171results about How to "Detailed description" patented technology

The invention discloses an improved fuzzy neural network bus intelligent scheduling method based on a chaos theory, and belongs to the field of intelligent transportation. According to the improved particle swarm bus intelligent scheduling method based on the chaos theory, advantages and complementarity of various algorithms are fully utilized, a series of improvement measures are also introduced, such as conjugate gradient optimization, and inertia factor and constraint factor of the particle swarm algorithm etc., the mechanism and the search performance are researched from the theoretical and practical perspectives, problems of poor global search capability and premature convergence of the conventional optimization algorithm are fundamentally solved, the diversity of population can be obviously increased, the global search capability is obviously improved, the problem of fuzzy information can be effectively dealt with, the convergence speed is fast, and a new high-efficiency method is provided for bus intelligent scheduling.

The invention discloses a method for diagnosing mechanical faults of a distribution switch based on a two-dimensional feature vector cluster of vibration signals. The method comprises the following steps that an acceleration sensor is arranged near a switch operating mechanism and the vibration signals of the distribution switch on different states in the processes of gate switch-on and gate switch-off are obtained; two-dimensional information feature vectors of vibration signal energy and gravity center frequency are extracted through HHT band-pass filtering and conducted on the obtained vibration signals, the normalized two-dimensional feature vectors stand for effective feature quantity of the mechanical state of the distribution switch, and different kinds of mechanical fault diagnosis of the distribution switch can be achieved through a vague K mean value cluster (FKM).

The invention relates to an immersed vacuum membrane distillation plant and a sewage treatment technology using the same. The immersed vacuum membrane distillation plant comprises a raw water storage tank, a gas dissolving pump, a raw water heating water tank, a membrane distillation hydrophobic membrane module, a condenser, a vacuum buffer tank, a vacuum pump, a water producing tank, a valve, a measuring instrument, and an automatic controller. The sewage treatment technology is characterized in that: raw water is subject to pH regulation, microfiltration and other pretreatment, then the pretreated raw water enters into the raw water storage tank, the sewage in the raw water storage tank is subject to gas-water mixing through the gas dissolving pump, and then the gas-water mixture enters into the raw water storage tank for heating to a specific temperature, membrane distillation is carried out at the specific temperature, the produced water after membrane distillation is directly reused, and a little thick water is treated concentrately. According to the invention, the use of the plant in sewage treatment reduces the effect of concentration polarization and temperature difference polarization in the sewage, reduces membrane pollution, increases the membrane distillation flux, prolongs the operation period of the membrane module, reduces the heat loss of the pipeline, and increases the heat utilization rate.

The invention discloses a public opinion smart supervision method and a public opinion smart supervision system. The public opinion smart supervision method provided by the invention comprises the steps of S1, obtaining network public opinion texts by employing keyword lists and network public opinion website lists correlated to city emergency events; S2, analyzing the public opinion texts, thereby obtaining subjects and objects in the emergency events and emergency event characteristic identifiers; S3, carrying out semantic similarity evaluation analysis on the subjects and objects in the emergency events and the emergency event characteristic identifiers, clustering the network public opinion texts and determining hot event classes to which the network public opinion texts belong; and S4, output a clustering result and the determined hot event classes to which the network public opinion texts belong. Through application of the method, vocabularies such as geographic names, names and organization names with high event characteristic representation can be identified rapidly and accurately and the described public opinion events can be depicted deeply and carefully.

The invention relates to a method for synthesizing seismic records based on three-dimensional Gaussian beam ray tracing and a frequency domain. The method comprises the following steps of: 1) performing kinematics tracking by utilizing a common ray tracing way to obtain a ray path and kinematics characteristics; 2) performing dynamics tracking by utilizing a Gaussian ray beam to calculate dynamics characteristics; 3) synthesizing the seismic records in the frequency domain. As a Futyterman equation based attenuation algorithm, a frequency based green function and a weak anisotropic model of a coupling ray theory can be considered for the synthesis of the seismic records in the frequency domain, the dynamics characteristics of a seismic wave field can be described more delicately in comparison with a conventional method, and the seismic records synthesized by utilizing the ray theory is close to the precision of the wave theory. The method for synthesizing the seismic records based on the three-dimensional Gaussian beam ray tracing and the frequency domain can calculate information such as ray amplitude and phase shift conveniently, can be applied to the fields such as manufacturing of synthesized records, prestack depth migration and waveform tomography inversion.

The invention relates to a crack fluid type identifying method based on longitudinal wave frequency depending on amplitude versus offset (AVO) and azimuth. Earthquake anisotropism is related to frequency, and when crack media are filled with different kinds of fluid, difference exists between anisotropism intensity and the earthquake frequency changing gradient. According to the method, frequency information is introduced into an AVO and azimuth inversion theory of elastic media, and the inversion theory is expanded to the field of viscoelasticity, namely AVO and azimuth depending on frequency. By solving the formula of the AVO and azimuth depending on frequency, a longitudinal wave anisotropism frequency dispersion item is obtained. The method has the advantages that the application effect of practical data shows that longitudinal wave anisotropism frequency dispersion can be used for identifying the type of fluid in a crack, meanwhile, the method is good in water identifying effect, and the method can be used for practical data and can identify the type of fluid in a crack on an area where the anisotropism degree is high.

The invention discloses a method and a system for monitoring underground engineering portrait information and monitoring information safely. The system comprises a monitoring measurement information processing system, a portrait information processing system, a comprehensive safety monitoring analyzing module, an early-warning and warning output module and a next-stage geologic structure reporting module. The monitoring measurement information processing system and the portrait information processing system are respectively connected with the input end of the comprehensive safety monitoring analyzing module, and the output end of the comprehensive safety monitoring analyzing module is respectively connected with the next-stage geologic structure reporting module and the early-warning and the warning output module. The method and the system for monitoring the underground engineering portrait information and the monitoring information safely acquire monitoring measurement information and portrait information in real time, analyze safety level of acquired data, perform early warning and warning on dangerous situations and forecast geological situations at the next stage, and have the advantages of performing remote control, timely finding and recording abnormal data information and warning data information, being convenient for technical personnel to analyze, and the like.

The invention relates to a power distribution network comprising a direct-current distributed power supply and an analysis method of comprehensive load characteristics of the power distribution network. The power distribution network comprises static loads, a dynamic load bus and comprehensive loads, wherein the static loads are equivalent static loads formed by combining static load elements and the direct-current distributed power supply, a model structure of the comprehensive loads is a generalized comprehensive load model structure and comprises a reactive compensation device, static loads, induction motor loads, an equivalent power supply, a power distribution network equivalent impedor, the reactive compensation device, the static loads, the equivalent power supply and an induction motor are connected in parallel and are connected to an external system through the power distribution network equivalent impedor. The model structure of the comprehensive loads adopted in the power distribution network can integrally describe various load characteristics of nodes, and the problem that after a large number of distributed power generation devices are connected to the power distribution network, the power distribution network affects the comprehensive load characteristics is solved.

The invention provides an image description method based on a convolutional neural network, a computer readable storage medium and electronic equipment, and solves the problems that an existing recurrent neural network method cannot process sequence signals in parallel and is time-consuming in operation. The method comprises the following steps: 1) pre-training the convolutional neural network; 2) extracting global features and local features of the image, and projecting the global features and the local features of the image into a multi-modal mapping space; 3) performing convolutional coding on the image expression in the multi-modal mapping space in the step 2); 4) carrying out word feature expression; 5) carrying out convolution coding on the description statement in the step 4), 6) calculating the attention, and obtaining the probability of word generation corresponding to the input image; 7) constructing a target loss function between input and output, and performing neural network training by using the loss function to obtain position parameters of the neural network, and 8) inputting the test image into the trained neural network system to obtain a descriptive natural statement corresponding to the test image.

The invention relates to an exhaust gas purification system for diesel engines (1), wherein at least one oxidation catalyst (3), a reducing agent injection device (6) and a reduction catalyst (9) are provided, which are arranged together in a housing (5) having a first lateral chamber (15) close to a first face (16) and a second lateral chamber (17) close to a second face (18), wherein: - the reduction catalyst (9) is arranged in the first lateral chamber (15), - the oxidation catalyst (3) is arranged in an outer annular space (11) of the second lateral chamber (17), - the reducing agent injection device (6) is oriented toward an inner channel (19) of the outer annular space (11) of the second lateral chamber (17), and - a flow path (14) for the exhaust gas from at least one exhaust gas inlet (20) toward at least one exhaust gas outlet (21) is provided, through the following components: oxidation catalyst (3), reducing agent injection device (6), and reduction catalyst (9).

Recombinant Myxococcus host cells can be used to produce polyketides, including epothilone and epothilone analogs, which can be purified and crystallized from fermentation broths.

To support cell search, multiple (e.g., two) synchronization transmissions are sent in a frame with non-uniform spacing. Information is conveyed via the non-equal distances between consecutive synchronization transmissions. Multiple levels of non-uniform spacing may be used to convey different types of information. In one design, the multiple synchronization transmissions are sent in different subframes of a frame, and each synchronization transmission is sent in one of multiple symbol periods in a respective subframe. The synchronization transmissions may be sent in non-evenly spaced subframes to convey frame boundary. One synchronization transmission may be sent in one of multiple possible symbol periods depending on the information, e.g., a particular group of cell IDs, being conveyed. The distances between synchronization transmissions may also be used to convey cyclic prefix length. A secondary synchronization transmission carrying a cell ID may be sent at a predetermined offset from one of the multiple synchronization transmissions.

The invention relates to a method for establishing a logical relationship between an interested point and a building. The method comprises a building and interested point obtaining step for obtaining the building and the interested point associated with the building, wherein description information of the building comprises shape information and geographic coordinates of the building, and description information of the interested point comprises the name and geographic coordinates of the interested point; and a mapping establishing step for establishing a logical mapping between the associated building shape information and the interested point. According to other aspects of the invention, the invention also relates to an apparatus for establishing a logical relationship between an interested point and a building, a server and a computer readable medium. Through the method, apparatus, server and computer readable medium according to embodiments of the invention, the actual shape of the interested point of the building type can be accurately described, the geographic coordinates of the interested point can be intensively described, and human cost can be largely saved.

The invention discloses a method for manufacturing and managing an operation information model of high-speed railway passenger dedicated line equipment in a virtual reality environment. The method comprises technical steps of constructing a three-dimensional visual platform of the high-speed railway passenger dedicated line, establishing an operation information model of the high-speed railway passenger dedicated line, managing the operation information model of the high-speed railway passenger dedicated line, and performing operation information emergency response of the high-speed railway passenger dedicated line equipment. The method of the invention can perform functions of accurately describing equipment and operation state in detail, visually checking equipment position, surrounding geographical environment and spatial relation between adjacent equipment, performing searching and statistics on equipment and state of the equipment in a random mileage interval, making an equipment maintenance plan through spatial analysis, statistics algorithm, database technology and the like, realizing quick disaster point positioning after equipment alarm, making an emergency response solution according to information such as road network, residential cell, hospital and firefighting facility distribution, and improving management efficiency and operation safety of the equipment.

The invention discloses a network society influence maximization algorithm based on microblog text affective computing, and mainly relates to the field of text affective computing, network society calculation and influence maximization, in particular to a microblog emotional tendency calculation method and a network community relation structure extraction method. Firstly, a special microblog dictionary is constructed according to anagrams, neologisms and new meanings (such as 'watch man') appearing in microblogs. The emotional tendency of microblog texts is analyzed according to a HowNet dictionary. Then, a network community user relationship tree is constructed according to the interaction operation relationship of various users. Finally, network design emotional influence maximization calculation is carried out according to the emotional tendency of the microblog texts and the network community user relationship tree. The problems that the user relationship in a network community structure is single, and maximization influence problem calculation is incomplete are solved, and the microblog emotional tendency can be calculated more accurately, and a network emotional influence maximization user set meeting reality better can be obtained.

The invention discloses a time-space domain statistical matching and weight allocation combination-based moving target detection method. The method comprises the steps of firstly, proposing and researching the importance of neighborhood pixel points distinguishable for a 3-D LWR operator for extracting finer time-space local features of videos; secondly, performing background removal and multi-scale zooming on features of a 3-D LWR template set to form a composite template set, and performing matching with local features of a test video to obtain a local similarity matrix; and finally, performing time-space statistics to obtain a position probability matrix of a moving target, and extracting the moving target by analyzing the position probability matrix. According to the method, a conventional LARK operator is combined with weight allocation, and a new time-space statistical matching detection model of the moving target is built. Compared with an existing supervision method, the same detection precision can be achieved without a large amount of trainings; and compared with an existing non-supervision method, the scene and the shooting angle suitable for the test video are expanded, the false detection rate is reduced, and the method provided by the invention is suitable for visible light videos and infrared videos.

The embodiment of the invention relates to a data processing method and system used for the behavioral description of an intelligent vehicle. The method comprises the steps that environmental sensinginformation and vehicle state information are obtained; behavioral parameters and state parameters of the intelligent vehicle are extracted; behavioral parameters and state parameters of obstacles areextracted; execution object fields, driving action fields, to-be-executed object fields and constraint condition fields are generated; a driving statement structural model is called, and the fields are assembled into driving behavioral statement information; semantic recognition analysis is conducted on the driving behavioral statement to obtain a predicted running trajectory and state machine behavioral information of the intelligent vehicle; a running trajectory of the intelligent vehicle is generated. According to the method, through the driving statement structural model, description of the intelligent vehicle and target complicated behaviors can be accurately and clearly described in details so that the running trajectory of the intelligent vehicle can be accurately planned, the complicated degree of the system is simplified, and therefore the route planning time of the intelligent vehicle is improved.

The invention provides a crack based on a non-linear algorithm and a method for identifying fluid in the crack. The method provided by the invention is based on a trinomial Ruger reflection coefficient equation, and a non-linear equation containing a third member (sin<2>[theta]tan<2>[theta] member) of the Ruger equation and Thomsen anisotropic parameters are deduced out by a different position subtraction method. A non-linear algorithm-particle swarm algorithm is utilized for solving out the crack density, the Thomsen anisotropic parameters and the like from the deduced equation. A crack fluid indicating factor expression is deduced by utilizing the solved crack density and the Thomsen anisotropic parameters. In actual application, the crack density obtained on the basis of the provided non-linear equation is much closer to a theoretical value than the crack density obtained through conventional linear AVOZ inversion; anisotropic parameter values of the inversion are very close to the theoretical value; the crack fluid indicating factor obtained by using the solution of the non-linear equation is used for perfectly identifying the types of the crack fluid; and the feasibility of the method is sufficiently shown.