73 results about "Interval method" patented technology

Methods and systems involve the formation of a classification interval used for sensing a cardiac signal following a pacing pulse to determine a cardiac response to pacing. One or more cardiac signals associated with a type of cardiac pacing response are sensed. The timing of at least one feature of the cardiac signal may be used to define an initial cardiac response classification interval. The classification interval is adapted based on the variability of the timing of the feature. The classification interval may be adapted using a predetermined number of additional cardiac signals or until a predetermined stability criterion is achieved.

The invention discloses a train tracking interval real-time early warning system based on CTC (central traffic control) and an early warning method, which belong to the field of high-speed train safety control technology. A dispatching center subsystem early warning server of the system consists of an early warning server and a dispatching command output unit, an application server of the dispatching center subsystem consists of a train number tracking unit and a wireless checking unit, vehicular equipment comprises a wireless train number vehicular encoder, and the system comprises a wireless train number decoder. The method includes acquiring a train number from decoded train comprehensive information by the aid of the wireless checking unit, comparing the acquired train number with a train number obtained by the train number tracking unit, and acquiring an accurate and reliable train number; and computing tracking intervals of a train by the aid of the early warning server, and controlling the dispatching command output unit to output control instruction according to a computation result. The train tracking interval real-time early warning system based on CTC and the early warning method form double channels with an ATP (automatic train protection) computation tracking interval method, a monitoring effect for a train tracking interval ATP control effect is realized, and integral safety of a train control system is improved.

Method for the reduction of echo and/or noise signals in TK systems for the transmission of useful acoustic signals, in which, when a silence interval is present, the distorted useful signal is modified by a time-dependent control signal a_o(t) or by a control signal a_o(k) cycled in the rhythm of a scan rate f_T=1/T. The control signal a_o(k) is varied in such manner that, during the presence of speech signals in the useful signals, the amplitude of the control signal a_o(k) is set to a predetermined constant value c_o and, when a silence interval begins, the amplitude of the control signal a_o(k) is reduced continuously from one sample value to the next in accordance with the recurrence formula a_o(k+1)=a_o(k).β with β<1. After the end of the silence interval, a_o(k) is again set equal to c_o.

The measurement of the distance or/and the relative velocity with fast response is to be achieved while the accuracy of measurement of the distance to an object in close range is maintained. A calculation-execution determination section determines whether or not an object is present within a predetermined range from the strength of a two-frequency Doppler signal sent from an A/D converting section and past calculated distance sent from a calculation selecting section. If the object is outside the predetermined range, the distance calculated by an FFT-method calculating section is output from a calculation output section via an calculation selecting section. If the object is within the predetermined range, one of the distance calculated by a time-interval-method calculating section and the distance calculated by the FFT-method calculating section is selected by the calculation selecting section, and is output from the calculation output section. The invention can be applied to a fast response system such as a precrash system.

The invention discloses a traffic flow change trend extraction method based on floating car data and belongs to the technical field of intelligent transportation. The traffic flow change trend extraction method based on the floating car data comprises obtaining historical floating car data of at least three mouths of a road chain and classifying the data according to feature days; performing denoising and smoothing on the historical floating car data; dividing the historical floating car data of every feature days into at least one time frame according to the change trend of a morning peak and an evening peak; performing preliminary clustering on the classified historical floating car data through a K-means clustering method; further clustering the historical floating car data through a controlled interval method or a two-value method according to a coarse granularity expression of traffic information. The traffic flow change trend extraction method based on the floating car data combines the coarse granularity expression of the traffic information, further merges the traffic flow trends on the basis of a K-means clustering method, enables the traffic flow change trend to be more salient, thereby providing more crystal clear references for traffic flow prediction, route planning and induction, route planning and the like.

A modal intervals-based high-speed train bogie fault diagnosis method includes the steps of 1, acquiring a high-speed train bogie vibration signal; 2, preprocessing the high-speed train bogie vibration signal; 3, subjecting the high-speed train bogie vibration signal to modal interval valuing; 4, subjecting the high-speed train bogie vibration signal to EMD (experience modal decomposition); 5, subjecting the high-speed train bogie vibration signal to feature extraction; 6, constructing and training an initial interval neural network model; and 7, performing high-speed train bogie fault diagnosis. Uncertainty in bogie vibration signals is processed by the modal interval method, and high-speed train bogie faults are diagnosed by a classified recognition method of the interval neural network model; the uncertainty in the high-speed train bogie fault diagnosis is handled by the modal interval method, and reliability of fault diagnosis results is greatly improved. The method is applicable to the fault diagnosis for high-speed train bogies.

The present invention discloses a vehicle suspension leaf spring frequency domain fatigue analysis method. The method is characterized by comprising: targeted at a pre-stress and a large transformation effect of a leaf spring, establishing a leaf spring geometric model in a free state and importing the leaf spring geometric model into finite element software for analysis; by applying a displacement constraint on a plate spring seat and applying a theoretical axle load on front and rear lugs, obtaining stress distribution in an operating state of the leaf spring, so as to obtain a leaf spring modality result file; by acquiring experimental data of a vehicle on a durability test road, obtaining a power spectrum density of a relative acceleration; and targeted at the obtained leaf spring modality result file, by using the obtained power spectrum density as a load input, executing a random vibration analysis in the finite element software, extracting a dynamic response result of a virtual prototype under a random excitation and estimating fatigue performance of the leaf spring on the durability test road according to a Gaussian three interval method. The method disclosed by the present invention is accurate in result and high in operation efficiency.

The invention discloses a box separation method based on k-means clustering. The box separation method comprises the following steps that continuous variables are preprocessed; normalization processing is carried out on the preprocessed data, a k-means clustering algorithm is applied on the data obtained after the normalization processing is carried out to divide the data into a plurality of sections; the equal interval method is adopted for setting the initial center of the k-means clustering algorithm to obtain clustering centers; after the clustering centers are obtained, the midpoint of the adjacent clustering centers is used as a classification division point, each object is added into the closest class, and therefore the data are divided into the multiple sections; each clustering center is calculated again, then the data are divided again until each clustering center does not change any more, and the final clustering result is obtained. According to the box separation method, the technical problem that errors are likely to be caused for a data set with the obvious data density distribution bias according to an existing box separation method is solved, the k-means clustering algorithm does not select the initial center randomly any more, and the data separation result is accurate.

Methods and apparatuses are presented for communicating using a shared communication medium. A request is sent over the shared communication medium. The shared communication medium is organized to include a request signal space and a scheduled transmission signal space. The request signal space includes a plurality of request segments each having a different location within the request signal space. The scheduled transmission signal space includes a plurality of scheduled transmission segments each having a different location within the scheduled transmission signal space. The request occupies more than one request segment. Each of the more than one request segments is randomly selected by the first node. An assignment is received assigning the request to a transmission opportunity in the scheduled transmission signal space. The assignment is made in response to detecting at least one of the more than one request segments. A data transmission is sent using the assigned transmission opportunity.

The present invention refers to low code rate screen encoding method, belonging to video coding decoding technology field. It contains collecting computer screen picture; uniformly dividing screen picture into plurality of image pieces; comparing with previous frame screen picture corresponded piece; according to comparative result determining whether to make space domain resolution ratio reducing and encoding to current frame, if encoding then adopting time domain self adaptation key frame interval method to determine encoding as key frame or non-key frame; respectively processing mouse messages and image data, adopting destructive and non destructive encoding adjoined encoding method to image data. The present invention is suitable for low code rate videoconference, tele education, and long-range control etc.

Methods and systems are directed to detecting atrial tachyarrhythmia. A plurality of A-A intervals is detected. The detected A-A intervals are selected and used to detect atrial tachyarrhythmia. Selecting A-A intervals may be based on determining that A-A intervals are qualified. Qualified A-A intervals may be determined if a duration of the particular A-A interval falls outside a predetermined duration range, for example. Qualified A-A intervals may also be determined based on events occurring between consecutively sensed atrial events of the particular A-A interval, and whether the duration of the particular A-A interval falls within the predetermined duration range, for example.

The invention discloses a method of three-phase unbalance load flow calculation based on the complex affine mathematical theory. The method includes inputting network original parameters including impedance values of each line and transformers, and active power and reactive power of each load node phase; initializing amplitude values and phase angles of each load node phase voltage; setting zero of iteration; calculating each phase injected current complex affine vector of each load node; starting from an end load node, performing summation calculation of branch current, and acquiring starting current complex affine values of each phase of each branch; and utilizing a set original load node voltage as a boundary condition to calculate voltage drop of each phase of each branch and end voltage complex affine values. By the method compared with the prior art, effective optimization of an uncertain load flow calculation interval algorithm is provided, interval load flow result conservative property, defects of an interval method are overcome, load flow of a distribution network containing uncertain information can be figured out effectively, and conservative property in the process of interval load flow calculation can be solved.

The invention discloses semen diluent and a method for artificial insemination of breeding hens at an interval of six days. The semen diluent comprises semen diluent 1, semen diluent 2 and semen diluent 3; the semen diluent is prepared from the following ingredients in part by weight: 5-7 parts of monosaccharide, 7.2-10.1 parts of buffering substance, 1.5-2.8 parts of antibiotics, 0.2-1.2 parts of weak electrolyte, 6.4-8.3 parts of vitamin, 0.3-0.5 parts of EDTA-Na (ethylenediamine tetraacetic acid disodium salt) or 1.5-2 parts of lycopene. The semen diluent is adopted for artificial insemination by adopting a six-day interval method, the sperm motility is effectively improved, the fertilization probability is increased, the labor intensity of workers is effectively reduced, the investment of labor cost is also reduced, and working stress caused by less breeders can be alleviated.

The invention discloses a mine moving target positioning method based on RSS (received signal strength) and TOA (time of arrival) complementation, which combines an RSS method and a TOA method and overcomes the defect of overlarge positioning error caused by a traditional single positioning method. The method comprises adopting a distance measurement interval method to suppress an NLOS error signal, solving a distance correction weight value according to a distance relative error value between every two nearest neighbor positioning base stations in the roadway, and performing distance correction on the distance measurement value; obtaining the weight of each distance measurement value by adopting a speed threshold function method, and optimizing the distance measurement values according to the weights; and performing accurate positioning calculation on the corrected distance estimation value through a weighted positioning method. The method solves the problem that an existing mine personnel positioning system and method is influenced by the environment of a roadway and is insufficient in positioning accuracy, is simple and effective in positioning process, has strong anti-electromagnetic interference capability, and can effecively realize the accurate positioning of underground coal mine personnel, vehicles and other moving targets.

The invention relates to a thermal-electric coupling multi-energy flow system power risk assessment method based on an interval method, and belongs to the technical field of risk assessment of the comprehensive energy system. According to the risk assessment method, a multi-energy flow system equipment model and a multi-energy flow system stochastic model are established, the consumption effect ofoptimal scheduling of the energy storage equipment and the flexible unit in the system on the uncertainty is considered and the interval method solving the stochastic problem is given, and the size of the risk of the uncertainty of the renewable energy source and the uncertainty of energy consumption of the electricity user and the heat user in a day in the future on the multi-energy flow systempower balance is calculated. According to the method, the operation risk of the electric-thermal coupling multi-energy flow system can be more accurately calculated so that the operation safety can beenhanced, the operation cost of the multi-energy flow system can be reduced, and certain contribution is made for searching multi-consumption of the renewable energy source and multi-energy system joint scheduling.

The invention provides a rock-plug type water intake for the circulating water of power plants, as well as a construction method thereof. The rock-plug type water intake is arranged near a deep pool and mainly comprises a rock plug, a ballast collection pit and a derivation tunnel behind the ballast collection pit, wherein the derivation tunnel is arranged in a mountain body; an axis close to an inlet segment declines so as to keep the axis of the rock-plug type water intake at an upward inclination angle between 35 and 60 degrees; the outlet end of the derivation tunnel is directly connected with an inflow forebay of a circulating pump room; the sinking-type ballast collection pit is built between the derivation tunnel and the rock plug; the cross sections of the derivation tunnel and the rock plug are round, similarly round, square or rectangular; and the thickness-diameter ratio of the rock plug is between 1.13 and 1.50. The construction method comprises the following steps: the excavation construction of the derivation tunnel and the ballast collection pit is performed according to a new Austrian method; whether to line or not is determined according to the conditions of bedrock; the rock plug is blasted by use of a presplitting and millisecond time interval method; and once the rock plug is blasted, all ballast of the rock plug enters the prearranged ballast collection pit under the action of external water pressure. The construction method has the advantages of reducing project investment, shortening construction period, improving the operation efficiency of a circulating water system, and the like.

The invention provides a method for optimizing a power grid planning scheme based on a comprehensive cost model. According to the method, the comprehensive cost model, which adopts the planning target age limit as a boundary and considers the annual cost and the current value of a planned scheme at the end of the year, is created. The calculating range of the model is the grid equipment (substations and transmission lines) which produces variable amount of costs in the scheme, wherein economic life of old equipment is needed to be forecasted to determine whether needing to update and when updating within the planning period. Meanwhile, fault rate forecast of new and old equipment within the planning period is trained and output through a least square support vector machine algorithm. In addition, when the comprehensive cost model is applied to comparing planning schemes, in order to reduce the influence on error of economic variables, an interval method is adopted. Numerical examples show that economic optimization of the power grid planning scheme is effectively realized by combining the comprehensive cost model with the interval method, and the comprehensive cost model is suitable for planning target age limits in various lengths.

Methods, apparatuses, and computer program products for delivering one or more television programs for viewing during a specified viewing interval. The methods include receiving a viewer's selection of a broadcast channel from an electronic program guide, presenting the viewer with a list or menu of two or more programs on the viewer selected broadcast channel that are available for viewing during a specified viewing interval, and receiving a viewer's selection of a program from the list or menu. If the specified viewing interval has commenced and has not yet expired, the viewer selected program is delivered for viewing.

The invention discloses an interval uncertainty optimization method based on BP neural network differentiation and interval analysis. The interval uncertainty optimization method comprises the steps of training a BP neural network agent model of an original model; employing NSGA-II algorithm in an outer-layer optimization solver, calculating an inner layer interval by adopting an interval analysismethod; for each group of design variables, carrying out interval division by adopting a sub-interval technology; inputting the interval median of the subinterval combination into a neural network tocalculate an output response, carrying out a neural network first-order differential operation, carrying out first-order Taylor series expansion on the uncertainty objective function and the constraint function, and calculating the intervals by adopting an interval expansion method and an interval set method; converting the uncertainty optimization model into a multi-objective determinacy optimization model through an interval sequence, an interval possibility and an error economy evaluation index; and using NSGA-II algorithm for performing simulation search to obtain a Pareto optimal solution set. Through the method, the nonlinear interval uncertainty optimization problem, especially the engineering uncertainty optimization problem, can be efficiently solved, and the method has high engineering practical value.

The invention discloses a high-speed train noise prediction method based on the interval neural network. The problem of uncertainty of acquired parameters affecting high-speed train noise is solved by means of the general interval theory, and high-speed train operation noise is accurately predicted with an interval neural network model. The method comprises the steps of 1, selecting parameters affecting high-speed train noise; 2, acquiring the historical data of the parameters affecting noise; 3, conducting data preprocessing; 4, conducting interval treatment of preprocessed data; 5, establishing an initial interval neural network model; 6, training the initial interval neural network model; 7, predicting high-speed train noise. The problem of uncertainty of parameters affecting high-speed train noise is solved by means of the general interval method, high-speed train operation noise is predicted by means of the interval neural network model predicting method, and the reliability of a noise prediction result is improved.