799results about How to "Improve digging efficiency" patented technology

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.

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.

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 an excavator bucket material dynamic weighing device which can carry out weighing operation under a working state, and excavating efficiency is high. The excavator bucket material dynamic weighing device comprises a weight collecting unit, a microprocessor and a weighing displaying unit. The weight collecting unit comprises tilt angle sensors, gyroscopes and pressure sensors which are arranged on a front cavity and a back cavity of a bucket lever oil cylinder and a large arm oil cylinder of an excavator. The tilt angle sensors and the gyroscopes are arranged on a large arm, a bucket lever and a bucket of the excavator. The microprocessor is provided with a data collecting module and a data analyzing module. The output end of the microprocessor is connected with the weighing displaying unit. The tilt angle sensors, the gyroscopes and the pressure sensors are connected with the data collecting module. The input end of the microprocessor is connected with a signal triggering device which is used for triggering the data collecting module of the microprocessor to collect data or stopping data collection. The signal triggering device is in triggering-control connection with the input end of the microprocessor. The invention further discloses an excavator bucket material dynamic weighing method.

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 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.

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 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 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.