1906results about How to "Guaranteed reasonableness" patented technology

The invention provides a concrete pump truck intelligent arm support control system and a control method thereof. The control system comprises an arm support, a controller, an operating device and an actuator. The control system is characterized in that the control system also comprises an arm support detecting device which is used for detecting the spatial location of each segment of the arm support and transmitting detected spatial location signals of each segment of the arm support to the controller. The control method comprises: the construction of an arm support coordinate system; the detection of the current arm support position; the control of the actions of the arm support. In the concrete pump truck intelligent arm support control system, an operator is not required to manually regulate the position the gyratory angle of each segment of the arm support, the pouring accuracy and the operational reasonability are guaranteed, and the construction efficiency and the whole service life of the truck are improved greatly; within the stress impact allowable range and on the basis of the consideration of the concrete fluidity, coordinated actions of a plurality of segments of the arm support are realized; simultaneously, during the controlling process, extreme conditions and unreasonable operations of the movements of a plurality of the segments of the arm support are limited, the labor intensity and the experience requirement of the operator are alleviated greatly, and influences of unreasonable operations on the arm support structure and the service life of a hydraulic system are avoided.

The invention discloses a diagnostic method for a vehicle condition, and belongs to the field of automobile fault diagnosis. The method comprises that: a vehicle condition diagnosis and analysis model of a remote diagnostic center is built; Bluetooth connection between a terminal of a vehicle and on-board diagnostics-II (OBD-II) is built, OBD-II vehicle data are collected; the terminal sends the collected vehicle data according to a preset frequency to the remote diagnostic center through general packet radio service (GPRS); the remote diagnostic center is based on the vehicle data and the diagnosis and analysis model, according to the choice of a user, the vehicle condition is diagnosed according to an instant diagnostic mode or a month diagnostic mode. The diagnostic method for the vehicle condition solves the problems that the prior diagnostic method relies on professional equipment, diagnostic data are limited, and comprehensive diagnosis data banks are lacking.

The invention opens a data mining system based on Web, which mainly includes EJB server, Web server and database etc. The EJB server provides the interface between Web server and EJB layer, and implemented various data mining algorithms for different data and data mining tasks. The Web layer provides a user interactive interface to receive user inputs and display results of data mining and analysis. The system consists of several modules: authentication module, initialization module, data connection module, data visualization module, data pre-processing module, mining module, mining data indication module. The system provides on-line internet based data mining and result analysis services.

The invention relates to the technical field of ship collision avoidance, in particular to a method for detecting the degree of risk of ship collision on the basis of an evidential reasoning theory, wherein the method is used for assisting ship drivers in making decisions and guaranteeing safe navigation of ships. The method for detecting the degree of risk of ship collision includes the steps that dynamic data of navigation of threatening ships are acquired through an automatic identification system (AIS) of a ship, values of influential factors are calculated, subjection degree values of all the factors are calculated, weights are allocated to five factors through a hierarchical classification method, and confidence coefficient values of all the factors on the corresponding evaluation levels are calculated; confidence coefficient vectors of the threatening ships on the evaluation levels are calculated; degrees of threat of the threatening ships are crystallized, and CRI values of the threatening ships are obtained; the obtained CRI values are output and displayed on a comprehensive ship display system. According to the method for detecting the degree of risk of ship collision, while the uncertainty of obtained data of the threatening ships and the uncertainty of expert experience are fully considered, the degrees of threat of the threatening ships to the current ship are reasonably evaluated through superiority of the evidential reasoning theory for representing and fusing uncertain information.

The invention discloses a CT (Computed Tomography) value correcting method for cone-beam CT. The CT value correcting method comprises the following steps: scanning air, a water phantom and a bone tissue body phantom under different scanning conditions to respectively obtain projection data; reestablishing an image; removing noise and artifacts by adopting a polynomial fitting method based on a template image; selecting a plurality of interested regions and calculating a mean value of an attenuation coefficient and a standard deviation of the attenuation coefficient; obtaining the value range of the attenuation coefficient and taking the attenuation coefficient of maximum occurrence probability; fitting the attenuation coefficients of the air, the water phantom and the bone tissue body phantom under the different scanning conditions with corresponding ideal CT values to obtain respective fitting curves; performing CT scanning and image reestablishment on a scanned material; obtaining a CT value image according to a material attenuation coefficient image and a fitting curve and finishing the CT value correction. According to the CT value correcting method disclosed by the invention, image noise and artifact can be effectively reduced, the reestablished image of single material reaches the uniformity to the great degree, the precision of the attenuation coefficient of the material becomes higher and further high accuracy for the fitting of the curve of the CT value and the material attenuation coefficient is realized.

The invention belongs to the technical field of public transportation dispatching, and discloses an intelligent bus dispatching operation method. The method comprises acquiring the passenger flow data and/or the revenue from operations, and acquiring the vehicle model full load rate for line vehicle allocation to obtain the number of laps for planned departure of vehicles; acquiring the departure time of the first and last vehicles, according to the number of laps for planned departure of vehicles, obtaining the reference departure interval in the whole day, acquiring the crest segment setting in an expert system, obtaining the practical departure time for every lap, and forming a departure time table; acquiring the service time for the whole course for single time, according to the departure time table, obtaining the minimum planned departure number which can be revolved, acquiring the fatigue driving time limitation for a driver to obtain the practically required number of drivers corresponding to different departure numbers, and comparing the cost for two-by-two combination for different departure numbers with different numbers of drivers with the driving time of the drivers in different combinations; and outputting the departure time table, the practical departure number and the number of drivers as a bus dispatching operation scheme. The intelligent bus dispatching operation method can reasonably realize bus dispatching and improve the operation efficiency.

The invention discloses an inner and outer layer nesting ECMS (equivalent fuel consumption minimization strategy) multi-objective double-layer optimization method. The inner and outer layer nesting ECMS multi-objective double-layer optimization method includes steps of building multi-objective optimization models of plug-in hybrid electric vehicles; solving the multi-objective optimization modelsby the aid of inner and outer layer nesting multi-objective particle swarm algorithms to obtain multi-objective optimized Pareto solution set front edges; weighting equivalent fuel consumption per hundred kilometers and variation ranges of deviation of SOC (state of charge) final values and target values, building total evaluation functions related to the equivalent fuel consumption per hundred kilometers and SOC deviation and selecting the optimal charge and discharge equivalent factors and engine and motor power distribution modes corresponding to the optimal charge and discharge equivalentfactors. The inner and outer layer nesting ECMS multi-objective double-layer optimization method has the advantages that output power of engines and motors of the plug-in hybrid electric vehicles canbe reasonably distributed at CS (charge sustaining) stages, so that fuel consumption can be reduced as much as possible, battery SOC balance still can be effectively kept, and the fuel economy of theintegral vehicles can be improved.

The invention discloses a transmission system gearbox reliability test bed of a high-speed multiple unit. The transmission system gearbox reliability test bed of the high-speed multiple unit comprises an L-shaped bearer platform power flexible driving torque tester, a rectangular bearer platform power flexible driving torque detection tester, a trial gearbox assembly tester and a three-DOF (degree of freedom) vibration simulation test device, wherein the trial gearbox assembly tester and the three-DOF (degree of freedom) vibration simulation test device are mounted in parallel on the foundation, and a trial gearbox in the trial gearbox assembly tester is connected with a tested gearbox in the three-DOF (degree of freedom)vibration simulation test device through a synchronous universal joint coupling of a ball cage type. The L-shaped bearer platform power flexible driving torque tester is connected with the trial gearbox assembly tester trough a cross axial universal coupling, and the rectangular bearer platform power flexible driving torque detection tester is connected with the three-DOF (degree of freedom) vibration simulation test device through the cross axial universal coupling.

The invention relates to the design technology of computer-assisted cable laying, in particular to a method for designing a cable path of a nuclear power station according to an established cable bridge network. The method comprises the following steps of: establishing the matching relation between a cable and a bridge, and establishing a one-to-one relation list between the type and series colorcodes of the cable and the type and series color codes of the bridge; modeling equipment at two ends of the cable in a database, and establishing data of the cable in the database according to a cable list; arranging reasonable approach points for the equipment at two ends of the cable according to the arrangement condition of the equipment, so that the approach points are used as a starting point and a terminal point in the cable path design process; and selecting the path reasonably according to a cable bridge network data model to lay the cable. When the method is used, the design of the cable path can be completed quickly, and problems of layer jump, the rationality of laying, work efficiency and the like in the conventional cable path design also can be solved.

The invention discloses an uncertain software credibility assessment method based on an evidence theory. The method comprises the following steps that: (1) on the basis of a utility theory and the evidence theory, a software credibility assessment process requesting driving is defined and critical scientific problems and study difficulties to be solved are demonstrated clearly in credibility assessment reasoning process; (2) the standard formal definition of a multiscale quantitative index system TEIS based on multidimensional credible attribute is given; (3) ignorance space in an original cautious connection rule is differentiated and is led into an association coefficient based on discount and relative weight and a novel evidence composite rule-ECCR under relative belief background is defined in order to blend uncertain information; and (4) in accordance with complex hierarchy characteristic among credible indexes, a software credibility assessment reasoning module relative to a consideration information source is established, the uncertain software credibility assessment reasoning module is structured and solved according to the evidence theory and ECCR is used to solve the information fusion problem under the relative background of assessment information source.

The invention discloses a scoring card development method based on machine learning. The scoring card development method comprises the following steps: (1) defining a label of a target user accordingto vinage analysis; (2) integrating various data sources to obtain final data; (3) carrying out exploratory analysis and data cleaning on the data; (4) using an optimized chi-square binning method tobind the cleaned data; (5) carrying out variable screening on the box-separated variables; (6) constructing a logistic regression model; (7) evaluating the model; And (8) converting the model output target user default probability into a score. According to the method, machine learning, vinage analysis and a logistic regression model are utilized, and the problem is converted from manual solutionto machine solution according to the difficulties of low manual efficiency, difficulty in auditing and the like in the big data era.

The invention provides a hierarchical road network-based path search method and a hierarchical road network-based path search device. The method comprises the following steps of: searching a local optimal path RSJ=(S, ..., and Ji) of a starting point S and a local optimal path RNE=(Nk, ..., and E) of a finishing point E in a preset range in a lower road network respectively, wherein a node Ji and a node Nk are nodes in an upper road network; searching a local optimal path RJN=(Ji, ..., and Nk) of the node Ji and the node Nk in the upper road network; and combining the local optimal paths to obtain an optimal path from the starting point S to the finishing point E, namely RSE=(S, ..., Ji, ..., Nk, ..., and E). In the scheme, the road network search scale is controlled by the local optimal paths of the starting point and the finishing point in the preset range; and the optimal path between the remote nodes Ji and Nk is searched in the upper road network with a small road network scale, so that the overall search scale is in a small controllable range, and path search efficiency is greatly improved.

The invention provides a personalized tour route recommendation method. The personalized tour route recommendation method comprises the steps that 1, travel note information of tourists is obtained and preprocessed; 2, a scenic spot type expression vector based on category information is obtained; 3, a touristy preference expression vector of each user, touristy preference expression vectors of the tourists in each month and an expression vector of each scenic spot are obtained; 4, a candidate tour route set is obtained according to step 1; 5, candidate tour routes are obtained from the candidate tour route set according to individual constraints; 6, a preference expression vector to which each tour route belongs is obtained; 7, similarity matching is carried out on the user touristy preference and the candidate routes to obtain the playing route which is most matched with the user touristy preference to serve as a final tour route recommended to the users. In the method, according toeach scenic spot in a historical tour track of the tourists and the scenic spot category information to which the scenic spots belong, the personalized touristy preference of the tourists is obtained.

An intelligent power generation control method based on multi-agent reinforcement learning having time tunnel thought includes the following steps: determining a state discrete set S; determining a combined action discrete set A; collecting real-time operating data of each power grid, calculating an instantaneous value of each area control error ACE(k) and an instantaneous value of a control performance standard CPS(k), and selecting search action a<k>; in the current state s, obtaining a short-term award function signal R(k) by a certain area power grid i; obtaining value function errors rho<k> and delta<k> through calculation and estimation; updating a Q function table and a time tunnel matrix e(s<k>, a<k>) corresponding to all states-actions (s, a); updating Q values and updating a mixed strategy pi(s<k>, a<k>) under the current state s; then updating a time tunnel element e (s<k>, a<k>); selecting a variable learning rate phi; and updating a decision change rate delta (s<k>, a<k>) and a decision space estimation slope delta<2>(s<k>, a<k>) according to a function. The intelligent power generation control method based on multi-agent reinforcement learning having time tunnel thought aims to solve the problem of equalization of multi-area intelligent power generation control, has a higher adaptive learning rate capability and a faster learning speed ratio, and has a faster convergence rate and higher robustness.