INS initial measuring data to acquire INS navigation information; adopting a dynamic error model to establish a 9-order extended Kalman filter, integrating the INS navigation information with an optimal GPS navigation estimation value, performing feedback rectification to all INS navigation information at the same moment, and outputting optimal position data and orientation data after rectification and integration. The novel INS / GPS combined position and orientation method has such advantages as high precision, fast data processing speed and low hardware requirement and is applicable to low-cost INS / GPS combined position and orientation plan.
Owner:CHINA UNIV OF GEOSCIENCES (BEIJING)

Vehicle model identification method based on pooling multi-scale depth convolution characteristics

The invention discloses a vehicle model identification method based on pooling multi-scale depth convolution characteristics, comprising the following steps: extracting the depth convolution characteristic of each vehicle model image in a vehicle model database according to different scales, wherein the first scale is not processed; carrying out PCA dimension reduction of the depth convolution characteristics of the remaining scales; carrying out coding using a local characteristic aggregation descriptor; carrying out PCA dimension reduction again to get the characteristic representation of the current scale; cascade-pooling the characteristics of all the scales to get the final characteristic representation of the current image; training a linear support vector machine using the characteristic representation of the vehicle model images to get a vehicle model identification system; and for a vehicle to be identified, acquiring the characteristic representation of the vehicle, and importing the vehicle into the identification system to identify the model of the vehicle. The traditional depth convolution characteristic lacks of geometrical invariability, which limits vehicle model image classification and identification in a variable scenario. The problem is well solved by using pooling multi-scale depth convolution characteristics of images. The vehicle model identification method of the invention is of high practicability and robustness.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Data collection and control system for target tracking segmented power supply street lamp

The invention discloses a data collection and control system for a target tracking segmented power supply street lamp. The data collection and control system comprises an LCD (liquid crystal display) interface, a serial printer interface, a keyboard interface, a microprocessor, an external storage module, an internal storage module, a clock synchronization module, a GPRS (general packet radio service) module, a wireless ratio frequency communication module or an electric carrier communication module, wherein the LCD interface and the serial printer interface are connected with the microprocessor through a serial port expansion module, the wireless radio communication module or the electric carrier communication module is connected with the target tracking segmented power supply street lamp system, the GPRS module is connected with a remote street lamp management center, and the system adopts the real-time management data structure and the roll polling algorithm for realizing the state roll polling. The system can automatically collect the real-time data of the street lamp system, and can realize the automatic statistics analysis, high-speed large-volume storage and street lamp control, the real-time work state can be mastered in real time, and the operation fault can be found. The street lamps are organized and managed in different segments, the data collection and control system adapts to the duplex requirements of traffic management, energy saving and environment protection, and the management efficiency of an illumination system is improved.
Owner:HOHAI UNIV CHANGZHOU

Method for acquiring addresses of network video programs

InactiveCN101635826ASolve the problem that it is difficult to get the address from the pageTroubleshooting automated address discoveryPulse modulation television signal transmissionTwo-way working systemsVideo playerNetwork addressing
The invention relates to the technical field of network communication, and provides a method for acquiring addresses of network video programs. The method comprises the following steps that: a browser is used to open a plurality of webpages having audio and video programs and a player is ready to play the programs; the player requests the webpages from a remote video server, the player acquires the network address of the request video source according to the parameters transferred by the webpages, and the data source is remotely read and played; and the interactive information between the player and the remote video server are acquired and then analyzed so as to acquire the addresses of the network audio and video programs. Because the mode of combining the browser control and the network address monitoring is utilized to find the network audio and video addresses, and the browser is used for judging whether the webpages include the audio and video player and can control the playing of the player, the problems that the audio and video webpage scripts are complex and that the FLV is difficult to acquire the addresses from the webpages are solved.
Owner:上海星地通讯工程研究所

Finite state machine actuating device and method, and method for establishing and using finite state machine

The invention discloses a finite state machine actuating device and method, and a method for establishing and using a finite state machine. The finite state machine actuating method comprises the following steps of: receiving a trigger event; acquiring the current state of the finite state machine and acquiring a next state to which a current state is to be shifted according to an input event and a state shifting table; and determining a specific state type which corresponds to the current state from one or more specific state types belonging to a basic state type according to the basic state type, performing predetermined processing by using the specific state type and updating the current state by using the acquired next state. By adopting the method, actuating logic of the finite state machine is improved in combination with the principle of an object-oriented state mode and a Flyweight mode, the specific state type of a single example mode is established, and repeated creation and deletion of an object are avoided, so that resource consumption of a system can be lowered on various application developing and modeling occasions and the like, and the actuating speed and efficiency of the application are improved.
Owner:ALCATEL LUCENT SAS

Network intrusion detection method

The invention discloses a network intrusion detection method. The network intrusion detection method includes: searching network data to construct a test network data set; performing feature extraction on the test network data set by utilizing a kernel principal component analysis method; constructing a training data set, putting the training data set into a support vector machine classifier for training; obtaining feature datasets, obtaining an optimal feature subset from the feature data set by using a genetic algorithm; utilizing a firefly swarm optimization algorithm to obtain the overalllocal optimal feature subset and the optimal support vector machine parameters from the optimal feature subset, processing the training data set according to the overall local optimal feature subset,and inputting the training data set into a support vector machine classifier for classification modeling to obtain a network intrusion detection model. According to the method, the simplicity and convenience of the algorithm are improved, abnormal data can be more effectively found from samples, the detection accuracy of network intrusion is effectively improved, the missing report rate and the false report rate are reduced, and the overall performance of network intrusion detection is improved.
Owner:SHANGHAI MARITIME UNIVERSITY
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