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190 results about "Fuzzy inference system" patented technology
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What is Fuzzy Inference Systems. 1. Fuzzy inference is the process of mapping from a given input to an output using fuzzy logic. The mapping then provides a basis from which decisions can be made, or patterns discerned. Fuzzy inference systems have been successfully applied in fields such as automatic control, data classification, decision analysis.
System and method for image segmentation
A method of segmenting images receives an image (such as a medical image) and a segment in relation to the image, displays them to an observer, receives a modification to the segment from the observer, and generates a second segment in relation to a second image, responsive to the modification. An image segmentation system includes a learning scheme or model to take input from an observer feedback interface and to communicate with a means for drawing an image segment to permit adjustment of at least one image segmentation parameter (such as a threshold value). The learning scheme is provided with a knowledge base which may initially be created by processing offline images. The learning scheme may use any scheme such as a reinforcement learning agent, a fuzzy inference system or a neural network.
Owner:UNIVERSITY OF WATERLOO
Intelligent robust control system for motorcycle using soft computing optimizer
A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a motorcycle is described. In one embodiment, a simulation model of the motorcycle and rider control is used. In one embodiment, the simulation model includes a feedforward rider model. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and / or output variables; the type of fuzzy inference; and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual plant model of the controlled plant. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.
Owner:YAMAHA MOTOR CO LTD
Audio communication device, method for outputting an audio signal, and communication system
An audio communication device comprises an input connectable to a narrowband audio signal source. The input can receive a narrowband audio signal having a first bandwidth. An extraction unit is connected to the input and arranged to extract a plurality of narrowband parameters from the narrowband audio signal. An extrapolation unit is connected to receive the plurality of narrowband parameters and arranged to generate a plurality of wideband parameters from the plurality of narrowband parameters. The extrapolation unit comprises one or more adaptive neuro-fuzzy inference system modules. The device further comprises a synthesis unit connected to receive the plurality of wideband parameters and arranged to generate, using the wideband parameters, a synthesized wideband audio signal having a second bandwidth wider than the first bandwidth. And the device comprises an output connectable to an acoustic transducer arranged to output for humans perceptible acoustic signals, for providing said synthesized wideband audio signal to the acoustic transducer.
Owner:NXP USA INC
Self-adaptive tracking loop and implementation method
InactiveCN102540216AAccurate trackingSolve the noiseSatellite radio beaconingNumerical controlDiscriminator
The invention discloses a self-adaptive tracking loop, which comprises an unscented Kalman filter (UKF), an observation noise variance matrix detection module, a fuzzy inference system, an unscented transformation (UT) scale factor regulation module, a state compensator, a carrier wave numerical controlled oscillator (NCO), scale factors, a code NCO, an integration and zero-clearing module, a code loop phase discriminator and a second order code loop filter, and additionally discloses an implementation method for the self-adaptive tracking loop. The implementation method comprises a step 1 ofsignal correlation, integration and zero clearing; a step 2 of code phase tracking; a step 3 of UKF modeling; a step 4 of observation noise variance matrix estimation; a step 5 of process noise variance matrix estimation; a step 6 of UT scale factor regulation; a step 7 of state estimation deviation compensation; and a step 8 of assistance of the carrier wave NCO in the code NCO. According to theself-adaptive tracking loop, the UKF, the observation noise variance matrix detection module and the fuzzy inference system are designed in the carrier tracking loop, so not only can a contradiction between thermal noise vibration in the tracking loop and a dynamic stress error be solved, but a process noise variance matrix and an observation noise variance matrix can be regulated in a self-adaptive manner according to changes of the external environment, and thereby the self-adaptive ability of the tracking loop under complex changeable environments of high dynamic, strong interference, and the like is effectively improved.
Owner:BEIHANG UNIV
System and method for software estimation
ActiveUS20060041857A1The result is accurateEasy to useError detection/correctionDigital computer detailsInference systemNeuro-fuzzy
A system and method for software estimation. In one embodiment, the software estimation system comprises a pre-processing neuro-fuzzy inference system used to resolve the effect of dependencies among contributing factors to produce adjusted rating values for the contributing factors, a neuro-fuzzy bank used to calibrate the contributing factors by mapping the adjusted rating values for the contributing factors to generate corresponding numerical parameter values, and a module that applies an algorithmic model (e.g. COCOMO) to produce one or more software output metrics.
Owner:HUANG XISHI +3
Power distribution network fault classification method based on adaptive neuro-fuzzy inference system
InactiveCN104155574ASolve the problem of "rule explosion"Reduce unnecessary errorsFault locationSpecial data processing applicationsData validationPhase currents
The invention relates to a power distribution network fault classification method based on the adaptive neuro-fuzzy inference system. The method is an improved method based on the adaptive neuro-fuzzy inference system. According to several frequently-occurring short circuit fault types of the power distribution network, a hierarchical based adaptive neuro-fuzzy inference system is constructed in the method, various short circuit faults are simulated based on a simulation software and the fault phase current is collected as the training sample data, and the blended learning algorithm is used for training the constructed hierarchical adaptive neuro-fuzzy inference system to determine the parameter in the system; the hierarchical adaptive neuro-fuzzy inference system with the determined parameter can be used for discriminating the fault types of the power distribution network. A lot of simulation data validations indicate that the classification method provided by the invention has a higher classification and identification accuracy, and has a better robustness on the variation of the fault points and a strong adaptability on the variation of the network topology.
Owner:WUHAN POWER SUPPLY COMPANY OF STATE GRID HUBEI ELECTRIC POWER +1
Fuzzy logic guided inverse treatment planning
InactiveUS20070081629A1X-ray/gamma-ray/particle-irradiation therapyTreatment targetsReasoning system
A fuzzy inference system for use in modulating radiation treatment includes a fuzzifer for inputting imaging data, and inference device operatively to the fuzzifer for analyzing the imaging data and determining radiation treatment target from non-treatment target, and a defuzzifier for modulating radiation treatment pursuant to the analysis from the inference device.
Owner:HENRY FORD HEALTH SYST
Intelligent electronically-controlled suspension system based on soft computing optimizer
InactiveUS20060293817A1Near-optimal FNNMaximises informationDigital data processing detailsAnimal undercarriagesInput/outputSoft computing
A Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a suspension system is described. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and / or output variables; the type of fuzzy inference model (e.g., Mamdani, Sugeno, Tsukamoto, etc.); and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual suspension system model of the controlled suspension system. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.
Owner:YAMAHA MOTOR CO LTD
Parking lot reverse car seeking management system based on fuzzy positioning and implementation method of parking lot reverse car seeking management system
InactiveCN103440781AFind quicklyAvoid walking detoursRoad vehicles traffic controlFuzzy queryDatabase server
The invention relates to a parking lot reverse car seeking management system based on fuzzy positioning and an implementation method thereof. The parking lot reverse car seeking management system comprises an image capture device arranged on a traffic lane of a parking lot, a parking lot central database server connected with the image capture device, and intelligent car seeking query system terminals arranged at pedestrian exits / entrances of the parking lot. The intelligent car seeking query system terminals are all in communication connection with the parking lot central database server. The image capture device comprises a camera and an image recognition module, wherein the camera is arranged above the traffic lane and connected with the image recognition module, and the image recognition module is connected with the parking lot central database server. The parking lot central database server comprises a fuzzy inference system used for storing parking information and conducting search for parking spaces. Each intelligent car seeking query system terminal comprises a fuzzy query module, a printing module and a touch display unit, wherein the fuzzy query module, the printing module and the touch display unit are all in communication with the parking lot central database server. The parking lot reverse car seeking management system based on fuzzy positioning and the implementation method reduce the number of image capture devices and lower operation and maintenance cost.
Owner:SUZHOU ZHIDIE TECH
Battery SOC estimation method applying multiple models parallelly
Te invention discloses a battery SOC estimation method applying multiple models parallelly. The method includes following steps: 1), acquiring battery state parameters; 2), normalizing the battery state parameters; 3), respectively substituting the battery state parameters after being normalized into a genetic algorithm optimized BP neural network estimation model, a self-adaptive neural-fuzzy reasoning system model and an OS-ELM neural network model to acquire three SOC estimation results; 4), according to a SOC-OCV relation, acquiring initial estimation voltage values respectively corresponding to the three SOC estimation results acquired in the step 3); 5), respectively calculating difference values between the initial estimation voltage values and voltage, and normalizing the difference values to acquire weighting coefficient of the initial estimation voltage values; 6), calculating a final estimated value of SOC according to the weighting coefficient. By utilizing three importantparameters of a battery, using the three models parallelly, using multiple linear system estimation results to describe a nonlinear system and then weighting, summing and estimating the battery SOC value, estimation accuracy is improved effectively.
Owner:HUAIYIN INSTITUTE OF TECHNOLOGY
Device and method for suppressing subsynchronous oscillation of power system
InactiveCN102340146AReduce dependenceSuppression of subsynchronous oscillationsPower oscillations reduction/preventionDamping torqueElectric power system
The invention discloses a device and method for suppressing subsynchronous oscillation of a power system. The method comprises the following steps of: firstly, filtering the rotation speed signal of a generator to obtain the subsynchronous rotation speed signal of each mode; processing the subsynchronous rotation speed signal of each mode respectively to obtain a change rate; then, generating an additional control signal through a Sugeno type fuzzy reasoning system; and finally, performing amplification, overlapping and amplitude limiting on the obtained additional control signal, and generating an exciting voltage additional control signal so as to change the exciting current, generate a subsynchronous frequency damping torque and suppress the subsynchronous oscillation. In the method provided by the invention, a training sample of a fuzzy controller is established according to the phase compensation principle, and the parameters of the fuzzy system are optimized and trained by use of a learning algorithm of an error backpropagation neural network. The method solves the problem that the expert experience is difficult to obtain by the fuzzy controller, and the additional exciting damping controller can effectively suppress the subsynchronous oscillation of the power system.
Owner:SOUTHEAST UNIV
Intelligent real-time 360° enterprise performance management method and system
An intelligent real-time 360° enterprise performance management system and 6-step methodology, which provides an integrated way to evaluate the performance and effectiveness of specific ‘business components’ within organizations (e.g., internal functions, internal processes, and stakeholder relationships). The system serves as a highly scalable, customizable, and context-aware Unified Enterprise Performance Management Application Platform (UEPMAP) that automates static and dynamic real-time and asynchronous business intelligence gathering from employees, customers, suppliers, business partners and other key stakeholders; analyses structured and unstructured feedback data; identifies strengths and weaknesses for each business component by way of SWOT analysis; develops prioritized action plans, supported by an adaptive neuro-fuzzy inference system (ANFIS) in order to address weaknesses identified within business components.
Owner:ASAF SAMIR
Predicative control method for modeling and running speed of adaptive network-based fuzzy inference system (ANFIS) of high-speed train
ActiveCN103019267ARun on timeGuaranteed uptimeSpeed/accelaration controlAdaptive controlAutomatic controlSimulation
The invention provides a generalized predicative control method of a high-speed train based on an adaptive network-based fuzzy inference system (ANFIS) model. The method utilizes a data-driven modeling method to build the ANFIS model in a running process of the high-speed train according to acquired high-speed train running data; adopts subtractive clustering to determine rule number and initial parameters of a fuzzy model, and adopts a back-propagation algorithm and a least square method to optimize parameters of the fuzzy model. The predictive tracking control method of electric multiple unit running speed on the basis of the ANFIS model obtains accurate controlled quantity through multistep predication and circular rolling so as to change blindness of adjustment by experience, enables the high-speed train running speed to track a target curve accurately, solves the problem of large lag, achieves on-schedule, safe and effective running of the train, and guarantees safety of passengers. The method is simple, practical, capable of achieving automatic drive control of the high-speed train and suitable for on-line monitoring and automatic control of a running process of the high-speed train.
Owner:EAST CHINA JIAOTONG UNIVERSITY
Multi-robot angle control surround method based on fuzzy inference system
InactiveCN105487544AAvoid swingingRound up realizationPosition/course control in two dimensionsVehiclesAlgorithmFuzzy inference system
The invention provides a multi-robot angle control surround method based on a fuzzy inference system. According to the method, a multi-robot surround strategy is realized by adopting two layers of fuzzy inference; the first layer of fuzzy inference system is a decision layer which is used for identifying the state of a surround task and selecting a corresponding multi-robot strategy; when surround persons are in the search state, the decision layer outputs Search through fuzzy inference, and the surround persons perform the search strategy; when the surround persons are in the approach state, the decision layer outputs Approach, i.e. the surround persons perform the approach strategy; and when the surround persons are in the surround state, the decision layer outputs Surround, and the surround persons perform the surround strategy. The experiment is performed by using the simulation programs, the environment of the simulation programs is proportionally reduced according to the parameters in the actual environment, and movement of robots meets the kinematic model constraint. Multiple times of the simulation experiment is performed under different initial conditions so that feasibility of the algorithm is verified and great effect is achieved.
Owner:SHENYANG POLYTECHNIC UNIV
Car-following simulation method based on fuzzy mathematics
InactiveCN102662320AReflect the decision-making processEfficient reproductionAdaptive controlDriver/operatorState parameter
The invention discloses a car-following simulation method based on fuzzy mathematics in the technical filed of motor vehicle driving behavior simulation. The method comprises the steps of: firstly, drawing a speed-time curve and a speed-displacement curve of a leading car and a following car respectively; acquiring driving character parameters of the following car and moving state parameters of the two cars one after the other; and then, substituting the character parameters and the moving state parameters of the following car into a fuzzy inference system, deriving a vehicle motion control rule and simulating car driving. By taking into consideration feature differences of drivers and different characteristics of vehicles, the method can better reflect drivers' decision making process, better simulate drivers' driving behavior, and reproduce real traffic scenes more effectively.
Owner:吴建平
Soft computing optimizer of intelligent control system structures
InactiveUS7219087B2Near-optimal FNNTelevision system detailsChaos modelsEngineeringInternal combustion engine
The present invention involves a Soft Computing (SC) optimizer for designing a Knowledge Base (KB) to be used in a control system for controlling a plant such as, for example, an internal combustion engine or an automobile suspension system. The SC optimizer includes a fuzzy inference engine based on a Fuzzy Neural Network (FNN). The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and teaching signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and / or output variables; the type of fuzzy inference model (e.g., Mamdani, Sugeno, Tsukamoto, etc.); and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal. The GA produces a near-optimal FNN. The near-optimal FNN can be improved using classical derivative-based optimization procedures. The FIS structure found by the GA is optimized with a fitness function based on a response of the actual plant model of the controlled plant. The SC optimizer produces a robust KB that is typically smaller that the KB produced by prior art methods.
Owner:YAMAHA MOTOR CO LTD
Cloud configuration safety assessment method
InactiveCN104883369AImprove reliabilitySimple calculationTransmissionReasoning systemSecurity question
The invention discloses a cloud configuration safety assessment method. The cloud configuration safety assessment method comprises the following steps: (1), performing qualitative and quantitative analyzing on security problems and security evidences in the hierarchical structure of each service configuration including an IaaS layer, a Paas layer and an Saas layer; (2), assessing the security of each service configuration of a cloud platform; and (3), assessing the overall security of the cloud platform, establishing a first-level cloud security assessment model by use of a Sugeno fuzzy inference system based on an adaptive neural network, and analyzing the overall security of the cloud platform. Compared to the prior art, the number of users accessed to a network end is dynamically and reasonably controlled, loads accessed to the network end are always maintained within a certain acceptable scope, the users can be dispersed when a large number of users are simultaneously accessed to a network at the same frequency, the users can be accessed to the network as soon as possible, and the system random access performance in case of network congestion is greatly improved.
Owner:TIANJIN UNIV
Real-time prediction system and method for boiler entering heat value of circulating fluidized bed household garbage incineration boiler
ActiveCN105864797AAvoid the tedious work of offline measurementsIncinerator apparatusCluster algorithmAutomatic control
The invention discloses a real-time prediction system and method for a boiler entering heat value of a circulating fluidized bed household garbage incineration boiler. By means of hidden knowledge in operation historical data and an operational mechanism of the circulating fluidized bed household garbage incineration boiler and through an integrated modeling method of a particle swarm optimization (PSO) algorithm, a subtractive clustering algorithm and an adaptive neuro-fuzzy inference system (ANFIS) algorithm, the system and the method which are fast and economical are established for real-time prediction of the heat value of boiler entering garbage, the complicated work of off-line measurement for garbage components is avoided, a new path is provided for boiler operation operators and relevant management staff of a power plant to judge the heat value of the boiler, and meanwhile, a heat value judgment signal can be provided for an automatic control system of the power plant.
Owner:ZHEJIANG UNIV
Smart agent for examination of an application
InactiveUS20090150326A1Reduce riskIncrease probabilityOffice automationFuzzy logic based systemsAnalysis dataIntellectual property
A system, method, and article for profiling an applicant, an examiner, and agency or examination group for the purposes of examination of an application that undergoes a regulated or structured examination. One aspect of the invention can provide a greater degree of predicting success or potential success based on identifying a data factor that has a potential influence upon success of the application. Another aspect uses statistical methods or logic from a fuzzy inference system to analyze data factors. One example is directed towards the filing and prosecution of intellectual property documents such as patent and trademark applications.
Owner:FOUNDIP
Voltage sag source identification method based on Mamdani fuzzy reasoning
InactiveCN101572411AImprove accuracyReduce recognition errorsInference methodsInformation technology support systemFuzzy ruleElectric power system
The invention discloses a voltage sag source identification method based on Mamdani fuzzy reasoning, belonging to technical field of voltage quality monitoring of a power system. The method comprises the steps of calculating the membership degree of three-phase voltage to balance, the membership degree of the voltage at the end of voltage sag to mutation degree and the membership degree to harmonic content; inputting the membership degrees to an Mamdani fuzzy reasoning system and substituting into fuzzy rules to calculate a corresponding fuzzy result; and using the center of gravity defuzzification for defuzzifying the fuzzy result to obtain the type of a sag source. The method takes into account of inherent differences of four different sag causes and is started from amplitude, mutation and harmonic, thereby avoiding the impacts of a plurality of uncertain features on the analysis accuracy of different sag sources; in addition, the method fuzzifies the input and the output quantities of the reasoning system, thereby avoiding the practice that the prior art needs to determine thresholds of all the feature values and further reducing the identification errors caused by the fixation of the thresholds.
Owner:STATE GRID TIANJIN ELECTRIC POWER +1
Robot path planning method based on ANFIS fuzzy neural network
InactiveCN107168324AReduce logical reasoning workloadGet out of the trap statePosition/course control in two dimensionsVehiclesTakagi sugenoSimulation
The invention discloses a robot path planning method based on an ANFIS fuzzy neural network, and mainly solves the problems of complex trap path reciprocating and path redundancy in conventional reactive navigation. The method comprises the following steps: to begin with, establishing a kinematic model for a mobile robot; providing a mobile robot navigation controller based on the fuzzy neural network by means of autonomous learning function of the neural network and fuzzy reasoning ability of the fuzzy theory; constructing a Takagi-Sugeno fuzzy inference system based on an adaptive fuzzy neural network structure and serving the Takagi-Sugeno fuzzy inference system as a reference model for local reaction control of the robot; the fuzzy neural network controller outputting offset angle and operation speed in real time, and adjusting the migration direction of the mobile robot online to enable the mobile robot to be able to adjust speed automatically and approach the goal collisionless; and through an improved virtual target method, selecting an optimal path capable of allowing the robot to escape a trapping state.
Owner:CHINA UNIV OF MINING & TECH
Method and device for assessing level of fire interlock alarming in ship cabin
InactiveCN102682560AReduce major lossesExpand the range of associated alarmsFire alarmsMarine engineeringComputer module
The invention provides a method and a device for assessing levels of fire interlock alarming in a ship cabin. The method comprises the following steps that: 1) a central fire alarm control unit acquires fire situation information obtained by temperature sensing detectors and smoke sensing detectors which are in all ship cabins and adjacent to the ship cabin in which fire breaks out; 2) the central fire alarm control unit reads danger level information of the fire in the ship cabin; 3) the fire situation information obtained by the temperature sensing detectors and the smoke sensing detectors and the danger level information of the fire in the ship cabin are subjected to normalized pre-processing; and 4) processed data are sent to a fuzzy reasoning module to be subjected to fuzzy reasoning, so that a level assessment result of the fire interlock alarming in the ship cabin is obtained. On the basis of no increase of additional detection equipment and no addition of cost, information data from different types of detectors in all the ship cabins and danger level information data of the fire are analyzed and processed by using a fuzzy reasoning system; the alarming level information in each ship cabin is rapidly and correctly given, the correctness, the leading and the comprehensiveness of the interlock alarming of the ship cabin can be realized as far as possible, and serious fire accidents caused by omission of the fire situation information of the ship cabin are reduced.
Owner:HARBIN ENG UNIV
System for soft computing simulation
InactiveUS20060218108A1Near-optimal FNNGenetic modelsDigital computer detailsFuzzy inferenceAlgorithm
The present invention involves a Soft Computing Optimizer (SCOptimizer) for designing a Knowledge Base (KB) to be used in a control system for controlling a plant. The SC Optimizer provides Fuzzy Inference System (FIS) structure selection, FIS structure optimization method selection, and training signal selection and generation. The user selects a fuzzy model, including one or more of: the number of input and / or output variables; the type of fuzzy inference model (e.g., Mamdani, Sugeno, etc.); and the preliminary type of membership functions. A Genetic Algorithm (GA) is used to optimize linguistic variable parameters and the input-output training patterns. A GA is also used to optimize the rule base, using the fuzzy model, optimal linguistic variable parameters, and a teaching signal.
Owner:YAMAHA MOTOR CO LTD
System and method for software estimation
ActiveUS7328202B2The result is accurateEasy to useError detection/correctionDigital computer detailsInference systemNeuro-fuzzy
Owner:HUANG XISHI +3
Method and system for predicting bed temperature of circulating fluidized bed municipal solid waste incineration boiler
ActiveCN106224939AHigh degree of automationPrevent overfittingFluidized bed combustionIncinerator apparatusCluster algorithmTacit knowledge
The invention discloses a method and system for predicting the bed temperature of a circulating fluidized bed municipal solid waste incineration boiler. Based on tacit knowledge in operation mechanisms and operation history data of the circulating fluidized bed municipal solid waste incineration boiler, a modeling method is integrated by a Gamma Test algorithm, a PSO (particle swarm optimization) algorithm, a subtractive clustering algorithm and an ANFIS (adaptive neuro-fuzzy inference system) algorithm for predicting a bed temperature of the boiler in real time to avoid from complex mechanism modeling work. The whole modeling process is clear in logic, few in set parameters, high in modeling automation degree and easy to master and popularize. Meanwhile, an excellently trained ANFIS bed temperature diction model can serve control algorithms based on the model to provide help for ACC (automatic combustion control) system actuation of the circulating fluidized bed municipal solid waste incineration boiler.
Owner:ZHEJIANG UNIV
Intelligent robust control system for motorcycle using soft computing optimizer
The invention describes a vehicular intelligent touch control system using a soft computing (SC) optimizer, and the SC is used to design a knowledge base (KB) used in the vehicular control system. A user selection fuzzy model comprises one or a plurality of input and / or output variable numbers, fuzzy inference models, and the primary models of membership functions. A genetic algorithm (GA) is used to optimize language variable parameters and an input-output training mode. The GA is used to optimize a rule base through the fuzzy model, the optimized language variable parameters and teaching signals. The GA produces an approximately optimal fuzzy nerve network (FNN). The approximately optimal FNN can be improved through examples based on a derivative optimization procedure. The fuzzy inference systems (FIS) constructed by the GA can be optimized through the adaptation function of a controlled-shop-based real shop model response. The touch KB produced by the SC optimizer is usually smaller than the KB produced by the prior art.
Owner:YAMAHA MOTOR CO LTD
Mixing scheduling method suitable for real-time system periodic tasks
InactiveCN103810026AReduce loss rateDeadline Lost Rate ReductionMultiprogramming arrangementsHybrid SchedulingFuzzy reasoning
The invention discloses a mixing scheduling method suitable for real-time system periodic tasks. The method comprises the following steps: searching a ready real-time system task set T and sorting the tasks in an ascending order according to deadlines; finding the task with the shortest deadline, wherein the execution time C and the deadline D of the task with the shortest deadline are taken as input data of a fuzzy reasoning system; processing the input data by a CPU (central processing unit), i.e. mapping a threshold value delta output by the fuzzy reasoning system onto a membership function of the threshold value, and determining the property of the threshold value delta according to the membership function. The mixing scheduling method uses a fuzzy system theory to organically combine an RM (rate monotonic) algorithm and an EDF (earliest deadline first) algorithm for scheduling the execution tasks, so the deadlines of the tasks cannot be missed, and system resources are fully utilized.
Owner:中国科学院沈阳计算技术研究所有限公司
Early warning method for bridge structure strain response exception
ActiveCN108763763ASmall amount of calculationImprove forecasting efficiencyGeometric CADDesign optimisation/simulationKernel principal component analysisAlgorithm
The invention discloses an early warning method for a bridge structure strain response exception. The method comprises the following steps that: utilizing a wavelet packet decomposition method to separate a bridge structure strain response; (2) utilizing a principal component analysis method to extract the principal component of a bridge ambient temperature field; (3) on the basis of an adaptive neural network fuzzy inference system, establishing a complex nonlinear relationship between an actual measurement load factor and corresponding strain data; (4) identifying the position information ofa vehicle on a bridge; (5) identifying the geometric parameter and the axle load of the vehicle; (6) on the basis of the adaptive neural network fuzzy inference system, establishing a complex nonlinear relationship between an actual measurement vehicle load parameter and corresponding strain data; (7) solving a bridge structure strain response theoretical value; and (8) comparing a theoretical solving result of the bridge structure strain response and the actual measurement result of the theoretical solving result, and updating the adaptive neural network fuzzy inference system. By use of themethod, effectively according to the actual measurement load parameter, the bridge structure strain response can be accurately predicted.
Owner:SOUTHEAST UNIV
Intelligent robust control system for motorcycle using soft computing optimizer
Owner:YAMAHA MOTOR CO LTD
Environment parameter perceiving fire hazard judgment method
The invention relates to an environment parameter perceiving fire hazard judgment method which includes the steps of (1) building three layers of feedforward BP neural networks and invariable T-S-type fuzzy inference systems, (2) collecting infrared rays, smoke, temperature, humidity and light intensity data in a monitored site through a sensor, (3) calculating infrared values in natural light through a light intensity sensor, conducting background infrared removal processing, caused by the natural light, on the infrared values, obtaining the processed infrared values, (4) inputting smoke read values and the infrared values processed by the step (3) into the three layers of trained feedforward BP neural networks, outputting the fire hazard occurrence degree, (5) inputting temperature and humidity read values into the invariable T-S-type fuzzy inference systems, outputting a fire hazard judgment threshold value, (6) comparing the fire hazard occurrence degree with the fire hazard judgment threshold value, and determining that a fire hazard occurs when the fire hazard occurrence degree is larger than the fire hazard judgment threshold value. The environment parameter perceiving fire hazard judgment method has the environment parameter perceiving function and is good in adaptability.
Owner:菏泽建数智能科技有限公司
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