205 results about "Fuzzy decision" patented technology

The invention discloses an intelligent coordination control method for traffic flow of an urban road network with public traffic priority. Each intersection is provided with a network type multi-phase intelligent signal controller, and the intelligent signal controller consists of six main parts, namely a local intersection signal control module, an adjacent intersection information processing module, a communication module, a local vehicle information processing module, a social vehicle detection module, and a public traffic vehicle detection and positioning module. A core part of the intelligent signal controller is the local intersection signal control module which consists of three submodules, namely a public traffic priority module, a green light observation module and a phase switching module, and each module adopts a fuzzy decision method. The method realizes the coordination of the traffic flow of the whole urban road network and the prior pass of public traffic through the information exchange and coordination between intelligent signal controllers of adjacent intersections; and in time-varying and large-flow traffic environment, the control effect of the method is obviously superior to that of the conventional single intersection vehicle induction control method.

The invention discloses a wind, light and water-containing multi-source complementary micro-grid hybrid energy storage capacity optimal proportion method. According to the method, an annual output power curve of wind power generation, photovoltaic power generation and hydroelectric generation is simulated according to the distribution condition of natural resources such as wind, light and water, an annual load curve of a micro-grid is combined, system cost and power fluctuation are used as target functions, accumulator capacity and super-capacitor capacity are used as optimization variables, and meanwhile constraint conditions such as power balance constraint, maximum instantaneous power constraint, power supply reliability constraint, super-capacitor charge and discharge current and voltage constraint and accumulator SOC (System On Chip) constraint are determined to establish a wind, light and water-containing micro-grid hybrid energy storage optimization configuration model; optimized solution of the target functions is performed by using a fuzzy decision-containing multi-target planning GA-PSO (Genetic Algorithm-Particle Swarm Optimization) algorithm to obtain the optimal proportion of the hybrid energy storage capacity. Compared with the conventional GA algorithm and PSO algorithm, the method has the advantages that the convergence rate is higher and the problem of mutual conflict of the target functions in the multi-target optimization algorithm is avoided better.

The invention discloses a double-shaft photoelectric rotary table compound control system and a control method based on fuzzy decision. The control system comprises an integrated digital filtering, an estimation unit, a feed-forward control unit, a measuring unit, a change-over switch, a fuzzy-decision unit, a piping and instrument diagram (PID) controller, and a signal superposition unit. The double-shaft photoelectric rotary table position error e is compared with an error threshold K c set in advance, when e is less than K c, the fussy regulation is entered and regulation output controlled quantities delta kp, delta k and delta kd are obtained. PID control and regulation parameters kp, ki and kd are further obtained, and PID calculation is conducted. Otherwise, PID calculation is conducted by the utilization of the fixed regulation parameter set in advance and control signals outputted by PID are obtained. The effects of nonlinearity, time-varying characteristics, and model uncertainty on accuracy of the double-shaft photoelectric rotary table are effectively reduced. The problems of integral saturation and high frequency disturbance in the PID controller are solved, stochastic noise in the given stochastic signals is overcome, and long-term continuous stable work of the double-shaft photoelectric rotary table compound control system is ensured.

The invention discloses a fuzzy control method and a fuzzy controller, wherein the fuzzy control method comprises the following steps: receiving detection input quantity input by a detection device, and mapping a deviation value of the detection input quantity and a set value to an input discourse domain to obtain fuzzy input quantity; performing fuzzy reasoning and fuzzy decision according to the fuzzy input quantity to obtain fuzzy control output quantity of a corresponding output discourse domain; and converting the fuzzy control output quantity into control output quantity, outputting the control output quantity to an actuating mechanism, and controlling the controlled object by the actuating mechanism according to the control output quantity. Through fuzzy control method and the fuzzy controller, the chlorination in a water plant can reach optimal control effect.

The invention discloses a high-resolution remote sensing image classifying method based on fusion of multiple classifiers. The high-resolution remote sensing image classifying method comprises the following steps that first, a training sample set is selected in an area of interest; second, the multiple classifiers are used for classifying remote sensing images; then, areas with the ground feature category classifying precision being lower than a threshold value a are classified again by using a voting method based on priori knowledge; at last, areas with the ground feature category classifying precision being lower than a threshold value b are classified by using a fuzzy decision template method, and finally the classified result of the target images is obtained. According to the high-resolution remote sensing image classifying method based on fusion of the multiple classifiers, the advantages of a single classifier are concentrated furthest, the disadvantages of the single classifier are restrained, the influences of 'same object with different spectrums ' and 'different objects with the same spectrum' on the classifying precision are lowered, and the precision of high-resolution remote sensing image classifying is improved.

The invention discloses a vehicle scheduling method based on a fuzzy decision. The method comprises the following steps of: S1, performing schedule filtering on candidate vehicles; S2, performing effective distance filtering on the filtered candidate vehicles; and S3, screening the vehicles which most possibly receive orders by making use of a Bayesian Belief Network. According to the method, the candidate vehicles are excluded according to objective conditions, namely, after the candidate vehicles are excluded according to the schedules of the vehicles and after the distances between the vehicles and the pick up locations are excluded, the order receiving intentions of the drivers of the rest of candidate vehicles are calculated by the Bayesian Belief Network, so that the vehicles which most possibly receive orders are filtered, and then the filtered vehicles which most possibly receive orders are polled, thus, the polling is more targeted, the probability for receiving orders is greatly improved, and the time for polling the candidate vehicles which are less likely to receive orders is saved. Large amounts of data statistics shows that after the adoption of the method provided by the invention, the candidate vehicles are polled, and the probability for receiving orders is improved by 10-15%.

The invention discloses a method for selecting a cell by a multi-mode wireless terminal. In a cell reselection process, the multi-mode wireless terminal firstly divides a cell which is in accordance with a cell selection standard S into a preferential network mode cell and a suboptimum network mode cell, and then a finally reselected target cell is determined by using fuzzy reasoning and fuzzy decision methods, wherein in a plurality of pilot frequency cells, participating reselection, with same frequency and same priority, fuzzy reasoning is utilized to evaluate five measurement parameters, namely, a receiving level value of each cell, a minimum required receiving level value in the cells, relative frequency shift, available uplink maximum transmitting power of a terminal and maximum radio frequency output power of the terminal, then, the requirements of a user on transmission rate and service instantaneity are integrated, an optimal target cell is selected according to a fuzzy decision result, and then the terminal is switched to the cell for residing. According to the method, the time of the switching process is short, seamless transition can be realized, user calls can be avoided being lost, a user is ensured to reside in the cell with the optimal service quality, and furthermore, the risk of missing the call during manual mode switching is eliminated.

The invention discloses a method for detecting a tumbling state of a humanoid robot based on multi-sensor information. The method comprises the step of judging the current stability of the robot by a fuzzy decision-making system by combining the current walking state, posture information and position information of a ZMP (zero moment point) of the robot. Judgment states comprise 9 states: a controllable state, tumbling forwards, tumbling backwards, tumbling leftwards, tumbling rightwards, tumbling left forwards, tumbling left backwards, tumbling right forwards and tumbling right backwards. The method is suitable for judging whether the humanoid robot is in the controllable state when the humanoid robot is about to tumble and obtaining the tumbling direction of the humanoid robot when the robot is uncontrollable, so that a basis is supplied to generation of corresponding protection motion to the humanoid robot. According to the method, the stability of the motion of the robot can be really reflected, and the reliability and the judgment accuracy are higher.

The invention provides a global-local hybrid unmanned ship path planning method based on dynamic constraints. The global-local hybrid unmanned ship path planning method comprises the steps of: S1, constructing an unmanned ship kinematics model, and conducting kinetic analysis; S2, considering a safety range of an unmanned ship, realizing the planning of a global path of the unmanned ship by adopting a storage node mode, and constraining the safe driving of the unmanned ship by optimizing the generated path points; S3, for a dynamic unpredictable environment, constructing a hierarchical structure based on an FDM fuzzy decision module and an FDW precise dynamic window module, and realizing the planning of a local path of the unmanned ship, precisely taking drivable forward, heading angular velocities and acceleration into account in the planning of the local path, and generating a traceable path that enables real-time local collision avoidance; S4, and fusing a global path planning scheme and a local path planning scheme of the unmanned ship to form a global-local hybrid obstacle avoidance strategy. According to the global-local hybrid unmanned ship path planning method, virtual pathpoints are inserted into the global optimal path, so that global and local path planning is perfectly combined, and the whole path tracking task is completed.

The invention provides a method for intelligently scheduling buses, which is characterized in that: an electronic terminal of station is set at a bus station which is connected with a bus-mounted system through a wireless module wirelessly, and connected with a bus scheduling center through a GPRS (general packet radio service) module and a transmission network wirelessly so as to acquire the passenger flow volume at the bus station in real time. A predictor of scheduling decision software is connected with a passenger flow volume collector so as to predict passenger flows. A fuzzy decision device is connected with the predictor and the passenger flow volume collector so as to identify a bus running mode; and output of the fussy decision device is connected with a peak BP (back propagation) network, a middle-peak BP network and a low-peak BP network respectively so as to realize the optimal departure interval decisions under different running modes. The method has the advantages that: (1) the passenger flow information is real-time and reliable; (2) the prediction is scientific based on real-time passenger flow; and (3)the scheduling decisions are made under the different modes, and the results are more reliable. The method provided by the invention realizes exact monitoring, scientific prediction and reasonable decision, can be applied to the scheduling of bus system and has huge economic and social benefits.

The invention discloses a multi-objective optimization method for injection molding parameters. The method is a fuzzy decision Gkriging-NSGA-value strategy processing multi-objective optimization design method based on an improved Kriging agent model Gkriging, a non-dominated sorting genetic algorithm NSGA-II and a value set, and is used for solving the problem of fuzzy decision Gkriging-NSGA-value strategy processing multi-objective optimization design. Selecting injection mold sub-runner section size parameters and injection molding process parameters as decision variables to be optimized; respectively taking the maximum volume shrinkage rate, the flow channel total volume and the forming period of the product as evaluation indexes of the product quality, the production cost and the production efficiency, establishing a model, obtaining an optimal value of multiple targets of the quality, and realizing multi-target optimization of the comprehensive quality of the product through a multi-target decision-making method. According to the injection molding parameter multi-objective optimization method, high-quality injection molding products can be economically and rapidly obtained onthe basis of a one-mold two-piece mold.

An embodiment mode of the invention discloses an intuitionistic fuzzy association method for ADS-B monitoring data and radar tracks. The method comprises the steps of carrying out association pretreatment on the ADS-B monitoring data and radar tracks to obtain a plurality of primary association radar tracks, obtaining fuzzy intuitionistic indexes corresponding to association attributes between the ADS-B monitoring data and the primary radar tracks, obtaining fuzzy decision grades corresponding to the association attributes according to the fuzzy intuitionistic indexes, and carrying out weighing summation on the fuzzy intuitionistic indexes to obtain final associated radar tracks. The associated attributes comprise the distance, the speed, the speed difference and the course angle difference. The embodiment mode of the invention further discloses an intuitionistic fuzzy association device for the ADS-B monitoring data and the radar tracks. By means of the method, the intuitionistic fuzzy association method for the ADS-B monitoring data and the radar tracks can improve association accuracy between the ADS-B monitoring data and the radar tracks and is easy to achieve.

The invention discloses a power distribution equipment state evaluation method based on variable weight and fuzzy comprehensive evaluation. The power distribution equipment state evaluation method comprises the steps of 1, selecting evaluation indexes; step 2, index weight primary distribution: adopting an analytic hierarchy process, establishing a comparative judgment matrix by comparing the importance between every two evaluation factors, and finally calculating a feature vector under the maximum feature value to obtain the weight of each index; step 3, calculating the health state score ofeach index; step 4, weight redistribution: carrying out weight redistribution, wherein xi is the health state score value of the ith index; step 5, performing fuzzy decision index normalization processing; step 6, calculating a membership function; step 7, establishing a fuzzy evaluation matrix; step 8, determining an evaluation result by utilizing a membership degree maximum principle. The problem that in the prior art, when power distribution equipment is evaluated, other indexes with small weights cannot correctly reflect the health state of the equipment due to the fact that the indexes with large weights have too large influences on the equipment is solved.

The invention discloses a multi-target plant level load optimization method based on immune optimization and fuzzy decision in the technical field of energy-saving power generation. The multi-target plant level load optimization method comprises the steps that a thermal power plant coal consumption model, a model of time needed for completing distributed loads, and a nitric oxide emission model are established respectively; coal consumption characteristic parameters, current bearing loads, permitted load change rates and nitric oxide emission characteristic coefficients of all units in a thermal power plant are determined; constraint conditions of the models are determined, including upper limit and lower limit constraint conditions and balance constraint conditions of active power; a solution set including the active power of all the units in the thermal power plant, thermal power plant coal consumption, time needed for completing the distributed loads of the thermal power plant, and the nitric oxide emission of the thermal power plant is obtained through an immune multi-target algorithm; an optimal solution is selected from the solution set to serve as output power of all the units in the thermal power plant. According to the multi-target plant level load optimization method based on immune optimization and fuzzy decision, the immune multi-target algorithm is used for realizing multi-target plant level load distribution, an optimal power distribution scheme for the power plant units is decided according to a fuzzy decision theory, and therefore the computational process is faster and more accurate.

The invention provides a fuzzy control method and a system for the automatic combustion of an incinerator. The fuzzy control method for the automatic combustion of the incinerator comprises the steps of receiving a detection input variable sent by a detection device, calculating the deviation and the deviation change rate between the detection input variable and a given value, and adopting the deviation change rate as the input variable of the fuzzy control; fuzzifying the input variable as a fuzzy input variable, conducting the fuzzy reasoning and the fuzzy decision-making based on the fuzzy input variable to obtain a fuzzy output variable, and defuzzifying the fuzzy output variable to be as a control output variable; outputting the control output variable to a controller for the corresponding component of the incinerator so as to control the operation of the corresponding component of the incinerator. The detection input variable includes the oxygen content at the outlet of a boiler and the load of the boiler. The control output variable, corresponding to the oxygen content at the outlet of the boiler, contains the given data of the primary air flow. The control output variable, corresponding to the load of the boiler, contains an infrared temperature given value and a feeding speed value. Based on the above method and the above system, the complex control problems of multiple variables and large time delay during the waste incineration process can be solved.

The invention discloses an unmanned crane space collision avoidance strategy based on fuzzy decision inference. The unmanned crane space collision avoidance strategy includes the steps of firstly, determining the starting point and the ending point of a crane and a possible route; secondly, scanning the whole environment inside a workshop through lasers, and drawing a laser scanning result graph; calculating the space topological relations between the crane and entities such as devices and goods in all areas through the fuzzy inference and decision theory and a design algorithm when the route is selected, and judging whether the workshop is separated from the entities of equipment, goods and the like in each area of the workshop; replanning the route and executing the first step if the workshop is not separated from the entities of equipment, goods and the like in each area of the workshop; selecting and using the route and executing the hoisting task if the workshop is separated from the entities of equipment, goods and the like in each area of the workshop. The space topological relations between the crane on the assigned route and the other entities in the workshop are calculated through the fuzzy control theory and the fuzzy decision inference algorithm, the non-collision requirement of the hoisting task is met through supporting of the space topological relations, the detection means is provided for the feasibility of the route planning result of the unmanned crane, and reliability of the hoisting tank under the unmanned operation environment is improved.

The invention discloses a wireless sensor routing algorithm based on the fuzzy multi-attribute decision. The method comprises the following steps that (1) communicable nodes around the current node are created as decision schemes by starting from a source node; (2) the fuzzy attributes of the decision schemes in the step (1) are determined, and a fuzzy evaluation matrix X is established; (3) standardized processing is performed according to the fuzzy evaluation matrix so that a standardized fuzzy decision matrix H is obtained and the objective weight is determined by using the H; and the subjective weight is determined according to the preference in the fuzzy evaluation matrix; (4) the combination weight is determined by using the objective weight and the subjective weight of the previous step; (5) the combination weight is combined with the fuzzy decision matrix so as to calculate a comprehensive evaluation value, the optimal point is selected to act as a next jump node and set as the current node; and (6) whether the node belongs to a sink node is judged, and the algorithm is ended if the node belongs to the sink node; or the process returns to the step (1) for repetition if the node does not belong to the sink node. According to the technical scheme, the more stable, reliable, scientific and objective fuzzy multi-attribute wireless sensor routing algorithm can be obtained.

Provided is a method for acquiring a thermal power generating unit boiler mixed coal optimized coal blending scheme. The method, by using an objective function with maximum boiler efficiency, lowest mixed coal cost, and minimum pollutant discharge, establishes an optimized coal blending mathematic model, including a multi-objective fuzzy mathematic model, a boiler NOx discharge prediction model, and a boiler efficiency computing module, and enables the in-boiler coal blending scheme to be reasonable so as to guarantee the economical efficiency and the environmental friendliness of the operation of the boiler. The method comprises establishing the optimized coal blending mathematic model by using the objective function with maximum boiler efficiency, lowest mixed coal cost, and minimum pollutant discharge and using the boiler NOx discharge prediction model, a multi-objective fuzzy decision model, and the boiler efficiency computing module as a basis, and achieve prediction by using support vector machine technology and achieve optimization by using multi-objective fuzzy mathematic technology. The method is used for acquiring the thermal power generating unit boiler mixed coal optimized coal blending scheme.

The invention discloses a power grid vulnerability assessment method considering the minimum singular value sensitivity entropy and belongs to the field of power grid vulnerability assessment. The method includes the steps of obtaining a Jacobian matrix of a tidal current equation for a power grid to be evaluated, conducting singular value decomposition on the matrix, obtaining the sensitivity ofthe minimum singular value to a system state variable; obtaining the sensitivity of the minimum singular value to the control variable according to the hidden function derivation rule, selecting out the sensitivity of the minimum singular value to the node input active power and normalizing the data vectors; calculating the minimum singular value sensitivity entropy of the Jacobian matrix definedby the method according to the information entropy definition in combination with the weighted entropy theory, and defining a power grid vulnerability comprehensive evaluation index by using three indexes including a comprehensive power flow entropy, a minimum singular value and a minimum singular value sensitivity entropy, through a hesitation fuzzy decision method considering the reliability. According to the power grid vulnerability assessment method, the vulnerability of the power grid under multiple states can be evaluated, and the fragile link of the power grid can be effectively identified.