219 results about "Attenuation function" patented technology

The invention discloses a traffic network toughness diagnosis method under flood disasters based on a space-time diagram neural network, and relates to the crossing field of traffic engineering and artificial intelligence. The method comprises the following steps: collecting traffic topology, flood monitoring and traffic flow data, and carrying out space-time alignment; a flood coupling dynamic space-time diagram is constructed, a water depth-traffic capacity response mechanism is introduced, and real-time mapping from a disaster physical state to a network topology is realized by utilizing an attenuation function meeting physical monotonicity constraint and dynamically updating an edge weight of a diagram structure according to real-time water depth; inputting the dynamic graph into a pre-trained space-time graph neural network model, extracting space-time evolution characteristics and outputting a toughness diagnosis result; model training adopts a toughness label generated based on an anti-fact baseline to carry out supervised learning, and introduces a physical constraint loss function. According to the method, the problems of decoupling of disaster features and graph structures and unavailability of toughness labels in the prior art are solved, and the physical consistency and accuracy of diagnosis are improved.

The invention relates to the technical field of electroencephalogram signal processing, and provides a brain-computer AI glasses electroencephalogram signal multi-dimensional quality dynamic detection method, which comprises the following steps: preprocessing collected electroencephalogram signals; performing task frequency band component analysis on the channel signals subjected to the matrix rank analysis, and calculating a power proportion of a target frequency band; performing maximum gradient analysis on the channel signal, and calculating the maximum gradient value of the channel signal; performing root-mean-square analysis on the channel signal, and calculating a root-mean-square value of the channel signal; performing fluctuation amplitude analysis on the channel signal, and calculating a peak-to-peak value of the channel signal; performing brain hemisphere symmetry analysis on the left and right homologous channel signals, calculating the correlation and mean square error of the channel signals, and setting a dynamic threshold according to the frequency band of the channel signals; obtaining an electrode impedance value, and mapping the electrode impedance value into an impedance score through a preset exponential attenuation function; the final quality score of the channel is obtained, and dynamic detection and real-time score updating of the electroencephalogram signal quality are achieved.

The invention discloses a bidirectional grid-connected control system for a small-power energy storage inverter, and relates to the technical field of inverter grid-connected control. Aiming at the needs of the small-power energy storage inverter in a restricted scattering environment, a communication and control scheme is proposed, a channel attenuation matrix and an interference feature list are generated by measuring point layout and a multi-factor attenuation function, and a channel environment model is formed by nonlinear fitting; a multi-node multi-band communication topology is constructed and feasible routes are screened, the optimal or alternative combination is dynamically solved and the network topology configuration is output; multi-dimensional scoring and multi-path capacity allocation are performed on data streams with different sensitivities, and high-priority data is preferentially scheduled to a better route; when the network abnormality cannot be restored, the local buffering and offline control algorithm can calculate the inverter operating parameters based on the cached data and perform load reduction protection, and smoothly switch back to the online mode after the network is restored, so as to ensure that the energy storage inverter is still safe and controllable in the disconnected state.

The invention discloses a physical-data dual-drive retaining wall catastrophe robustness evaluation method, and relates to the technical field of structure catastrophe evaluation and computer science crossing. Aiming at the problems that an existing retaining wall catastrophe robustness evaluation method cannot correct physical model errors in real time and is insufficient in accuracy, the invention provides a retaining wall catastrophe process robustness evaluation method driven by fusion of a physical model and a neural network. The method comprises the following steps: 1, carrying out time discretization and parameter vectorization on retaining wall catastrophe monitoring parameters; 2, constructing a performance attenuation function based on the physical model; 3, updating an implicit damage state in combination with a neural network Cell module; 4, correcting an error through a feedforward network to obtain a total performance attenuation function; and 5, finally calculating a robustness index and outputting a corresponding robustness grade, thereby realizing quantitative evaluation of the retaining wall catastrophe robustness. Reliable quantitative support can be provided for retaining wall design optimization, operation monitoring and post-disaster recovery evaluation.

The invention relates to the field of robot navigation, and particularly discloses a spatial perception observation information quality evaluation method and system, a terminal and a medium, and the method comprises the steps: converting the measurement information of each dimension into a normalization probability according to the measurement target of each dimension; according to the concept of entropy in the information theory, the normalized probability of each dimension is converted into a computable entropy value; a downstream task weight coefficient is introduced for the entropy value of each dimension, the multi-dimensional entropy value after the downstream task weight coefficient is introduced is mapped into a physical interpretable confidence coefficient in a [0, 1] interval through an exponential attenuation function, and the confidence coefficient explicitly represents the uncertainty of observation information of each dimension. According to the method, a space perception quality evaluation system with mathematics interpretability, scene adaptation and real-time calculation is formed, multi-source uncertainty is mapped into executable confidence, and multi-dimensional accurate evaluation of intelligent agent space perception observation information is achieved.

The invention relates to the technical field of medical diagnosis, in particular to an eye white image acquisition and disease auxiliary diagnosis method and device, and the method comprises the steps: obtaining a video frame collected by a camera in real time, obtaining eye socket detection frame information in the video frame through a target detection algorithm, and adjusting the three-axis displacement of a motor to be positioned to an eye socket based on the eye socket detection frame information. The method comprises the following steps: completing image acquisition of eye white area maps in five directions, automatically marking abnormal parts, establishing a dynamic coordinate system and a mapping area which take a pupil center as a pole, calculating polar radius and polar angle of polar coordinate parameters, calculating a spatial weight value of mapping abnormity through a distance attenuation function, calculating a comprehensive gain value of the mapping area, and normalizing the comprehensive gain value. Generating an eye white abnormity thermodynamic diagram and performing hierarchical display; according to the invention, eye sockets are automatically positioned, eye white area maps in five directions are adaptively acquired, hierarchical display of eye white abnormity thermodynamic diagrams is realized, batch acquisition of eye white images of patients is satisfied, diagnosis efficiency is improved, and doctors are assisted to complete disease diagnosis.

The invention discloses a well mining unmanned driving fault data processing method and system, and relates to unmanned driving. The method comprises the following steps: obtaining multi-source heterogeneous data; performing space-time fusion processing on the multi-source heterogeneous data to obtain a fused data set; inputting the fused data set into a pre-trained LSTM-Attention prediction model, and outputting a fault probability prediction value of the unmanned vehicle; calculating a fault risk score according to the fault probability prediction value in combination with the fault influence level; according to the fault risk score, triggering a preset fault processing mechanism of a corresponding level; aiming at the problem that the influence of water mist spraying on equipment operation is not considered in traditional well industrial and mining unmanned driving fault prediction, the method introduces UWB positioning-based vehicle and spraying point distance calculation, adopts a Gaussian distance attenuation function to quantify a spraying influence weight, constructs a temperature compensation factor alpha fused with a spatial distance and a time accumulation effect, and performs fault prediction on equipment operation according to the temperature compensation factor alpha. And the compensation factor is used for dynamically correcting the temperature of the motor and the like, so that the interference of underground dust falling spraying on the temperature monitoring of the equipment is effectively eliminated.

The invention relates to the technical field of computer vision and robot positioning, and discloses a dynamic 3DGS-SLAM method and system based on Gaussian pyramid and adaptive densification. The method comprises the following steps: generating a semantic mask through real-time dynamic target detection so as to distinguish a static background from a dynamic object; constructing a 3D Gaussian map model of the scene; rendering images in parallel on a full-resolution view and a down-sampling resolution view by adopting a motion perception Gaussian pyramid rendering method, and fusing rendering results by utilizing a dynamic mask so as to eliminate motion edge artifacts; a self-adaptive densification strategy based on a monotonic attenuation function is adopted, the initialization radius of the Gaussian ellipsoid is dynamically adjusted based on the training progress, and high-density initialization and progressive redundancy pruning are executed to optimize the geometric fidelity; and finally, performing coarse-to-fine camera pose optimization, and outputting a precise pose and a high-fidelity static map. According to the method, the problems of tracking drift and rendering artifacts under dynamic interference are effectively solved, and the positioning precision and the rendering quality are improved.

The invention discloses an aging model and aging state prediction method and system of a retired power battery. An aging characteristic parameter sequence of a battery cluster is obtained; the aging characteristic parameter sequence is divided into multiple sections; in each section of the aging characteristic parameter sequence, different types of attenuation functions are adopted for fitting, and the membership probability of each type of attenuation function to each section and the weighted sum of each type of attenuation function serve as a fusion fitting function of each section; splicing the fusion fitting functions of all the sections to obtain an aging model of the retired power battery; clustering the fusion fitting function of each segment to obtain a typical fusion function of each cluster in each segment; establishing an aging state prediction model, wherein the aging state prediction model comprises an input layer based on a Transform network, a physical constraint layer based on an attention mechanism, a composite loss calculation layer and a feedback layer; an aging characteristic parameter fusion sequence output by the aging state prediction model is an aging state prediction result of the target battery cluster; and precise modeling and dynamic prediction of the aging state of the battery are realized based on finite parameters.

The invention discloses an urban population flow prediction method based on multi-source data, and the method comprises the steps: collecting and preprocessing mobile equipment position data, public transport card swiping data and POI point location data, and extracting time and space features; calculating a regional attraction coefficient, an inter-regional distance attenuation function, a regional connectivity matrix, a time dynamic parameter and an external influence parameter, constructing a comprehensive population flow prediction mathematical model, and optimizing model parameters through a machine learning method to realize accurate prediction of population flow among urban regions in a future time period; the urban population flow prediction method comprehensively utilizes multi-source heterogeneous data, fully considers the influence of a space factor, a time factor and an external environment factor on population flow, introduces an innovative index of a regional connectivity matrix, realizes adaptive updating of parameters, can effectively improve the accuracy of urban population flow prediction, and improves the urban population flow prediction efficiency. And a scientific basis is provided for smart city construction and urban traffic planning.

The invention discloses a gradient heating control system and method for a disposable medical endoscope. The control method comprises the following steps that temperature values Ti are collected in real time through three temperature sensor sets distributed on the front section, the middle section and the rear section of an endoscope body; the temperature gradient delta Tj of each section is calculated, and the calculation result is compared with a set threshold value theta; when any temperature gradient delta Tj exceeds a threshold value theta, a gradient compensation algorithm is started, and heating power output Pout is calculated; and according to a compensation calculation result, the power output of each heating sheet is dynamically adjusted, so that the temperature gradient delta Ti is within a set value. The temperature sensor group is arranged on the endoscope body, the power output of the heating sheet is dynamically adjusted by adopting a self-adaptive gradient compensation algorithm, and the gradient compensation coefficient alpha is adjusted by introducing an exponential attenuation function, so that accurate temperature control, adaptation to different operation modes, reduction of temperature fluctuation and improvement of equipment reliability are realized.

The invention relates to the technical field of bolt connection, in particular to a method for predicting the working condition of a bolt connection structure based on representation of pretightening force relaxation. The invention provides a double-exponential attenuation function, parameter identification of different functions is carried out, the double-exponential function which is simple in structure and good in characterization is obtained, the fitting precision of the double-exponential attenuation function reaches 99.3%, and the bolt pretightening force relaxation rule can be accurately characterized. According to the method, a pre-tightening force relaxation rule function is introduced into an Iwan model to represent the Iwan model under the relaxation condition meeting the actual condition, the relation between various parameters and pre-tightening is analyzed, a mathematical expression is constructed by adopting a least square method, the pre-tightening relaxation rule in a period is equivalent to the pre-tightening relaxation rule of tangential displacement and loading time, and the pre-tightening force relaxation rule is obtained. And constructing an Iwan model density function under a relaxation condition based on various variable parameters. According to the method, nonlinear behaviors such as energy dissipation and rigidity degradation can be predicted, and particularly, a relatively accurate method is provided for predicting various indexes under the working condition of bolt pretightening force relaxation.

The invention relates to the technical field of 3D scanning, and discloses a real-time alignment highlight curved surface metallographic 3D scanning method and system, and the method comprises the steps: extracting normal vector features from a multi-view point cloud, calculating an approximate geodesic distance, and constructing a normal vector geodesic distance correlation graph; constructing a constraint propagation intensity matrix through a geodesic distance inverse ratio and a normal vector included angle exponential attenuation function, and enabling the constraint propagation intensity matrix to act on a multi-view point cloud registration residual error to generate a closed-loop error energy field; constructing a graph cut network node at the gradient extreme value of the energy field, and executing a minimum cut algorithm under geodesic constraint by taking the integral value of the energy field as the side capacity to complete global point cloud fine registration; according to the method, the local geometry and the global topology are combined through the normal vector geodesic association diagram, the problem that the registration accumulative error breaks out at the closed loop position due to the fact that the highlight curved surface metallographic surface lacks texture features is solved, and real-time accurate alignment of the highlight curved surface metallographic workpiece multi-view point cloud on an automatic detection production line is achieved.

Disclosed in the present application are an audio enhancement method and apparatus, and a computer storage medium. The method comprises: generating a group of audio collection signals by means of a microphone array; performing delay-and-sum processing on the group of audio collection signals, so as to generate a delay-and-sum signal; performing blocking matrix processing on the group of audio collection signals, so as to generate a blocking matrix signal; using an adaptive filtering matrix to filter the blocking matrix signal, and removing the filtered blocking matrix signal from the delay-and-sum signal, so as to obtain an enhanced audio output signal. The adaptive filtering matrix is based on at least one attenuation function, and each of the at least one attenuation function is updated at an interval of a corresponding predetermined update interval T.

The invention discloses an image fusion enhancement method for a multi-signal-source liquid crystal splicing screen, and relates to the technical field of large-screen display control, and the method comprises the steps: building a virtual coordinate system taking a physical gap as a reference at an input end, carrying out the decoding, time synchronization and unified mapping of a multi-source heterogeneous signal, converting the multi-source heterogeneous signal into a unified color space, and carrying out the image fusion enhancement of the multi-signal-source liquid crystal splicing screen. The display consistency of different signal sources is ensured; then, a compensation model based on a brightness attenuation function is introduced into the splicing boundary area, edge pixel brightness is subjected to self-adaptive correction, and brightness unevenness caused by physical gaps is relieved; calculating the content complexity based on the row-level gradient magnitude in the fusion screen area, dynamically constructing a content-sensitive fusion weight, and carrying out weighted fusion on the images on the two sides to generate a transition image frame; and through joint output of the transition image frame and the original side image frame, visual seamless connection of the splicing gap area is realized. Therefore, the integral continuity and visual experience of tiled display are effectively improved while the image detail fidelity is ensured.

The invention provides a silicon-based millimeter wave digital attenuator and a millimeter wave active phased-array antenna, and relates to the technical field of phased-array antennas. The attenuation function of the silicon-based millimeter wave digital attenuator is realized by switching two groups of identical A / B differential circuits of each core attenuation unit, that is, in the whole attenuation range, only one group of circuits of each working core attenuation unit are switched on, and the attenuator circuit formed by combining all the units can be switched on in the aspect of radio frequency small signals. The attenuator circuit is not changed in the aspects of a direct-current working circuit or a direct-current working circuit, that is, the change of radio frequency input and output impedance in the whole attenuation range is very small, the matching of the attenuator circuit and a front-stage circuit and a rear-stage circuit is easily maintained, meanwhile, the working current is basically kept unchanged, and the phase fluctuation is very small when the attenuator works.

The invention relates to a laser radar point-to-line weighted matching method based on edge point quality evaluation, and belongs to the technical field of measurement. The method solves the problems that in traditional point-to-line matching, due to the fact that the quality of edge points is not evaluated, the pose estimation precision is low, and the robustness of an unstructured scene is poor. According to the technical scheme, a preprocessing module screens candidate edge points through projection point cloud, target segmentation and roughness calculation; the position judgment module classifies the candidate points as middle, left or right edge points according to the category consistency of the adjacent points; the direction consistency judgment module calculates a direction standard deviation and screens effective edge points; and the dynamic weighting module allocates weights according to an exponential attenuation function, and optimizes the pose through weighting residual errors. The method has the advantages that the pose estimation precision is remarkably improved, the weak structure environment adaptability is enhanced, the calculation efficiency is optimized, and redundant iteration is avoided.

The invention relates to the technical field of digital information transmission, in particular to a 5G Ethernet switch testing method and system, and the method comprises the steps: obtaining the operation state data of a target 5G Ethernet switch under a plurality of network testing conditions; determining data processing time and data transmission time corresponding to the same bandwidth in the plurality of network test conditions according to the running state data, and determining a data transmission delay rate of each network test condition according to the data processing time and the data transmission time; according to the operation state data, determining the change prominence of a plurality of network environment parameters under each network test condition, analyzing the promotion effect of the change of the network environment parameters on data transmission delay, and obtaining the promotion probability of each network environment parameter; and constructing a performance attenuation function of the target 5G Ethernet switch according to the data transmission delay rate of each network test condition and the promotion probability of each network environment parameter. According to the invention, the overall performance of the switch under different conditions can be comprehensively and accurately reflected.

The invention discloses an improved method for calculating grazing incidence sea surface back scattering through a small slope approximation method, and belongs to the technical field of sea surface electromagnetic scattering calculation, and the method comprises the following steps: S1, determining the wind speed of each stage of sea condition, and calculating the seawater dielectric constant; s2, generating sea surface geometry by using a linear filtering method based on a sea wave spectrum according to the determined wind speed; s3, introducing a conical incident wave; s4, introducing an edge geometric attenuation function; and S5, calculating sea surface back scattering by using an approximate integral formula of a small slope approximation method. According to the improved method for calculating grazing incidence sea surface back scattering through the small-slope approximation method, the edge geometric height is attenuated to 0 by applying the edge geometric attenuation function, so that the situation that the height fluctuation of the sea surface edge is close to an incident wave energy central axis is avoided, the problem that the calculation result is large under grazing incidence is solved, and the calculation efficiency is improved. And meanwhile, the calculation result is more accurate.

The invention discloses a thermal infrared three-dimensional modeling method and system based on linear Gaussian primitives, and the method comprises the steps: obtaining an infrared image of power transformation equipment, so as to construct a multi-view image set of the power transformation equipment; generating a sparse point cloud from the multi-view image set to construct an initial Gaussian primitive, and converting the initial Gaussian primitive into a linear Gaussian primitive through a linear attenuation function; constructing a thermal infrared physical model, and inputting the image set and the primitives into the physical model to obtain a thermal infrared synthetic image; constructing a composite loss function to calculate an error value of the infrared image and the composite image, calculating a gradient of the composite image, and carrying out back propagation iteration on the error value and the gradient to update parameters of the physical model; according to the method, the thermal infrared physical model is constructed, the atmospheric transmission effect and the thermal diffusion process are modeled, and the thermal loss is compensated by combining a residual addition mechanism, so that the problem of thermal radiation confusion caused by depth information attenuation is solved, and high-precision three-dimensional rendering under the dynamic illumination condition is realized.

The invention discloses a data quality dynamic evaluation analysis method and system based on fusion factors. The method comprises the following steps: constructing a multi-dimensional data quality factor set; constructing a dynamic evaluation window based on an aging attenuation function, and automatically adjusting an evaluation cycle of each quality factor according to a data life cycle stage; based on each data quality factor evaluation period, processing a multi-factor conflict problem in the evaluation period through an improved D-S evidence theory; constructing a hierarchical scoring model based on non-conflict factors, and obtaining a comprehensive quality score by adopting an improved entropy weight-TOPSIS fusion algorithm; and constructing an adaptive threshold triggering mechanism, and dynamically adjusting the weight in the data quality scoring model based on the historical scoring standard deviation. The method has the advantages that the data quality evaluation period is dynamically adjusted based on the aging attenuation function, the improved D-S evidence theory is utilized to fuse the multi-factor conflict evidence, and high-timeliness and high-precision dynamic evaluation of the data quality is achieved.

The invention relates to a video recommendation method, device and system and a computer readable storage medium, and the method comprises the steps: obtaining the video type preference of a user at each time node based on a plurality of time nodes; determining a time difference between each time node and the current moment, and for any video type preference, obtaining a weight of the video type preference according to the time difference and a preset time attenuation function; on the basis of the weights and the video preferences, obtaining weighted preferences through weighted averaging; taking the weighted preference as the input of a DeepFM model, and obtaining the output results of a linear module, a factorization machine module and a deep neural network module in the DeepFM model; according to the output result and the multi-layer perceptron, scores of the video type preferences are obtained, and a video recommendation list is determined according to the scores from large to small. According to the method and the device, videos can be recommended according to interests, changing along with time, of the user.

The invention is suitable for the technical field of automobiles, and provides an automatic driving control right smooth transfer method and system based on dynamic gradient amplitude limiting, and the method comprises the steps: detecting the operation intention of a driver, preventing false triggering through double thresholds, and triggering a transfer signal. Dynamic amplitude limiting is calculated according to driver torque, and multi-mode parameter selection is supported to adapt to different scenes. And the torque change rate is subjected to amplitude limiting smoothing, compensation torque is generated, and final torque is output through an attenuation function. According to real-time error dynamic optimization, iterative convergence is achieved, and it is ensured that the switching process is rapid and stable. According to the method, the problem that the torque generated in manual takeover during existing man-machine co-driving is not smooth is solved, and the risk of man-machine co-driving is reduced. According to the method, by designing an iterative optimization scheme, jitter and errors in the whole switching process are reduced, the mastering feeling of a driver is enhanced, the situation that the driver is nervous due to the problems such as steering wheel response is avoided, and the driver feels more comfortable and safer when taking over automatic driving.

The invention discloses a substation emergency lighting self-service power supply system, and relates to the technical field of emergency lighting power supply, and the system comprises the following steps: installing a sensor and a communication module, and setting basic parameters; collecting data, dynamically calculating illumination requirements, and compensating visual delay of human eyes; reading battery parameters, and quantifying the aging degree and the residual available capacity of the battery; calculating the power supply priority of each node by combining the emergency exit position based on the adjacent node state; the LED driving current is dynamically adjusted according to the priority, and gradient switching is adopted when the brightness changes in a large range; the low-electric-quantity node automatically initiates help seeking, and the surrounding nodes reduce own brightness in proportion; operation data are uploaded regularly, algorithm parameters are optimized, and a positioning signal is activated to guide maintenance when the battery is seriously lack of electricity. According to the invention, through the double-variable dynamic model coupling the ambient light attenuation compensation factor and the battery health degree attenuation function, the error accumulation of a single electric quantity criterion is eliminated, so that the power supply duration prediction better fits the real working condition.

The invention discloses an AGV full-life-cycle intelligent operation and maintenance method based on a twin map and reinforcement learning, and belongs to the technical field of equipment operation and maintenance management, and the method comprises the steps: employing an edge-level dynamic attenuation function and a node-level economic weight operator for aggregation, and obtaining a health vector containing a whole vehicle risk score and a part first-level risk identifier; the method comprises the following steps: training a reinforcement learning agent according to a three-section reward function comprising production line instant income, health improvement income and future risk deduction, and determining an operation and maintenance strategy weight file by adopting a profit-oriented gradient update mode optimization strategy with risk suppression factors; and carrying out equipment operation and maintenance management on the AGV in workshop operation according to the strategy weight file. According to the method, dynamic risk propagation and economic quantitative evaluation are adaptively fused under the real-time working condition of a workshop, and a comprehensive optimal decision of maintenance opportunity and production line income is realized under the condition of non-stop observation through a reinforcement learning strategy closed-loop driving AGV fleet preventive maintenance and scheduling method.

The invention relates to a control strategy correction method and device based on the health state of energy storage converter equipment. The current value and the current efficiency of health influence parameters of an energy storage converter are monitored and collected in real time; according to the current value and the rated value of the health influence parameter, obtaining the standard exceeding proportion of each parameter relative to the rated value; obtaining efficiency loss according to the rated efficiency of the energy storage converter under the current working condition and the corresponding current efficiency; respectively taking the exceeding proportion and the efficiency loss as independent variables, and combining an attenuation function, a penalty function and a corresponding weight to obtain a current health state evaluation value of the energy storage converter equipment; and correcting a control strategy of the energy storage converter equipment based on the health state level of the energy storage converter equipment. According to the method, self-adaptive control strategy correction of the energy storage converter based on the equipment health state is realized, and the equipment operation reliability and economic benefits are remarkably improved.

The invention discloses a Bluetooth device rapid pairing method and system based on multiple scenes. The method comprises the steps that scene features, device historical pairing, demand features, an efficiency set and signal intensity data are acquired; performing time sequence sampling on the signal intensity, calculating a stable distance value in combination with the correction model, and weighting historical data by using a time decay function to generate a historical weight score; scene correlation scores are obtained through scene model matching, demand features are mapped into demand vectors, an efficiency set is subjected to standardization processing, and function matching scores are calculated through cosine similarity. And performing weighted summation and normalization processing by integrating the stable distance, the historical weight, the scene correlation and the function matching to obtain an equipment priority score. And finally, carrying out intelligent grouping and conflict resolution on the equipment library based on the scores, generating a dynamic pairing strategy and executing connection. According to the method, rapid pairing of the Bluetooth equipment can be realized.

The invention discloses a house safety level prediction method and system based on a Bayesian network, and relates to the technical field of house safety evaluation. The method comprises the following steps: acquiring structural characteristic parameters, environmental influence factors and historical state information of a target house; performing three-level quantization processing on the structural characteristic parameters to obtain a structural evaluation matrix, and constructing a dynamic attenuation function based on the environmental impact factors to calculate a dynamic attenuation weight; generating a historical state index based on the historical state information through a multi-dimensional feature fusion technology; based on the structure evaluation matrix, the dynamic attenuation weight and the historical state index, calculating the structure redundancy as a hidden variable; constructing a three-layer Bayesian network; and probability propagation calculation is carried out through a Bayesian network inference engine, and the house safety level of the target house is determined according to the probability distribution of the output layer. By implementing the technical scheme provided by the invention, the actual safety level of the house can be accurately evaluated and predicted.

The invention relates to a high-order staggered grid viscous sound medium reverse time migration tunnel advanced detection method and system, and belongs to the field of tunnel engineering geophysical prospecting. According to the method, a viscoelastic anisotropic TTI medium anisotropy wave equation expressed by a fractional Laplace operator is deduced, and a viscoelastic anisotropic TTI medium first-order speed-stress elastic wave equation is solved by adopting a high-order staggered grid finite difference method. According to the invention, the wave field information at any moment is obtained, so that the propagation process of seismic waves in an underground medium is simulated more accurately. In order to solve the problem of reflection possibly caused by artificial boundaries, a PML (perfectly matched layer) absorption boundary processing method of a new attenuation function is adopted. According to the method, seismic waves can be effectively absorbed, reflection is avoided, and therefore simulation stability and accuracy are guaranteed. Generally speaking, the invention provides an accurate and stable tunnel advanced detection forward modeling method, and a reverse time migration algorithm is carried out in an attenuation TTI medium.

A computer having a system for mitigating mechanical rattle arising due to a mechanical coupling of an audio output transducer to a part of the computer device, the system comprising: a processing subsystem configured to receive an input audio signal and to output a drive signal for driving the audio output transducer to produce a transducer output, wherein the processing subsystem is configured to selectively apply an attenuation function to the input audio signal to attenuate a signal component of the input audio signal at a frequency that causes mechanical rattle in the computer; and an analyser subsystem configured to receive the input audio signal and to output a control signal to the processing subsystem to control application of the attenuation function to the input audio signal by the processing subsystem based on a spectral content of the received input audio signal; wherein the attenuation function is based on characteristic acoustic behaviour of the computer.