802results about How to "Improve digging efficiency" patented technology

The invention provides a method and a device for fault locating, and relates to the application field of computer networks. The method and the device for fault locating solves the problem that an existing alarm relevance rule mining system is poor in timeliness and low in efficiency. The method includes constructing a network element topology constraint model; detecting running status of each network element device in a managed network so as to find fault events; collecting the fault events; and using the network element topology constraint model for time layer correlations and space layer correlations of the collected fault events so as to determine a fault location. The method and the device for fault locating are appropriate for fault diagnosis, and achieve efficient and accurate fault locating.

The invention discloses a machine learning device, a machine learning method based on the machine learning device, and a big data platform using the machine learning device and the machine learning method thereof. The machine learning device comprises a user-defined process module, a configuration module, a database and an event server, wherein the user-defined process module comprises a logic module, the logic module can receive an executable file contained in a request initiated by a user, and can be called by the event server; and the database binds a front-end development application with the executable file through a configuration file written by the configuration module. According to the machine learning method, the machine learning device and the big data platform, the service logic component is completed by means of the user-defined process module, the adaptability and universality of the machine learning method, the machine learning device and the big data platform for various application scenarios are realized, efficient operation of data mining and machine learning involved in the development process of standardized big data are achieved, the development process of the standardized big data is simplified, and the development and deployment efficiency of the standardized big data is improved.

The invention discloses a data mining method and a data mining system. The data mining method comprises the following steps of: setting a workflow for data mining, wherein the workflow comprises a plurality of parallel data processing tasks; starting the workflow, and when the plurality of the parallel data processing tasks are triggered, allocating an execution node to each one of the data processing tasks to ensure that the plurality of the parallel data processing tasks are executed in parallel on the allocated execution nodes; and when the execution nodes execute each data processing task, allocating the data processing tasks to Map tasks executed in parallel to perform processing by a Map / Reduce mechanism, and combining processing results of all the Map tasks corresponding to the data processing tasks through a corresponding Reduce task so as to obtain the processing results of corresponding data processing tasks. By adopting the data mining method and the data mining system, the data mining efficiency can be improved.

The invention provides a method and device for mining synonyms. The method comprises the following steps of: searching a query and a webpage title which is clicked or browsed in a searching result corresponding to the query from a searching log, or allowing the clicked or browsed webpage title to correspond with different queries, and acquiring a candidate resource of a synonym formed by phrase pairs; and extracting a synonym from each phrase pair of the candidate resource, wherein the extracted synonym pair has the same context from the phrase pairs. According to the method and device for mining synonyms, the efficiency and accuracy of mining synonyms can be improved, and the mined synonyms can be in more accordance with the language characteristics of a search engine.

This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collects any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.

The invention provides a detection method of a user's electricity consumption behavior based on clustering analysis. According to the detection method, a user data warehouse is created so as to collect user's electricity consumption information, the created user data warehouse is processed to form principal component data so as to process large sample data, and the mining efficiency is improved; clustering calculation is conducted on the principal component data to obtain different user's electricity consumption modes, wherein outlier objects in the user's electricity consumption modes probably are electricity stealing users, and then electricity stealing suspected users are obtained by calculating for the outlier objects by means of the hierarchical clustering method. In the provided detection method of the user's electricity consumption behavior based on the clustering analysis, the hierarchical clustering method only needs to sequence the distance between the objects and conduct clustering according to a distance sequence, and the objects do not need to be inspected or estimated; meanwhile, the detection of the outliers and the clustering calculation are highly complementary, and good scalability is achieved.

The present invention discloses a gas pipeline leakage detection and identification method based on optical fiber sensing data excavation. The method comprises: employing distributed optical fiber sound waves / a vibration sensor to pick up leakage sound waves / vibration signals propagated along a pipeline, performing Mel cepstrum, AR model feature extraction and feature selection of the collected leakage sound waves / vibration signals of each space point, and establishing an association rule of the selected feature attributes and a type of a leakage event through an improved feature rule excavation method and positive and negative sample excavation to perform real-time online intelligent detection, identification and classification of a gas pipeline leakage event and solve a gas pipeline online leakage detection problem under a complex noise environment. The gas pipeline leakage detection and identification method based on optical fiber sensing data excavation can detect and identify simple pipeline leakage signals, and can detect and identify leakage signals mixed with different interference sources.

The invention relates to the technical field of data mining and data privacy, and discloses a frequent item set mining method. The frequent item set mining method comprises the following steps: S1: segmenting a transaction of which the transaction length is greater than a restriction length in an original database into a plurality of sub-transactions, and causing the length of each transaction in the segmented database to be smaller than or equal to the restriction length; and S2: according to a support degree threshold value which is appointed in advance, utilizing a support degree estimation method and a dynamic descent method to mine the frequent item set in the segmented database. The frequent item set mining method can provide higher mining efficiency and mining result availability while differential privacy protection is met.

This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine by filling earth into a hole within the site and compacting the earth. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.

The invention discloses a method and system for mining Chinese event information. The method includes the steps of defining an event sample model based on the mining requirement, instantiating the event sample model to obtain a seed event, taking the seed event as the foundation of an event mined from an original text, conducting preprocessing on the original text to obtain a candidate template set, conducting information labeling on the seed event, processing the seed event on the basis of labeling information to obtain a seed template set, then, processing the candidate template set through an iterative method according to the grade scores of candidate templates and the semantic similarity between the candidate templates and seed templates so that an event mining anchor set can be obtained, and obtaining the event types corresponding to mining event anchors according to the lexical semantic similarity between each event mining anchor in the event mining anchor set and any seed event anchor in the seed event set. The aim of mining the Chinese event information from the original text can be achieved only by labeling a small amount of samples, namely, the seed events, and the mining cost is reduced.

The invention discloses a related resource address push method and device based on video retrieval. The related resource address push method and device based on the video retrieval comprises the steps of obtaining the characteristic text information of first video resource data when the loading or playing requests of the first video resource data are received, mapping the characteristic text information as one or more first participles, searching related second participles having the co-occurrence rate with the one or more first participles higher than a preset threshold value, wherein the co-occurrence rate is the possibility of the current one or more first participles and the second participles emerge together in identical video resource data, obtaining the network chained addresses of the second video resource data matched with the one or more fist participles and the related second participles, and pushing the network chained addresses of the second video resource data. The related resource address push method and device based on the video retrieval achieves the purpose of delving resources of good quality in a video database deeply, and improves delving efficiency of the resources. In addition, an index table can be enlarged continuously along with the accumulation of the video content of the internet, and the fact that a recall rate is facilitated is enlarged.

Embodiments of the invention provide a data processing method device as well as a server. The data processing method comprises the following steps of collecting data reported by at least one terminal device, wherein the data comprises unique identifiers pre-distributed to the terminal devices, record data generated through operating the terminal devices by a user and device attribute information of the terminal devices; analyzing the record data and / or the device attribute information according to a preset data association algorithm, so as to determine the unique identifiers of the terminal devices which belong to the same user; and matching the record data reported by the terminal devices which belong to the same user and the device attribute information with preset user behavior models so as to determine a matched user behavior model, and carrying out data pushing according to the user behavior model. According to the data processing method and device as well as the server, the efficiency of data mining and the correctness of user behavior analysis can be improved.

A job practice of which center island is done in sequence and partial skirts done inversely, comprising the following steps : set up exterior-protected construction, purlin and steel upright columns around the foundation ditch; dig on basin pattern for the first time to the depths to structural plane of purlin, earthwork are unified dig beneath the designed to the surrounding medium plate in the foundation ditch, pour the surrounding medium plate; dig for the second time with basin pattern downwards from the position of foundation ditch medium plate to the bottom of the designed foundation ditch, pour the center island plate; after the center island plate meets the maintenance time request of plate, construct in sequence to close the medium plate, setting fetching holes; then use medium plate for support system, construct criss-cross structural upper plate and plates in inverse zones. This construction method is convenient, save labor force and resources, improves the progress of the project, shorten the construction period.

The invention discloses a time axis-based intelligent recommendation calendar and a user-based presentation method. According to the intelligent recommendation calendar, using data in the calendar are acquired according to the time axis, and the using data comprise browsing behaviors and browsing contents of a user; the above using data are synchronized to a backstage server in a log form, a user log using behavior is simulated, and a user log recommendation model is built; key words are obtained through extraction, the key words serve as index words for an event in the time axis, and a user dimension-based label system is built; and according to the label system, a data label for the user is obtained, the data label comprises a content which interests the user, and then, according to the data label, time reminding is completed in the calendar, and recommendation of a related content is completed. The time axis-based intelligent recommendation calendar and the user-based presentation method have high efficiency, classification and integration and collaborative filtering functions, intelligent recommendation can be carried out based on the content which interests the user, and precise online and offline event / content recommendation can be made according to time management habits and interests of the user.

The invention discloses a method for applying large-diameter well sinking by utilizing an underground shaft robot, which comprises the following steps: hanging a cutting edge ring into a foundation pit of a position on which well sinking is applied, and temporally locking and positioning the cutting edge ring through a descending device positioned outside the foundation pit; mounting a bottom ring strip above the cutting edge ring, and mounting a digging robot on the inner surface of the bottom ring strip; digging a soil body positioned below the foundation pit by utilizing the digging robot, mounting an upper ring strip above the bottom ring strip when a section of deep soil is dug; controlling the cutting edge ring to settle downwards by using the descending device, and reciprocating until the robot tunnels to preset depth. The method has the advantages that the digging robot can automatically dig so that the digging efficiency is high; moreover, by adopting hydraulic power, underwater operation is carried out; by using the descending device, a well sinking process of the ring strips is controlled, the sedimentation velocity and the posture of the ring strips can be effectively adjusted, and deviation is avoided.

The invention provides an OPTICS clustering algorithm based on a Spark big data platform, and relates to a computer information obtaining and processing technology. Parallel data is structurally partitioned, the optimal data set partitioning is obtained, a corresponding RDD is generated, neighbor sample numbers and core distances are calculated in parallel, partitions are subjected to parallel execution of the OPTICS algorithm to obtain a cluster sequence of the partitions, and the cluster sequence is obtained persistently; clusters are given to the partitions according to the cluster sequence, and samples can obtain global cluster numbers by combining the partitions. By means of the Spark distributed parallel technology, the optimal partitioning structure is found, and the cluster sequence of the partitions is obtained through parallel calculation. According to the OPTICS cluster sequence, a user can observe the inherent clustering structure of a data set from different levels of structures, the method can process a large data set which cannot be processed by a serial algorithm, and the time for obtaining the clustering result is greatly shortened.

The invention provides a software vulnerability discovery system and method based on attribute extraction and belongs to the field of computer safety. The system comprises a key code discovery module, a vulnerability analyzing module and a vulnerability deduction module. The method includes the following steps: extracting key codes of software to be tested; executing the software to be tested in the virtual machine environment and adopting a virtual machine fault injection engine and the key codes to conduct testing interaction and record a testing result; conducting deduction by combining the testing result and the discovery experience knowledge base. The system and the method effectively achieve complex causal relationship between uncertain software flaw and loopholes. The software vulnerability discovery system method based on the attribute extraction has certain advantages in the aspects of safety, flexibility and compatibility.

The invention discloses a system and a device of automatically searching a hot point video. The system comprises a video information base, a population parameter statistics module, an increment statistics module and a hot point video computation module. The video information base stores a mass of video information. The population parameter statistics module is used for counting total statistical magnitude of each population parameter statistics item of each of the video information in the video information base. The increment statistics module is used for counting newly increased statistical magnitude of each increment statistics item of each of the video information in a particular time period. The hot point video computation module is used for calculating weight of each property of each of the video information, weight of each population parameter statistics item of the population parameter statistics module and weight of each increment statistics item of the increment statistics module by using each video-weight calculation model. Hot weight value of the video information is obtained through the hot point video computation module according to each weight result obtained by calculation. A hot point video list is selected to be displayed according to the hot weight value of the video information. The system and the device of automatically searching the hot point video is capable of automatically generating hot point video searching result through acquisition of clicking of a user.

The invention discloses a fault early warning and life prediction method of escalator equipment. The method calculates the health status of an escalator system according to each module status of the escalator, the escalator health status is compared with the escalator abnormality time fitting function, the escalator operation time is obtained, and the remaining life of the equipment can be calculated according to a failure threshold of the escalator corresponding to the escalator operation time. According to fault early warning and life prediction method of escalator equipment, all kinds of algorithms adopted are designed based on equipment index analysis, the escalator index in algorithms is changed to other equipment indexes, the real time index data of the corresponding detection equipment is collected, so that the health evaluation status and the remaining life of the detection equipment. Therefore, the algorithm system is suitable for the prediction of each key equipment, and hasthe commonality.

The invention relates to a technology for reconstructing a network attack path based on a frequent pattern-growth algorithm, belonging to the technical field of network information safety and being suitable for an intrusion detection system (IDS) and other safety monitoring systems. In the invention, data of alarm event of the IDS and other security tools such as antivirus / scanner and the like are associated and fused into a complementary intrusion evidence so as to enable the attack per step to have a corresponding system state as objective reflection of attack effects; Bayesian network-based attack scenes are established on the basis of the data; frequent attack sequences are excavated from the attack scenes by adopting the frequent pattern-growth algorithm, thus improving the excavation efficiency and obviously reducing system expenses; and the excavated frequent attack sequences are associated once again so as to reconstruct the attack path and judge possible attack intentions clearly.

The invention discloses a vertical in-tunnel construction method of a multilayer transverse channel of an underground excavation station of a metro. The vertical in-tunnel construction method comprises the following steps: a, excavating a silo till below a bottom elevation of the transverse channel at the first floor, and temporarily sealing the bottom of the silo through section steel and C20 net spraying concrete; and b, setting up a working platform to carry out surveying and lining, and releasing a horsehead of the transverse channel at the first floor to excavate a contour line so as to complete construction of the transverse channel at the first floor. When the horsehead at the lower-layer transverse channel is destroyed, a ring is formed in the horsehead, so that deposition caused by break of the horsehead is reduced, that is to say, risk of breaking the horsehead is greatly reduced through a manner of forming the ring in the transverse channel and then breaking the horsehead.

This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to perform an excavation routine by excavating earth from a hole using an excavation tool positioned at a single location within the site. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, navigating the excavation vehicle over a distance while continuously excavating earth from a below surface depth, and preparing a digital terrain model of the site as part of a process for creating the excavation routine.

The invention provides an addressing class query word mining method and system. The method comprises that: primary domain URLs with the same domain names recorded in a click log of a user are normalized so that corresponding primary domain names are generated, and a query word set of the primary domain names is generated according to corresponding query words of the primary domain URLs; word segmentation is performed on the query words in the query word set, occurrence frequency of the obtained word segments is counted, and the longest word segment in the word segments with the highest occurrence frequency is confirmed to the corresponding core word of the primary domain names; and the query word set comprises the core word through confirmation and the query word with the highest query frequency is a corresponding addressing class query word of the primary domain names. According to the technical scheme provided by the invention, an addressing class query word set can be automatically mined and generated, and addressing class Bad Case mining recall rate is enhanced.

The invention relates to a fault early warning system of a wind turbine generator system. The fault early warning system comprises a real-time monitoring module, an early warning model module, an early warning result feedback module and a knowledge database module. The real-time monitoring module is used for reading parameters of a blower fan in real time and transmitting the parameters to the early warning model module for analysis, if an analysis result reaches early warning standards, an early warning mechanism is triggered, the information is transmitted to the early warning result feedback module, the feedback result is recorded by a worker into the knowledge database module; the results of the early warning result feedback module are continuously accumulated by the knowledge database module, when accuracy of the early warning results is lower than 60%, the result of the knowledge database module is fed back to the early warning model module to carry out model re-training. The fault early warning system is advantaged in that early warning in advance before fault generation can be realized, and improvement measures and maintenance schemes can be provided after early warning according to accurate cases of the knowledge database module; according to knowledge database accuracy calculation, if a historical data training model is not practical, new data is employed by the early warning model as training data for re-training, and accuracy of the early warning model is improved.

The invention relates to a device and a method for vertically transporting earthwork by a reverse construction method, which belong to the field of civil construction. In the device, segmental belt-type conveyor belts are adopted as earthwork transporting tools in a deep foundation pit; the conveyor belts pass through reserved holes of floor slabs on each floor; and the earthwork is transported to a dump truck obliquely from the bottom to the top by the conveyor belts. The device is formed by connecting independently segmented and obliquely arranged belt-type conveyor belts end to end; and each floor is provided with at least one conveyor belt which consists of an electric motor, a conveyor belt rack, an unloading tank, a scraping plate, a roller wheel, a roller wheel shaft bracket, a belt, a feeding funnel and an emergency brake device. The device and the method for vertically transporting the earthwork by the reverse construction method can effectively increase the earth volume in single vertical transport, effectively improve excavation efficiency, reduce excavation machines, reduce excavation cost, and simultaneously, reduce the influence of the construction of underground excavation on the simultaneous construction of an upper structure to the minimum.

The invention discloses a method of item-all-weighted positive or negative association model mining between text terms and a mining system applied to the method. The method comprises the following steps of preprocessing by using a Chinese text preprocessing module to establish a text database and a feature word item library; mining item-all-weighted feature word candidate item sets from the text database by utilizing a feature word frequent item set and negative item set mining implementation module, calculating a weight dimension ratio, and cutting out uninteresting item sets by adopting a multi-interestingness threshold value pruning strategy to obtain an interesting item-all-weighted feature work frequent item set and negative item set model; mining an effective item-all-weighted positive or negative association rule model from frequent item sets and negative item sets by utilizing an item-all-weighted positive or negative association rule mining implementation module between terms, and outputting the mined positive or negative association rule model to a user by utilizing an item-all-weighted association model result display module between terms. By applying the method and the system, unnecessary frequent item sets, negative item sets and association rule models can be greatly reduced, Chinese feature word association rule mining efficiency is improved and a high-quality association model between Chinese terms is obtained.

The invention relates to an intelligent diagnosis system based on metering device failures. The intelligent diagnosis system comprises a data collecting and monitoring module, a meta event information generating module and a failure diagnosing and decision making module, wherein the data collecting and monitoring module is used for collecting and uploading related data according to collection frequency and transmission modes, the meta event information generating module is connected with the data collecting and monitoring module and used for comprehensively analyzing and preprocessing the related data collected through the data collecting and monitoring module, matching the collected related data according to the archival information of a user and generating meta event information through a meta event diagnosing model; the failure diagnosing and decision making module is connected with the meta event information generating module and used for carrying out relevance matching according to the meta event information provided by the meta event information generating module to achieve intelligent diagnosing of the metering device failures. Compared with the prior art, the intelligent diagnosis system has the advantages that information is effectively integrated, redundant information is removed, the diagnosing efficiency is improved, and the diagnosing accuracy is high.

The invention discloses a frequent item set mining method and system supporting differential privacy, and belongs to the field of computer data privacy protection and data mining. The method comprises the steps of processing an original data set by adopting a transaction truncation method, and avoiding privacy leakage in the truncation process by using an exponential difference mechanism-based method; then constructing a tree structure, wherein each node corresponds to an item of a transaction, frequent information on the transaction is stored in a node corresponding to the last item of the transaction, and the support degree of each node is initialized by using Laplace noise to avoid the privacy leakage in the tree construction process; and converting the constructed tree into an FP tree, so that a frequent item set can be mined by using an FP-Growth method. According to the method and the system, the released frequent item set can meet security demands of the differential privacy; compared with an original frequent item set, the released frequent item set has relatively high similarity with the original frequent item set and relatively high data availability; and compared with a conventional algorithm, higher efficiency is achieved.

The invention discloses a user tag determination and information pushing method and device. The method includes the steps that by configuring a label rule and a label feature library of to-be-mined user labels, user behavior data is collected, the configured label rule and the label feature library are tested by means of the user behavior data so as to determine whether the configured label rule and the label feature library meet conditions of the user labels or not, quick mining of the user labels is achieved, and the mining efficiency of the labels is effectively improved. Meanwhile, the precise user labels can be configured for different users according to the matching relationship between the user labels and a target object, a foundation is laid for subsequent business popularization, and the efficiency of responding to business requirements is improved.