622 results about "Classification treatment" patented technology

An automated data management system and method for logging, processing, and reporting a large volume of data having different file types, using different versions, stored on different media, and / or run by different operating systems, includes a first processor for restoring a plurality of received data files, the data files being capable of being different file types; a file organizing / categorizing processor for organizing the received data files into data slices, each data slice including an identification number and a descriptor that describes characteristics of the received data file; a file logging processor for logging the received data files into a first database based on the data slices; a data uploading processor for uploading the first database to a second database; a de-duplicate processor for calculating a SHA value of the received data files to determine whether the received data files have duplicates and flagging duplicated data files in the second database; an image conversion processor for converting at least a portion of the received data files into image files; and a second processor for exporting the image files.

The system and method facilitate the control and management of information and actions related to the computerized scanning, categorization, processing, storage, and retrieval of paper documents and electronic document images for the purposes of creating electronic data; data entry; data capture; data classification and categorization; and document-, file-, and records-management. The systems and methods facilitate the conversion of paper documents into electronic images and into more useful forms.

The invention provides a data processing method, apparatus and system based on block chain technology. The method comprises the following steps: collecting information from information sources and summarizing the information; classifying the information according to the attributes of the information, and carrying out data processing on the different types of information after classification; packaging processing results of the different types of information to generate block basic unit information; and organizing at least one piece of block basic unit information to enter a new block according to preset conditions, and linking the new block to the previous block in a block chain. The technical scheme provided by the invention encrypts plaintext containing complex variable-length information into ciphertext by fixed-length calculation, and merges the plaintext containing fixed-length information and the ciphertext in the block chain, thereby guaranteeing the storage and non-manipulation of the plaintext in the entire block chain; and classification processing and fixed-length calculation are carried out on the complex variable-length information and the fixed-length information contained in the plaintext, so that the objective of writing the complex and variable-length information in the block chain in the block form is achieved.

The invention discloses a classified processing method of internet public information. The method comprises the following steps: selecting a classified public information text as a training text, and parsing words; selecting and screening nouns and verbs, acquiring feature words by extraction, vectorizing the training text, then acquiring a PCA transformation feature matrix, a BP neural network model, and a decision tree rule; performing dimension reduction on vectors of the vector matrix of the public information text to be classified by the PCA transformation feature matrix, and transforming the vectors by the BP neural network model to obtain an output vector which has the same number of dimensions as the classified number, and then performing matching by the decision tree rule, and determining that the public information text to be classified belongs to the public information category marked by the rule if the matching is successful. As the PCA transformation converts a feature word space related to a high dimension into a low-dimensional orthogonal feature space, the disadvantage of inaccurate classification is solved; meanwhile, the decision tree rule is used for classification without data similarity comparison so that a plurality of data sources can be processed in a short time.

The embodiment of the invention discloses a building refuse treatment regeneration system, including a classification stacking, sorting processing system, a classification processing system and a plurality of storage bins, wherein, the classification processing system includes at least two parallel crushing screening process production lines and water circulating systems, each crushing screening process production line includes a feeder, crusher, as well as a screening machine connected in series in sequence, and a plurality of outlets of the screening machine are respectively connected to the plurality of storage bins through conveyor belts. By adoption of the building refuse treatment regeneration system of the embodiment of the invention, bricks, tiles, dust and sand and concrete blocks and the like in the building refuse can be divided into at least two production lines for parallel processing, which greatly enhancing the production efficiency and the purity of recycled aggregates, so that the recycled aggregates can be applied to a variety of uses, reproduced into a variety of high-quality recycled products, reducing the waste of resources and minimizing pollution that will be probably caused to the environment.

The invention provides an efficient separation method for low-grade and complex iron ores. The method is characterized in that the complex iron ores of different grades and species are classified, so as to obtain lump ores and mineral powder which are balled, dried and preheated; reduction roasting, cooling, ball milling, magnetic separation, ball milling and magnetic separation or reverse flotation are performed in turn, so as to obtain iron ore concentrate or reduced iron powder; classification treatment is to crush and screen the iron ores with iron-containing grade between 50 and 56 percent and then dry and preheat obtained ores; fine-grained mineral powder is ground, washed, ground, deslimed and separated so as to obtain the iron ore concentrate and slime containing 58 to 60 percent of iron; the slime which is washed, deslimed, and separated is dewatered and dried and is added to and well mixed additives, so as to be balled then; the iron ores with the iron-containing grade between 40 and 50 percent are crushed and screened so as to obtain the lump ores which are directly dried and preheated, while the fine-grained mineral powder is obtained through dry-type grinding and then is added to and well mixed the additives so as to be balled then; and the iron ores with the iron-containing grade between 25 and 40 percent are crushed and screened so as to obtain the lump ores which are dried and preheated, while the fine-grained mineral powder is subjected to grinding, gravity separation or high-gradient magnetic separation and reverse flotation, so as to obtain coarse iron concentrate powder which is added to and well mixed with the additives and then is balled.

The invention relates to a flight dynamic information data integrator and a processing method, belonging to the field of civil aviation technology. The flight dynamic information data integrator comprises a power-supply system, a microprocessor, an input control display unit, a communication unit, a data receiving unit, a data processing unit and a data storage unit; wherein, the data receiving unit is internally provided with a receiving process program module which can realize real-time physical reception of the transmitted data and executes data decompression, data source feature recognition and classification treatment to realize data interchange and share. The processing method of the integrator comprises dynamic information of production departments such as air traffic control (ATC), airports and airline companies are integrated into a platform database for supplying data service; standard flight information is formed by integrating the received related data of the flights and then stored in a data center; meanwhile, the integrative process is monitored, and the integration results are analyzed. The invention can realize data interchange and share, and provides complete, accurate and timely data service.

The invention discloses an object-oriented remote sensing image coastline extraction method which belongs to the field of full automatic remote sensing image coastline extraction. The steps are as follows: carrying out filtering treatment on a remote sensing image; selecting the segmentation algorithm to segment the remote sensing image; utilizing sample points for classifying the remote sensing image after segmentation; utilizing the seed growth method for extracting a seawater region; and finally utilizing the corresponding judgment criterion to extract a coastline. By utilizing the method disclosed by the invention, the accuracy of the existing coastline extraction algorithm can be improved, the correct rate of seawater extraction after segmentation and classification treatment throughthe object-oriented method is improved and the accuracy of the coastline extraction is ensured. As the coastline changes frequently, the method can provide convenience for maintenance and updating ofcoastline information of all levels of national fundamental geographic information databases.

The invention discloses an urban sewage treatment system and purification method and belongs to the technical field of sewage treatment. The sewage treatment and purification method comprises the steps of collection, physical precipitation, chemical precipitation, anaerobic biological treatment, anoxic biological treatment, aerobic biological treatment, adsorption, disinfection, ultrafiltration membrane filtration and sludge treatment in sequence. According to the method, a physical precipitation method, a chemical precipitation method and a biological purification method are used comprehensively to perform step-by-step classification treatment on different pollutants, the purification efficiency is high, the effluent quality is good, the nitrogen and phosphorus treatment capacity is higher, operation and maintenance are convenient, management is simple, and popularization and use can be realized.

A multi angle measuring system for a display comprises a MURA image capturing unit, a MURA image processing unit and a data base unit, using a multi angle image capturing mechanism to capture the MURA phenomenon of the display, with a MURA image processing program for image analysis and identification classification treatment, providing quantified MURA inspection, establishing quality interactive handling analytical database, to provide friendly interface and interactive inquiry function. Through oblique angle calibration to improve view depth optical structure and ladder infidelity program image restoring establishes a quality interactive process analytical database, to provide a measuring system for the application of production line in an objective and stable way.

The invention discloses an alarm monitoring strategy analysis method based on a data mining technology and belongs to the field of communication alarm monitoring. Through data mining, valuable knowledge can be extracted from enormous fuzzy data comprising noise, alarm data of a communication network is enormous and dynamic and is rich in knowledge, the alarm data of the communication network is mined without reliance on a network structure, and dynamic change of the network can be adapted. Data mining comprises the following steps: obtaining and preprocessing the alarm data; converting the obtained alarm data into a set of transaction items, and carrying out frequent item set data mining by use of a correlation algorithm; and through combination with actual application, performing compression, merging and classification processing on a result of a frequent item set. According to the invention, through merging and converting alarms, the multiple alarms are merged into one alarm with a larger information amount so as to replace the multiple alarms, and assistance is provided for network management personnel in analyzing fault information and rapidly positioning faults.

The invention discloses a digital line graph mapping method, relating to the fields of mapping and remote sensing. The digital line graph mapping method comprises the following steps of: verifying flight by using onboard LIDAR (Laser Intensity Direction and Ranging) equipment to realize calibration of equipment parameters; establishing a point cloud data error model according to an onboard LIDAR point cloud generation principle, acquiring a parameter correction value according to overall adjustment to realize integral accuracy optimization for point cloud data, and acquiring a point cloud with optimized accuracy; carrying out filtering and sorting treatment on the ground and buildings, acquiring a ground point cloud and a building point cloud, and establishing a digital ground model according to the ground point cloud; carrying out aerial triangulation encryption on an air photo according to the digital ground model and POS (Position and Orientation System) auxiliary positioning information to realize integral accuracy optimization for fixed-position and fixed-attitude data of the air photo, and acquiring the air photo with optimized accuracy; accurately matching the point cloud with the optimized accuracy and the air photo with the optimized accuracy; and establishing a mapping environment of a point cloud and air photo fused mode, realizing semi-automatic extraction of vector lines and total-manual extraction of residual ground feature elements in the fused mode mapping environment, and generating a digital line graph product.

The invention discloses a classification rule mining method under a cloud computing environment. The classification rule mining method is characterized in that a master-slave type organization structure consisting of a control center and a plurality of slave servers is adopted, and comprises the following steps of: dividing, by the control center, a data set to be classified into a training sample and a test sample, and distributing each of data blocks of the same size which are formed by uniformly dividing the training sample to one processing unit; training, by the processing units, the data blocks, by using a genetic algorithm to obtain an atomic rule for classification; and finally, reducing the atomic rule by a classifier, and selecting a reduction result which meets classification accuracy requirement as a final result of the classification rule mining. The classification rule mining method is suitable for data classification on distributed data storage under the cloud computing environment; distributed parallel processing of data classification tasks under the cloud computing environment can be performed; and the classification rule mining method has a positive effect on the classification processing problem of mass data under the cloud computing environment.

The invention discloses an urban waste classification treatment monitoring system based on the Internet of Things. The system provided by the invention contains a central processing module; a satellite positioning module which forms a wireless connection with the central processing module; several wet waste treatment monitoring systems which respectively form a wireless connection with the central processing module and are used to monitor the wet waste treatment flow of a wet waste recycling bin, a regional wet waste centralized recycling station, a wet waste transport station, a wet waste transport vehicle and a wet waste disposal factory at real time; and several dry waste treatment monitoring systems which respectively form a wireless connection with the central processing module and are used to monitor the dry waste treatment flow of a dry waste recycling bin, a regional dry waste centralized recycling station, a dry waste transport station, a dry waste transport vehicle and a dry waste disposal factory at real time. According to the invention, dry and wet wastes are separated for processing so as to minimize waste moisture and burning fetor, increase burning calorific value, promote energy conversion and raise waste utilization rate.

The invention relates to a neural network training method and device and an image processing method and device. The training method comprises the following steps: carrying out classification processing on a target image in a training set through a neural network to obtain a prediction classification result of the target image; and training the neural network according to the prediction classification result, the initial category label and the correction category label of the target image. According to the embodiment of the invention, the training process of the neural network can be supervisedby initializing and correcting the category label, and the training process and the network structure are simplified.

The invention relates to the field of garbage classification treatment, and specifically relates to an intelligent garbage classification treatment system. The intelligent garbage classification treatment system comprises a data control center, a garbage classification terminal, a garbage treatment terminal and a maintenance set, wherein the data control center is used for recording user information file, garbage treatment data and maintenance information; the garbage classification terminal comprises an information input part, a recognizing code generating part, an information transmission part and at least more than two garbage storing areas; the garbage treatment terminal is in communication connection with the data control center through an information monitoring part; the information transmission content includes garbage treatment information and terminal state information which are recorded into the garbage treatment data after being transmitted to the data control center; the maintenance set is provided with an ID identification card and a communication device.

The invention discloses an NB-IoT-based wisdom tip water quality monitoring system and method. The system comprises an intelligent monitoring system, a cloud service center, an NB-IoT module and a wisdom tip, wherein the wisdom tip collects to-be-monitored water quality original data, processes the data and transmits the data to the cloud service center through the NB-IoT module; and the cloud service center performs management and analysis on the data and finally transmits the data to the intelligent monitoring system for performing trend prediction and classification processing. The method comprises the steps that the wisdom tip collects the to-be-monitored water quality original data and processes the data by adopting an edge calculation method; the processed data is transmitted to thecloud service center through the NB-IoT module; the cloud service center performs the management and analysis on the data and finally transmits the data to the intelligent monitoring system; and the intelligent monitoring system performs the trend prediction and classification processing on the received data, thereby providing data services for water quality monitoring personnel. The water qualitychange can be correspondingly processed intelligently; and referable processing schemes are provided for the monitoring personnel and field working personnel.

The invention provides a text based commodity classification treatment method and system. The text based commodity classification treatment method comprises extracting text format of commodity data from a commodity database; grouping the commodity data and performing feature extraction; constructing out a classifier through a training document according to a probability model; performing classification on the commodity data. According to the text based commodity classification treatment method and system, the automatic classification on the commodity data is achieved and the classification speed is high and the text based commodity classification treatment method and system is suitable for the commodity classification treatment of high-volume electronic commerce websites due to the fact that the machine learning mode is adopted.

Deployment of new elements in a computer network can result in development of patch kits adapters, and other software and trigger corresponding regressive test efforts. In a storage area network, a method is disclosed for defining a general, extensible model of a manageable entity for use in management of the entity. The method includes obtaining a set of attribute values related to the manageable entity in relation to the storage area network. A deployment engine identifies corresponding entity categories within a storage area network entity model that contains attribute definitions that correspond to respective attribute values in the set of attribute values obtained from the manageable entity. The deployment engine assigns the respective attribute values of the manageable entity to the corresponding respective attribute definitions identified in the model. The deployment engine then determines if all attribute values of the manageable entity have been assigned. If unassigned attribute values remain, a classification processor defines new entity categories to contain new attribute definitions, and assigns the unassigned attributes value to the new attribute definitions contained in the new entity category.

The invention relates to an intrusion detection method and device for an industrial control system, computer equipment and a computer-readable storage medium. The method comprises the steps: extracting an original data set of the industrial control system from a network data set of a communication protocol of the industrial control system; obtaining a training data set and a test data set from theoriginal data set; performing feature dimension reduction on the training data set and the test data set by using a principal component analysis method to obtain a training data set subjected to feature dimension reduction and a test data set subjected to feature dimension reduction; training the training data set subjected to dimension reduction based on an intrusion detection model to obtain aclassification model; and inputting the test data set subjected to feature dimension reduction into the classification model for classification processing to obtain an intrusion detection result of the industrial control system. According to the scheme, the feature dimension reduction is carried out through a principal component analysis method, redundant information is removed, the calculated amount is reduced, and therefore the technical problem that a traditional technology industrial control system intrusion detection method has a long training time is solved.

The invention relates to the field of preparation of lightweight ceramsites, in particular to a lightweight ceramsite prepared from waste foundry ash and waste sand, and a preparation method of the lightweight ceramsite. The lightweight ceramsite is prepared from the following components in parts by weight: 95 parts of waste foundry sand and waste ash, 3 to 7 parts of bauxite, 0.1 to 0.5 part of rubber powder and 0.1 to 0.3 part of polyvinyl alcohol, wherein the weight ratio of the waste foundry sand to the waste ash is (8 to 2) to (9 to 1). According to the preparation method disclosed by the invention, the waste foundry sand and the waste ash are directly used for preparing the lightweight ceramsite, and classification treatment of the waste ash and the waste sand are not needed; in addition, special requirements on the granularity of the waste ash and the waste sand are avoided, and all the waste foundry ash and waste sand can be disposed by using a set of equipment, so the preparation method has the advantages of simple preparation technology, small input quantity of the equipment and few hardware requirements on sites and the like; meanwhile, resources are saved and environmental pollution is reduced by secondary utilization of the waste foundry ash and the waste sand.

The invention discloses an intelligent signal frequency-conversion collection method which supports various communication interfaces, constructs a communication protocol library and supports an automatic loading communication protocol to realize interaction with equipment. Each equipment can be configured with different collection frequencies, and a collection task can be automatically or manually triggered. The dynamic change of the collection frequencies is realized according to the condition of signal change, and the sampling frequency is lowered when data are not changed. When an alarm and a fault occur and the data exceed a set threshold or a change rate, the data are automatically collected at high frequency. Aiming at various communication protocols of MODBUS, CDT and the like and the modes of a nested protocol, a condition judgment protocol, a plurality of continuous messages and the like, automatic adaptation and collection is carried out. Classification processing is carried out on the collected data, real-time triggering collection and revelation is carried out on alarming information, intelligent analysis is carried out on monitoring data, and intelligent processing is carried out on the classified analysis and the like of different classes of signals of single equipment and the mixed signals of a plurality of equipment.

The invention relates to an intrusion detection method and device for industrial control system based on a convolutional neural network, a computer device and a computer readable storage medium, and the method comprises the steps: extracting an original data set of an industrial control system from a network data set of a communication protocol of the industrial control system; dividing the original data set into a training data set and a test data set according to a preset proportion; training the training data set through a convolutional neural network classification model to obtain an optimal classification model; and inputting the test data set into the optimal classification model for classification processing, and obtaining an intrusion detection result of the industrial control system. According to the scheme, the classification model with excellent performance is designed through the convolutional neural network, massive data can be processed quickly, multi-classification can be performed, and the classification performance is more accurate, so that the technical problem of poor classification precision of an industrial control system intrusion detection method in the priorart is solved.

The invention relates to an intelligent garbage classification method and a modular intelligent garbage classification processing system. The classification method comprises the following steps: (1) acquiring garbage data to be classified; (2) preprocessing the obtained junk data to be classified; and obtaining junk data which is easy to identify by the server. (3) sending the garbage data which is easy to identify by the server to the server; and (4) sending the information of completing the garbage category judgment to the user by the server, and prompting the user of the category of the garbage to be classified. The processing system consists of a cloud computing server, a CPU (Central Processing Unit) for computing data, a plurality of garbage cans, a display screen capable of inputting instructions, and a sensor for generating image, sound and electromagnetic data. The modular garbage classification system is designed, the number and types of the garbage storage modules can be defined by a user so as to provide higher flexibility, the cost is low, and the user experience can be well improved.

The invention relates to a system and a method for the centralized classification treatment of steel metallurgic dust mud, which belong to the technical fields of the comprehensive utilization and the innocent treatment of metallurgical industry solid waste. The system comprises an impurity removing system, a homogenizing system, a granulating system and a sintering proportioning system, wherein an outlet of the impurity removing system is connected with an inlet of the homogenizing system, an outlet of the homogenizing system is connected with an inlet of the granulating system, and an outlet of the granulating system is connected with an inlet of the sintering proportioning system; the impurities in high-impurity materials are firstly removed through the impurity removing system, the materials and the rest ferruginous dust mud together enter a mixing system for homogenization treatment, the homogenized materials enter the granulating system for granulation treatment, and the granular materials made by the granulating system enter the sintering proportioning system and are used as sintering raw materials. The system has the advantages of simple and practical technology, large processing capacity, cleanness, environmental protection and lower initial investment and running cost, and fully expresses the ideas of cleaner production and cyclic economy in iron and steel industry.

The invention relates to a water flotation regeneration process of agricultural waste plastics, comprising the following steps: (1) the agricultural waste plastics are sorted, cut, crushed and pulverized to obtain waste materials after classification treatment; (2) the waste materials after classification treatment are circularly washed in a cleaning pool to obtain clear waste materials and sewage, and then the sewage is discharged into a purification tank, filtered and then recycled; (3) the clear waste materials are dehydrated and then enter a water flotation separation device for flotationseparation to obtain a floating object and precipitate; and (4) the floating object obtained in step (3) is filtered with a sieve, lifted and dried and then enters a granulator and a pelletizer sequentially to obtain plastic A regeneration particles with diameter of 0.5cm and uniform size, and the precipitate is dried, mechanically grinded and filtered with the sieve to obtain plastic B regeneration powder with fineness of 20 mesh sieve. The water flotation regeneration process has convenient operation and high separation efficiency, reduces errors of manual identification according to materials and improves utilization ratio of the regeneration plastics.

The invention discloses a labeling method and device for web page topics. The method includes the steps that based on titles and main bodies of web pages, topic feature vectors of the web pages are acquired; classification processing is performed on the topic feature vectors through a classifier which is obtained through training in advance; whether types which the topic feature vectors belong to exist is judged; if yes, the web pages are labeled as the types which the topic feature vectors belong to; otherwise, the web pages are labeled as web pages to be labeled; furthermore, clustering processing is performed on the multiple web pages to be labeled; the type of each cluster is obtained through analysis; the web pages to be labeled are labeled as the types of the clusters which the web pages belong to. By the adoption of a supervised classification method and unsupervised clustering method cascading mode, the topics are automatically acquired from the web pages, the web pages are labeled, and the labeling efficiency and accuracy of the web page topics are effectively improved.

The invention provides a step calculation method, which reduces the interference of body situation of a user in step calculation and improve the step calculation accuracy. The method comprises the following steps: based on a step calculation device with sound recognition function, starting walking, prompting the currently various walking states of the step calculation device, and collecting the user step parameters by a sensor; setting an acceleration threshold for step calculation; collecting the acceleration parameter during walking through the sensor, and the like. Information of walking status corresponding steps can be obtained by combining the classification of acceleration values according to the walking states and the check and countering of an envelope line, the user experience is increased, and the step calculation accuracy of the user with weak or bad body status can be improved.

The invention discloses a wastewater treatment and recycling technology for aluminum profile production enterprises. According to different pollutants, the wastewater produced by the aluminum profile production enterprises can be divided into three types to be treated: chromium-containing wastewater, high fluorine-containing wastewater and low fluorine-containing wastewater. The three types of wastewater carry out classification treatment and splitting treatment: (1) the chromium-containing wastewater is secondarily processed to remove hexavalent chromium and other harmful impurities; the processed water can be 100 percent recycled; (2) most of the fluorine and aluminum in the high fluorine-containing wastewater can be removed by coagulation precipitation method; part of the first treated wastewater can be recycled and used in the related process which has low requirement to the quality of water; other wastewater is secondarily processed by adopting composite of modified activated carbon and modified zeolite to further remove the fluorine and chemical oxygen demand COD; then part of the wastewater is recycled and the other part achieved standard is discharged; (3) most of the aluminum in the low fluorine-containing wastewater is removed by neutralization precipitation method; then the wastewater is secondarily processed by adopting the composite of the modified activated carbon and the modified zeolite to further remove the pollutants in the wastewater; the wastewater can be all recycled.

The invention discloses a safe distance calculation method for the electrified operation of a transformer substation. The method comprises the following steps of carrying out data acquisition by utilizing a laser radar point cloud, and subjecting point cloud data to classification treatment, wherein during the data classification, the point cloud data are subjected to the intelligent analysis andcalculation or the manual calculation of electrified wires, ground equipment facilities and electrified operation safety distances. According to the calculation method of the invention, electrified wires and equipment safe operation distances are comprehensively detected, so that the working safety of the personnel during the construction process in the transformer substation is ensured. The operation risk is reduced, and the requirements of the construction safety specification in the transformer substation are met. The above safe distance calculation method for the electrified operation of the transformer substation is different from existing universal point cloud segmentation algorithms, wherein the characteristics of the transformer substation are fully considered. The method is aimingat target features, such as the features of wires, equipment and the like in the transformer substation, and serves as a special treatment method for the surface features of the transformer substation.