90 results about "Fuzzy identification" patented technology

The invention provides a method of judging a mode of transportation of a train chain based on a GPS (Global Positioning System) positioning and fuzzy theory. The method comprises the steps of carrying out GPS positioning to a traveler, and collecting personal attribute data; preprocessing the collected GPS data, and dividing a travelling section to a behavior of the traveler; carrying out fuzzy identification on the travelling section, and judging the travelling way of the traveling section; and finally, judging a travelling way which is judged to the travelling of a motor vehicle again, and judging whether the travelling way is either a car travelling way or a bus travelling way. According to the method provided by the invention, a smart mobile phone, a GPS positioning technology and other technologies can be combined to be convenient and comprehensive to obtain the travelling data of the traveler and the personal attribute data, dividing the travelling of the traveler practically, and analyzing and processing the aforesaid information based on the fuzzy theory, the personal attribute data of the traveler and the like; furthermore, compared with the prior art, the mode of transportation of a resident can be more accurately obtained, and the effectively data references can be provided to traffic rules, traffic demand forecasting and the like.

The invention relates to the technical field of electronic information, in particular to a refrigerator food information management device and method. The refrigerator food information management device and method for automatically identifying food information are utilized in the invention. The refrigerator food information management method comprises the following steps of: collecting food colors, outlines or food bar code information by a video collecting module; carrying out fuzzy identification by a main processor, judging the food bar code information or image information and comparing with a comparison bar code table and comparison image information stored in a memory; then sorting foods according to keyboard and touch screen module settings; and displaying related information via adisplay module. The refrigerator food information management device and method are mainly applied to the field of refrigerator food management.

The invention discloses a household electrical appliance and a control system thereof. The system comprises the household electrical appliance; the household electrical appliance comprises a main control panel, an audio acquisition module, an identification module and a loudspeaker; the audio acquisition module is used for acquiring voice information of a user; the identification module is used for identifying the voice information of the user to generate a voice instruction, and sending the voice instruction to the main control panel; the loudspeaker is used for playing a response message of the voice instruction; the system further comprises a cloud server; and the cloud server is used for providing an identification result for the identification module. According to the control system of the household electrical appliance provided in the embodiment of the invention, the voice information is intelligently identified through the identification module; fuzzy identification of the voice information can be realized; furthermore, the user does not need to say the complete control instruction; operation is easy; therefore, the user can conveniently configure the control instruction in a personalized manner; the user experience is improved; furthermore, the control instruction sent by the user through localism can be identified through a localism database of the cloud server; and thus, the household electrical appliance can be conveniently and rapidly controlled to work.

The invention discloses a rapid digital imaging fuzzy identification and restored image quality assessment method, and relates to a fuzzy identification and restored image quality assessment method, for solving the problems of poor real-time performance, incapability of effective identification of a blurred image and a clear image and effective assessment of an image restoration result, and instable output result after fuzzy restoration processing by use of a conventional method. The method is realized through the following steps: 1, obtaining a gradient image G (i, j); 2, calculating an average gray scale gradient value; 3, obtaining statistical distribution information of the gradient image; 4, performing threshold determining on BIM; 5, obtaining a restored image; 6, generating reference images F1 and D1; 7, calculating brightness similarities, contrast similarities and structural similarities between the reference images and an image to be assessed; 8, calculating g(F(i, j), F1) and g(D(i, j), D1); 9, obtaining a non-reference-image assessment index; 10, determining the non-reference-image assessment index; and the like. The rapid digital imaging fuzzy identification and restored image quality assessment method is applied to the field of fuzzy identification and restored image quality assessment.

The invention discloses a hybrid power bus driving condition forecasting method based on an internet of vehicles, and belongs to the technical field of modern transportation. The hybrid power bus driving condition forecasting method is characterized by including steps that real-time vehicle position information and running data are matched and stored; the position information of a vehicle is transmitted in real time, the position information of vehicles around the vehicle is received, and front vehicles which run in the same direction and on the same road with the vehicle and are positioned in front of the vehicle by certain distances are selected; the front vehicles separated from the vehicle within a certain distance transmit historical data to the vehicle; forecasting weights of driving parameters of the front vehicles to the driving condition of the vehicle are determined according to the distances between the front vehicles and the vehicle, and forecast characteristic parameters of the driving condition of the vehicle are computed according to the forecasting weights and characteristic parameters of the front vehicles; the driving condition within a certain distance in front of the vehicle is identified and forecast according to the forecast characteristic parameters of the driving condition of the vehicle and a fuzzy identification model; and control parameters of the vehicle are adjusted by an HCU (hybrid control unit) according to a forecast result. The hybrid power bus driving condition forecasting method has the advantages that lagging of a traditional method is eliminated, forecast accuracy is improved, and accordingly fuel economy and emission performance of the vehicle are improved.

The invention provides an adaptive cascade PID control method. In the method, based on conventional cascade PID control, an adaptation module is introduced into a cascade PID control system, and control parameters of a master controller in the cascade PID control are directly generated by an online fuzzy identification method and a recursive least square algorithm according to the historical information of the control system, so that the robustness and adaptive capability of the cascade PID control system are improved; and in the process of online identifying the control parameters of the master controller, the influence of a secondary controller to the control performance of the system is reflected by the output of a main loop of the cascade PID control system, and good control effect can be obtained only by performing online regulation on the control parameters of the master controller in the system.

In soft measurement technology frame, the easy-to-measure reliable pressure difference fluctuation signal is adopted as auxiliary variable in detecting flow pattern of two phase flow as the main variable. The acquired pressure difference signal is wavelet analyzed, corresponding characteristic values are extracted, and the characteristic values are used in fuzzy identification of the flow pattern of two phase gas/liquid flow in horizontal pipe. The key soft measurement model is established by means of combining the wavelet analysis technology and fuzzy pattern identifying technology. Then, one flow pattern identifying system for two phase gas/liquid flow is established, and the system consists of test pipeline, pressure sampling hole, pressure sampling pipe, pressure difference sensor, amplifier, data acquiring card, microcomputer and printer. The detected pressure difference signal is processed in the system for pattern identification of two phase gas/liquid flow.

The invention belongs to the technical field of drilling safety, and discloses a reservoir gas drilling safety risk analysis system and method based on a BP neural network. A gray correlation analysisof reservoir gas drilling risk identification is carried out; fuzzy identification of the reservoir gas drilling risk identification is carried out; the invention aims at the engineering practical problem of risk control of a gas drilling reservoir, the method and software achievement for real-time observation and prediction of gas drilling accident identification are established through basic theory analysis, model establishment and computer simulation analysis by combining modern information acquisition, data processing, risk intelligent identification and management technologies to reducethe possibility of safety risk occurrence to the greatest extent. According to the invention, a drilling accident identification method based on gray correlation degree is provided by utilizing a graycorrelation analysis method. The identification example shows that the method of risk prediction with grey correlation degree is feasible and has the advantages of small calculation amount, simplicity and convenience, reliable result and the like.

The invention discloses a dissolved oxygen control method based on a fuzzy neural network. The method comprises the following steps: S1, modeling is carried out; S2, fuzzy identification is carried out, and a fuzzy identification method is adopted to identify the structure and parameters of an object model; S3, a clustering method is adopted to determine the number of rules; S4, a neural network is used for learning reasoning data of an expert, a fuzzy reasoning rule is acquired, and each connection weight is adjusted at the same time; S5, after a least square method is used for order identification, a transitive closure method is used for clustering analysis according to a fuzzy similarity relation; S6, a Smith predictor is introduced; and S7, two independent control circuits of blower pressure and oxygen dissolution are adopted. The wastewater treatment effects are good.

The invention relates to a power transmission and transformation project cost dynamic control target calculating system and a calculating method. The method comprises the steps that a power transmission and transformation project cost data set is established; data preprocessing is carried out, and a project feature vector set is defined; similar project identification is carried out by inputting a similar project identification condition; a fuzzy identification technology is used to select similar projects; before a power transmission and transformation project cost dynamic control target is calculated, similar projects are selected in historical data samples according to the attribute of a cost control object; a weighted Hamming distance proximity formula is used to calculate the proximity of a target project of cost control and historical data; according to the number of the samples and the sample proximity, a proximity threshold is determined; according to the proximity threshold, whether the number of similar projects meets a calculation requirement is determined; according to the proximity threshold and the number of similar projects, a similar project cost sequence is generated; identified power transmission and transformation similar project cost is decomposed to determine the power transmission and transformation project cost control target. According to the invention, power transmission and transformation project cost pre-intervention and in-process control are realized.

The invention discloses an ultrasonic wave airtightness detecting system based on multiple sensors and a method thereof. The system comprises a plurality of ultrasonic wave transmitters which are arranged in a container, an energy transducer set, a signal conditioning circuit, a main processor and a signal output module, wherein the energy transducer set, the signal conditioning circuit, the main processor and the signal output module are successively connected. The main processor is used for converting an amplified and filtered ultrasonic wave to a digital signal, and processes the digital signal through a fuzzy identification algorithm, a weak leakage determining algorithm and a data fusion and leakage determining algorithm, thereby obtaining a consistency interpretation to the leakage condition after fusing the signals of the sensors, converting a determining result to an analog signal, and transmitting the analog signal to an information terminal for displaying. The ultrasonic wave airtightness detecting system and the method thereof have high detecting precision and high detecting capability for weak leakage signals. Furthermore the ultrasonic wave airtightness detecting system has advantages of small size, high convenience in carrying, high sensitivity, high stability, and high benefit for dynamic online detection.

The present invention relates to a coking waste-gas desulfurization process optimized control method applied to a desulfurization and denitrification integrated process device. The method includes the following steps that: a current working condition is determined through using a fuzzy identification algorithm according to flue gas temperature, flue gas flow rate, flue gas oxygen content and sulfur dioxide concentration at the entrance of the desulfurization and denitrification integrated process device; the optimal pH value of a desulfurization absorption liquid under the current working condition is determined by using a variable step size progressive decrease method; the amount of ammonia compensation under the current working condition is determined through using a neural network model; the amount of ammonia control under the current working condition is determined through using an inner membrane control method and according to the sulfur dioxide concentration at the entrance of the desulfurization and denitrification integrated process device; and the pH value of the desulfurization absorption liquid is controlled according to the amount of ammonia compensation and the amount of ammonia control and based on the optimal pH value of the desulfurization absorption liquid. With the coking waste-gas desulfurization process optimized control method provided by the embodiments of the invention adopted, the fastness and accuracy of control are improved, and the desulfurization and denitrification integrated process device can operate under a most economical and environmentally friendly state, and the operating cost of the desulfurization and denitrification integrated process device can be reduced.

The invention discloses an improved generalized prediction control method for a work arm of an underwater robot. A T-S fuzzy identification model suitable for nonlinear system identification is established, a real-time CARIMA parameter model of the underwater arm is obtained by identification, a step factor is introduced to form a progressive relation, a progressive generalized prediction controlalgorithm is used to generate an optimal control variable via rolling prediction optimization, and a controller of a hydraulic driver is acted on, so that the underwater arm generates a correspondingmotion. According to the improved algorithm of the invention, it is not required to know the structure of a controlled object model, dynamic change of the system can be reflected timely, tedious matrix calculation processes are omitted, the computational complexity is reduced, and the algorithm is simpler and more practical.

The invention relates to personnel counting method and equipment based on an embedded system. Information collected by adopting the traditional mode for collecting human body information is messy. The method comprises the following steps of: collecting signals: placing a detector of a signal collecting device at the top of a human body passing area, only responding human body signals limited in a detection area by an infrared pyroelectricity sensor through a reformed optical system, and converting the collected irregular signals into regular signals which can be identified by a processor; processing the signals: after the identifiable regular human body infrared signals are inputted to the core processor, indentifying the human body moving directions by adopting a fuzzy identification algorithm, and then counting personnel quantity in real time and automatically storing in an external memory; and establishing a system USB transmission interface by utilizing a USB controller of an embedded microprocessor so that users can transfer the data of personnel information in the memory through the USB interface. The invention is used for counting personnel in messy streams of people.

The invention brings forward an image fuzzy identification method of a standard constant temperature bath glass thermometer. The method comprises the following main steps: acquiring a fuzzy image of the thermometer, converting the acquired fuzzy image into a gray-scale map, performing threshold processing on the gray-scale map; performing rotation correction on the fuzzy image after the threshold processing, and obtaining a liquid column position of the thermometer by use of a projection method; segmenting the fuzzy image after the rotation correction to obtain a graduation line subarea, a liquid column subarea and an indication character subarea; performing morphological processing on the subareas to obtain pixel coordinates of a graduation line and a liquid column fixed point; and performing character search on the indication character subarea to identity characters and obtain temperature information of the graduation line, and finally obtaining an indication temperature of the thermometer in the acquired fuzzy image. According to the invention, thermometer characters are identified by use of a fuzzy closeness algorithm, fuzzy closeness digital repair is performed on incomplete digits, correct identification of incomplete characters is realized, the correct rate of the identification is about 96%, and the thermometer reading accuracy can reach 95%.

The present invention discloses a method and a device for determination of rainfall features, belonging to the technical field of hydrology. The method comprises the steps of: obtaining one rainfall rain-type feature matrix of each rainfall station in a plurality of rainfall stations of an urban area to be researched and a time feature matrix of the rainfall stations, and determining one sample rainfall type of each sample rainfall station through a first preset cluster algorithm according to the sample rainfall rain-type feature matrixes of the sample rainfall stations; performing fuzzy identification of the rainfall rain-type feature matrix of each rainfall station according to the sample rainfall type of each sample rainfall station, and obtaining one rainfall type where each rainfall station belongs to; performing statistics of relative time of the maximum rainfall happening of the rainfall stations after clustering through a second preset cluster algorithm according to the time feature matrix of the rainfall stations; and determining a rainfall type of the urban area to be researched according to the relative time of the maximum rainfall happening of the rainfall stations after clustering and the rainfall types where the rainfall station belong to.

The invention discloses a color space transition method based on the fuzzy logic and the neural network, comprising steps of selecting sampling points of input color space, collecting modeling data of the sampling points, creating a fuzzy nerve color space transition model, and inputting the modeling data of the sampling points into the fuzzy nerve color space transition model to accomplish the transition of the color space. The color space transition method based on the fuzzy logic and the neural network of the invention makes full use of fuzzy identification on advantage of rapidity in WAN firstly, and the input color space is divided into a plurality of subspaces; then the invention also makes full use of neural network on advantages of strong ability and high precision on self-adaption and identification in local subspace and reasonably achieves the complementary advantages between fuzzy and neural network arithmetic, thereby greatly improving the processing speed of model conversion and effectively improving the precision of model conversion.

The invention discloses a distribution network high-fault region identification method. The method comprises the following steps: performing fuzzy identification on distribution network fault positions on the basis of multisource data; based on historical load data and meteorological monitoring data, performing distribution network fault power failure load loss evaluation; performing grid division on a geological view and realizing mapping between faults and geological grids; calculating a fault influence statistical index of each geological grid in a given time period and quantifying fault influences in each grid area; according to each fault influence statistical index, performing coloring so as to generate a fault influence color spot graph; and bringing forward corresponding auxiliary decision-making advice to a high-fault region. According to the invention, power failure loss quantification and fuzzy positioning are performed on vast distribution network faults, the mapping is performed with the geological grids, the fault influences of the geological grids are statistically analyzed, and the fault influence color spot graph is formed, such that refined and customized auxiliary decision-making advance is provided for distribution network scheduling, operation and maintenance.

An apparatus for artificially and intelligently identifying money over and short in an RFID cashbox is disclosed. The apparatus comprises certificates of deposit and withdrawal, a cabinet box, a counter group, a foot box, a camera shooting system, a damping keyboard, a character identification system and a financial server. The cabinet box is used for placing the counter group. The counter group is formed by a plurality of counters and is used for placing scattered money and bundles of money. Each counter comprises an electromagnetic force balance weighing sensor located in a lower portion anda counter body located in an upper portion. The electromagnetic force balance weighing sensor comprises a bearing bench located in an upper portion and a pedestal located in a lower portion. A pedestal bottom is provided with a circuit interface. An artificial intelligence fuzzy identification server uses a neural network image identification algorithm, acquires all or parts of images of a specific face value of money from the camera shooting system and assesses a condition of the specific face value of money. A fuzzy k-nearest neighbor algorithm is used. The face value of each piece of moneyin the same counter is assumed to be the same. Because of the different conditions of the money, weights are different. A fuzzy rule base is set for each counter. According to the weights and added weights, the number of the money is determined.

The invention provides a method of detecting users in a channel. The method comprises steps: multiple attributes reported by access under user triggering in an application distributed by the channel are acquired, wherein the users are newly-added users for any application distributed by the channel; hierarchical clustering is carried out among the users according to the multiple attributes to obtain a preset number of user categories, wherein the users belong to different user categories respectively; according to behavior attributes of users in each user category, a user category to which absolute real users belong is removed; and fuzzy identification is carried out on users in the user category to judge and obtain suspicious false users. Besides, the invention also provides a device for detecting users in a channel. Due to the above method and the device for detecting the users in the channel, use of an amount brushing tool in the channel can be recognized accurately, and partial false users mixed in the channel can be recognized accurately.

The invention relates to a method for identifying various concealed information implanted in a goods by using a portable equipment, in particular to the portable equipment capable of identifying the concealed information in entertainment goods such as mahjong, playing cards, Paigow poke and the like and the identification method for the concealed information. In the portable equipment, various concealed information acquisition devices are integrated; concealed image information is acquired by a special camera, an infrared/ultraviolet supplementing light source and a special optical filter; magnetic field information is detected by a magnetic field; and the acquired concealed image information is directly provided to an analysis identification module in the portable equipment for being screened and an identification result is displayed on the portable equipment. The invention is characterized in that when word characters are analyzed, a special fuzzy identification method is used. The portable equipment is preferably a mobile phone. The portable equipment and the identification method for the concealed information can be used in various application fields such as counterfeiting prevention of the goods, cheating prevention and the like.

The invention discloses a method for evaluating water quality in a water functional area based on a fuzzy identification index. The method comprises the following steps of: counting and screening out water quality evaluation factors by use of a box plot; establishing an improved fuzzy synthetic evaluation model; determining an improved six-order membership function on the basis of a trapezoid function, and calculating the membership degree of the water-quality evaluation factors for each evaluation order to obtain a fuzzy relation matrix and a fuzzy synthetic evaluation result, and determining a water quality classification; and displaying a water quality evaluation result by use of the fuzzy identification index. The method can not only improves the precision of water quality evaluation but also makes the evaluation result simple and intuitive and makes the conveyed information rich and can provide technological and theoretical supports for further promotion of water environment pollution improvement work.

The invention discloses a BIM project material and project cost statistical method. The method comprises the following steps: adding corresponding material attributes to each component of a three-dimensional model; uploading a historical engineering cost list to a material center; collecting engineering cost information; giving a weight value to each construction cost index in the construction cost information, and storing the weight values into a database; processing each engineering component in the database and then constructing a cost model; inputting each component attribute into a cost model to obtain a cost prediction value; and superposing the construction cost prediction values of the components to obtain the final project construction cost. According to the method, the cost modelis constructed in the historical engineering cost list of the material center, the similar cost model is identified by using the fuzzy identification technology and the three-dimensional model is input to obtain the specific cost of the three-dimensional model, the building scheme is modified at any time, the engineering quantity and the cost are output, the advantages and disadvantages of the schemes are compared, and the investment is saved; and the most beneficial and most economical scheme is selected.

The invention discloses a method for fuzzy identification of a water supply network model based on waterpower adjustment. According to the invention, the EPANETH software is adopted to establish a waterpower adjustment model of the water supply network, the operating simulation to the water supply network is realized, and the simulated experimental data is obtained. The system input and output time history obtained through simulating the waterpower adjustment model is utilized to replace the observation data, and the fuzzy identification method of the T-S model is adopted to deal with the input and output time history, so that a system parameter model is obtained. According to the invention, the advantages of the EPANETH software are utilized, stationing and data collection of onsite sensors are simplified, and the high-precision fuzzy identification of the T-S model is utilized for predictive control of the water supply network, so that the reliability of optimized dispatching of the water supply network is ensured.

The invention discloses a traffic participant behavior safety assessment method, which can determine the safety level of behaviors according to the basic information of traffic participants and traffic behavior data. The method comprises the following steps of: firstly, establishing a traffic behavior safety assessment index system according to the behavior process of 'pre-event, amid-event and post-event' of the traffic behaviors and according to the principle of two-layer index systems; then determining each safety level of the traffic participants and a standard value of each level assessment factor by comprehensive assessment; designing an assessment index corresponding scale, and acquiring sample data; and finally, based on the research of 'traffic participants, traffic safety assessment indexes and traffic behavior requirements', determining a fuzzy measure model and a fuzzy integral assessment model by using the fuzzy measure theory aiming at an assessment sample structure assessment function, establishing a traffic behavior safety assessment method, and finally obtaining the safety level of the assessed sample by fuzzy identification.

The invention realizes a weather image acquisition and identification method and constructs an intelligent weather image acquisition and identification system. An automatic weather image acquisition method is realized in a device of an automatic meteorological observing station, corresponding weather image sample data is automatically acquired according to various weather phenomena, and a weather phenomenon image sample library is automatically established; and an intelligent weather image identification method is realized, a weather image fuzzy identification method is realized based on the weather phenomenon image sample library, and the weather phenomena corresponding to weather images can be quickly identified. The defect of incapability of acquiring weather images in conventional meteorological observation is overcome, so that the visualized weather images can be automatically acquired according to the weather phenomena during weather observation, a visualized weather image sample library can be established, and the weather observation is more visual. Meanwhile, based on the intelligent weather image acquisition and identification system, the weather phenomena corresponding to the weather images can be quickly identified, more weather information can be obtained, and the intelligent method for identifying the weather by the images is innovatively realized.