88 results about "Heuristic search algorithm" patented technology

The invention discloses a method for shortening an intelligent car path planning and searching time based on a heuristic search algorithm. The method can be applied to the situation that an intelligent car deviates from an initially-set optimum path due to emergency. In view of the situation, the present invention provides a path searching algorithm having a dynamic heuristic function. The method comprises the following steps: extracting environmental information in real time by virtue of a global positioning system and a laser radar of a differential technology, and establishing an environmental map containing a barrier zone and a free zone by virtue of uniform rasterization of the environmental information; and triggering a deviation mechanism in the case that the intelligent car deviates from the original path, and calling the dynamic searching algorithm, and rapidly searching a feasible path in real time. By adopting the method, the contradiction between the optimism and searching efficiency of the global path planning and searching can be effectively processed, and technical support can be provided for the path planning of unmanned driving.

The embodiment of the invention discloses a route planning method and device. The method comprises the steps of acquiring a route planning request containing a start point and an end point; acquiring an experience weight set of a section between the start point and the end point according to the route planning request, wherein the experience weight set is determined according to historical routes of a user; according to the experience weight set of the section, performing route planning for the route planning request by adopting a heuristic search algorithm. According to the technical scheme provided by the embodiment of the invention, an existing route planning technology can be optimized, and planning speed and planning result accuracy can be improved.

The present invention discloses a low-energy loss robot full coverage path planning method and system. The system comprises a robot, a ranging sensor, an encoder and an IMU. The method comprises: establishing an environment grid map by using an instant positioning and map construction algorithm; preprocessing a grid map, and adjusting a resolution and a reachable cleaning area of the grid map; defining the energy loss cost function of a mobile cleaning robot full coverage path, and calculating an optimal grid map segmentation direction by using a finite heuristic search algorithm; using the segmentation direction to perform area segmentation on the grid map through each vertex in the grid map; performing matching detection on the adjacent segmented areas, and combining the segmented areaswith a higher matching degree into a segmentation area; and determining a traversal direction according to the map segmentation direction, and sequentially traversing each segmentation area to plan afull coverage path. According to the technical scheme of the present invention, the concave polygon is segmented into convex polygons, so that planning an arch full coverage path can be facilitated, and the cleaning efficiency is greatly improved.

A method for enhanced location sensing based on topology constraints. A potential position value and a corresponding probability value with respect to an observed position data of an object within a structure can be calculated utilizing a normal probability distribution function. Thereafter, an optimal route between adjacent observed time periods may be calculated utilizing a heuristic search algorithm. The potential position value and the optimal route can be calculated by accessing a pre-installed topology data associated with the structure. An optimization problem can then be solved to refine the observed position data. The position between a pair of observed time periods can be interpolated and the position of the object before a next observed time can be predicted by interpolation based on the spatial constraints.

The invention relates to an identification method for a stressed state of a water fertilizer of a greenhouse crop on basis of a computer vision technology. According to the identification method provided by the invention, a crop under a greenhouse environment is taken as a research object; a computer vision monitoring platform is constructed; a plant image cutting method which adapts to the change in natural illumination and a complex scene is researched; an obtained plant blade image is extracted at the aspects of morphology, color, grain and the like, and sufficient characteristic sets are constructed; a heuristic search algorithm, such as a genetic algorithm, a simulated annealing algorithm, an ant colony algorithm, a particle swarm optimization, or the like, is combined with a neural network technique for searching for the optimal characteristic subset; and a BP (Back Propagation) neural network is utilized to identify a stressed characteristic of the crop. A camera is moved by using a horizontal positioning system, so that the plant image is all-dimensionally obtained; the algorithm operation is realized by using a CUDA (Compute Unified Device Architecture) hardware platform, so as to meet the real-time demand on monitoring; and the invention provides a technical method for measuring destructiveness under the stressed state of the water fertilizer of the greenhouse crop and the application prospect is wide.

The invention discloses a train conflict predicting and solving method based on a time colored Petri network. Through the method, first, the real-time state data, the train number, the path and the arrival and departure time of a train running in a railway system at the moment are acquired; according to a railway road network, a time colored Petri network model of the railway road network is established. Then, on the basis of the established time colored Petri network model, the future state of a train group is deduced, and whether potential conflict happens or not is detected; after conflict is detected, the optimal or quasi-optimal solution for solving the running conflict of trains is searched for through a heuristic search algorithm based on a Petri network reachability tree, and a train running scheme is adjusted according to a train conflict solving result. On the basis, whether a new training running scheme is feasible or not is verified through the time colored Petri network model so that it can be guaranteed that there is no conflict in the actually-executed running scheme.

The invention relates to the research field of an aircraft ground hitting protection method, and particularly relates to a flight into terrain threat avoidance method based on real-time performance of an aircraft. The flight into terrain threat avoidance method comprises the steps of predicting a future flight path of the aircraft by adopting an aircraft six-degree-of-freedom model, and performing a next step when a ground hitting threat is judged to exist from the future flight path; planning an avoidance flight path of the aircraft by adopting a heuristic search algorithm so as to acquire a planned avoidance path, wherein the step comprises restriction for constraint conditions and punishment conditions in the heuristic search algorithm; and converting the planned avoidance path into a manipulation indicator in the form of an attitude angle so as to guide a pilot to operate. The flight into terrain threat avoidance method based on the real-time performance of the aircraft can improve the alarm accuracy, and guide the pilot to perform appropriate alarm response measures, thereby not only reducing the operation load of the pilot, but also improving the safety, the economy and the comfort of flight of the aircraft.

The invention provides a thesis recommendation method based on a multilayer drawing, which comprises the following steps: Step I, taking a target thesis and candidate theses as nodes in the drawing, constructing a thesis drawing according to reference relationships among the target thesis and the candidate theses and among the candidate theses; Step II, calculating weights of words in the theses by a word weight calculation method, removing the words with the weights less than a threshold, taking the rest words as the nodes, constructing a keyword feature map by virtue of semantic dictionary information; Step III, formulating a target equation by a similarity learning method based on the multilayer drawing; and Step V, optimizing a target function by a heuristic search algorithm of the map, updating weights of sides in the multilayer drawing, and recommending the thesis according to a final multilayer drawing result. The method allows a computer to be capable of recommending the target thesis according to the interested theses read or marked by a user.

The invention discloses a screen control and handover method based on an electronic flight strip. In the method, electronic progress list is taken as a basis, by establishing heuristic search algorithm (Dijkstra algorithm) model and automatically calculating control and handover routes, the automation of the screen control and handover is realized. The method is mainly applied in air traffic control automation systems in the airports, and the automatic handover of the control authority is realized by clicking the electronic flight strip on the screen. The screen control and handover method improves the automation level of the air traffic control system and avoids the repeated control and handover, and screen control and handover optimize the control work flow.

The invention discloses a vehicle following behavior prediction method under an Apollo platform. In the construction process, dynamic information and static information in vehicle driving are obtainedthrough scene understanding; the expected distance and reaction time of a driver are obtained by capturing behavior characteristics of the driver, the defuzzification process of a vehicle following model is improved by adopting a heuristic search algorithm, and the optimal solution of the acceleration range of the following vehicle based on safety and comfort is obtained after calculation of a fuzzy reasoning model. And meanwhile, the Apollo simulation platform is used for testing and verifying the model, so that the accuracy and the practicability of the model are ensured. According to the method, the problem that only the speeds and accelerations of the guide vehicle and the following vehicle and the distance between the two vehicles are considered and the driving environment is not considered in the fuzzy theory and the artificial neural network method in the prior art is solved.

The invention relates to a method used for optimizing the electric network hydropower spinning spare capacity in the real-time dispatching. The method utilizes an EMS system to acquire the real-time electric network load data, and the ultra short-term load prediction is performed after preprocessing; the curve fitting is performed to a sequence formed by the real-time load and the predicted data based on the least square to obtain the absolute value of the maximum deviation between the sequence point and the curve, and the absolute value is determined as the hydropower spinning spare capacity of the next segment; and the no-load quotative discharge under the current water head of a hydropower generating unit is divided by the full output quotative discharge and then multiplied by the full output (i.e. the spinning spare capacity of the hydropower generating unit) to obtain a start-up ordering coefficient, and a machine set combination with the minimum energy consumption and the reserve capacity meeting the requirement is obtained by a heuristic searching algorithm. The method has the advantages that the method changes the traditional method of determining the hydropower spinning spare capacity according to a load coefficient and reduces the no-load reserve capacity of the hydropower; and the method utilizes the no-load energy dissipation coefficient to guide the start-up of the hydropower generating unit, further optimizes the economical operation of the hydropower generating unit and achieves the purposes of energy conservation and emission reduction.

The invention relates to a power optimization method for multi-target position estimation of a distributed MIMO radar system. The method comprises the following steps of taking minimum radar system transmitting power as a target function, and establishing a transmitting power optimization model under the constraints of different position estimation accuracy requirements for multiple targets and anupper limit of radar transmitting power; loosening a non-convex optimization problem of power distribution to be a convex optimization problem through an SPCA algorithm, and solving an approximate solution of power distribution; and adopting a heuristic search algorithm to carry out further optimization on a power distribution result in order to obtain an optimal power distribution result. According to the method, the resource utilization rate can be maximized and the minimum power resources are consumed under the condition that the different position estimation requirements for multiple targets are met; less system consumption can be used, the resource utilization rate is improved while the calculation amount of the system is reduced; through controlling the target number and the position estimation precision requirement, the higher the target tracking precision requirement is, the more stable the performance is, and the more the number is, the more obvious the advantages are; and the method has better application value.

The invention discloses an auxiliary method for fault location and power supply recovery based on a GIS platform. The method comprises: distinguishing regional measurement and control properties; selecting a suitable fault location method and carrying out fault location (a rough set method, a Bayes formula method, and a power distribution network fault location method based on a GIS hierarchical power supply tree method); using an FTU device or a computing device to avoid human or power distribution network information interference, and to carry out accurate fault location; using a heuristic search algorithm to carry out analysis of different power supply recovery situations such as self-feeder recovery, whole area recovery of support feeders, partial area recovery of support feeders, load shifting, load shedding, and the like of the power distribution network, and enabling selection of a power supply recovery scheme set after a power distribution network fault; and evaluating and analyzing the selected scheme set by using a fuzzy evaluation method, to select an optimal power supply scheme. According to the method, multi-class multi-source information is comprehensively obtained; a scientific and systematic comprehensive analysis method is established to locate a faulty point; an optimal power supply recovery scheme is obtained, thereby making a conventional simple determination method obsolete.

The invention relates to an algorithm for planning a lane changing track of an automatic driving vehicle by applying a potential energy field theory. The algorithm is applied to automatic driving lane changing track planning in a complex road environment. A potential energy field model of the vehicle risk is constructed by considering the position influence of the environmental vehicle and the vehicle motion trend; the lane line and the road boundary potential energy field in the road environment are described by Gaussian distribution and inverse proportion functions respectively. On the basis of a potential energy field, an unacceptable minimum risk threshold of a vehicle is calibrated, a vehicle track non-intrusive area is divided, and an A-star heuristic search algorithm is adopted to search for a path with the minimum risk value. According to the method, the actual trajectory of the vehicle is solved by adopting a self-adaptive model prediction control method, and the planned trajectory is tracked. According to the invention, the adaptability of automatic driving lane changing trajectory planning to complex roads and traffic environments is improved.

The invention discloses a method and system for mapping spiking neural network to a brain-like computing platform and a medium, and the method comprises the steps: carrying out SNN simulation and analysis, extracting a topological structure of a trained SNN network and the behaviors of neurons, and forming an undirected SNN graph and a pulse behavior track; dividing the extracted undirected SNN graph into a plurality of SNN sub-blocks, and optimizing pulse communication traffic among the SNN sub-blocks; and finding an optimal mapping scheme by using a heuristic search algorithm, allocating theSNN sub-blocks to neuron cores on the target brain-like platform, and minimizing the average hop count of pulses communicated on the target platform. The large SNN can be divided into a plurality ofsub-blocks and then mapped to the NoC-based brain-like processor to be efficiently executed, the division scheme found in time can be optimal, the cost for finding the mapping scheme can be low, the time consumption for searching is reduced, and the efficient execution of the execution speed is ensured.

The invention belongs to the field of power generation scheduling of power systems and discloses a network province two-stage multi-power short-period coordination peak shaving method. On a network province two-stage coordination platform, the operation characteristics of different types of power sources such as water, fire, pumping storage and nuclear power can be given full play to on the basis of the daily load complementary characteristic of a plurality of provincial level power grids, and the peak shaving requirements of the multiple power grids are coordinately met. According to the technical scheme, an original problem is decomposed into a pumping storage sub-problem, a conventional hydropower sub-problem, a conventional thermal power sub-problem and a conventional nuclear power sub-problem which are independent of one another according to the types of the power sources, and a pumping storage heuristic search algorithm, a water and electricity hybrid dimensionality reduction algorithm and a thermal power load shedding peak shaving algorithm are adopted for solving the sub-problems; on the basis, system loads are used as correlation factors, the preceding algorithms and an internetwork electric power distribution quadratic programming method are coupled to form a coordination framework of the sub-problems, electric power distribution of power stations among the multiple power grids is adjusted through iteration, and the differential peak value load requirements of the multiple provincial level power grids are met. Through the method, the multiple power sources and the multiple power grids can efficiently and coordinately run, a regional power grid network debugging power source peak shaving effect can be played better compared with actual scheduling, and the method is efficient and practical.

The invention discloses a large-scale road network group traffic induction task decomposing method, and belongs to the field of smart traffic, in particular to a large-scale road network group trafficinduction task decomposing method capable of changing signal timing dial. In a conventional path induction, a single function is difficult to describe a mutual relation among a plurality of variables. A plurality of target functions are established for optimal processing. The problem is solved by adopting an immune genetic algorithm, and the immune genetic algorithm is combined with an optimal heuristic search algorithm which adopts an immune theory and a genetic algorithm, and the advantages of the two kinds of algorithms are kept. The problem that the genetic algorithm is lost in local optimal solution is solved, the immune genetic algorithm has search feature, the optimal self-adaptive feature is solved by using a target function, and over-quick local convergence is avoided. A large-scale road network is decomposed into a plurality of induction cells, an induction strategy based on a tree structure chart is adopted, and an induction task is decomposed layer by layer for building aroad network to serve as a specific example for verifying the effectiveness and superiority of the method.

The invention belongs to the field of cloud computing and multi-cloud service, and relates to a method for constructing a QoS-based application optimization deployment scheme in a multi-cloud environment. According to the method, an overall design framework is expanded, and the framework comprises the steps that for a user demand entity and a cloud service entity, corresponding entity models are designed to express configuration setting of two parties for application specifications, and the problems of SLA mechanism fuzziness and an objective function are solved. Aiming at an application optimization deployment problem in a multi-cloud environment, modeling is carried out based on a QoS model, and constraint conditions and an objective function of optimization deployment are provided. Meanwhile, aiming at single-cloud application deployment and cross-cloud application deployment requests, a multi-objective optimization strategy is applied, and different solutions are given by a heuristic search algorithm. By designing an effective application service optimal deployment scheme, the automation level and the service quality level of the cloud service are improved.

The invention relates to a joint resource optimization method for multi-target position estimation in a distributed MIMO radar system. The joint resource optimization method comprises: a target is designated and a minimized maximum value of a multi-target position estimation error is used as a target function; under the circumstances that the total numbers of the transmitting and receiving array elements are limited and the transmitted power is given, a resource optimization model of combination of transmitting and receiving array element selection and power allocation is established; and on the basis of a heuristic search algorithm and a continuous parameter convex approximation algorithm, a resource joint allocation algorithm based on cycle minimization is proposed to solve a hybrid Boolean type joint optimization problem to obtain a joint resource allocation result. According to the invention, the energy relationship between system resources and tracking capabilities is analyzed quantitatively; compared with the array element number, the influence on the system performance by the transmitted power becomes obvious and the influence on the target tracking precision and number by the system resources is displayed, so that the computing load of the system is reduced, the good system performance is realized, and the overall multi-target tracking accuracy is improved. The joint resource optimization method has the great practical application value.

The invention relates to a travel navigation method meeting activity needs and path optimization, which comprises the following steps of: building initial activity schedules and listing specific activities, activity place limiting conditions and time constraint conditions of the travel by common individual travelers according to practical individual travel requirements; finding activity places capable of meeting the activity requirement of travelers by combing the intraday activity and place limiting conditions, extracting alternative activity place from the activity places for congregation; and determining the number of fixed point activity pairs, obtaining the optimal place in each fixed point activity pair by combining the time constraint condition and utilizing the heuristic search algorithm, using the optimal places as unfixed point activity places, simultaneously obtaining the optimal travel path of each activity pair in each fixed activity pair, and determining all intraday activity places and travel paths of the travelers. A geographical information system (GIS) is utilized as a technology platform, and the individual traveler is navigated according to the optimal activity places and the travel paths obtained in the step 3.

The invention relates to a rapid site selection method and device for a new store based on big data analysis, and belongs to the field of data processing and information systems. The method comprisesthe following steps of step S1 a data acquisition step; S2 a data filtering calculation step; S3 a data analysis step; S4 a data labeling step; S5 a data query step; and S6 a data updating and correcting step. The structured data information is established in a diversified data acquisition mode. A direction point matrix is constructed, multiple factors such as people flow and people flow quality (including people flow sources and directions) are fully considered, the multiple factors are integrated from one or more to-be-selected predetermined point addresses through a mathematical model in combination with a heuristic search algorithm, the objectivity of commercial site selection is enhanced, and a user can be helped to rapidly select the optimal address.

The invention discloses a cross-floor path planning method. According to the method, nodes, road segments and distances are used; and the nodes are the connection points of two or more than two road segments, and comprise a starting node, path nodes and an ending point node, the starting node is the node having the shortest distance from the a starting point, the ending point node is the node having the shortest distance from an ending point, each path node is corresponding to a distance, and each distance is the distance corresponding to each path point and between the starting point and thepath point. According to the present invention, the simple data structure is used, and the vertical road segments and the horizontal road segments are subjected to unified storage, such that the goodversatility is achieved; and the heuristic search algorithm is used in the indoor cross-floor path planning, such that the search efficiency is improved, the distance difference between elevators, stairs, escalators and other different cross-floor channels is considered, the habits of users are well met, and the user experience is effectively improved.

A method for enhanced location sensing based on topology constraints. A potential position value and a corresponding probability value with respect to an observed position data of an object within a structure can be calculated utilizing a normal probability distribution function. Thereafter, an optimal route between adjacent observed time periods may be calculated utilizing a heuristic search algorithm. The potential position value and the optimal route can be calculated by accessing a pre-installed topology data associated with the structure. An optimization problem can then be solved to refine the observed position data. The position between a pair of observed time periods can be interpolated and the position of the object before a next observed time can be predicted by interpolation based on the spatial constraints.

The invention discloses a method for extracting a characteristic line of a repair model of a tooth preparation body. The method comprises the following steps that key characteristic points in a characteristic area of the preparation body are picked up, then according to a comprehensive constrained control function, a heuristic search algorithm is adopted to obtain all optimal candidate nodes between the key characteristic points through searches, and finally, all the optimal candidate nodes are connected in sequence to form an initial characteristic path between the key characteristic points,wherein the distance, the direction and characteristics are regarded as comprehensive constraint conditions of the comprehensive constrained control function; the initial characteristic path between the key characteristic points is edited; by adopting a modified characteristic path smoothing algorithm, form optimization is conducted on the edited initial characteristic path to obtain the characteristic line of the repair model of the tooth preparation body, wherein form optimization of the initial characteristic path is completed in a three-dimensional space by the modified characteristic pathsmoothing algorithm directly according to the spatial topology form of preparation body grids. The method has the advantages that the method is accurate and stable, the efficiency is high, and the extraction quality is guaranteed, so that the method can be widely applied to the field of false tooth repair.

The invention discloses a method and system for automatically selecting an address for a cloud data center. The method comprises the steps that a mathematical model for address selection of the cloud data center is built according to an address selection standard of the cloud data center; a solution of the mathematical model is obtained from existing addresses to be selected of the cloud data center through a heuristic search algorithm, and the solution serves as the optimal set address of the cloud data center. According to the method and system for automatically selecting the address for the cloud data center, the optimal set address of the cloud data center is selected automatically from the existing addresses to be selected of the cloud data center by building the mathematical model, combining the mathematical model with the heuristic search algorithm, and synthesizing all kinds of factors.

The invention discloses an intelligent fire evacuation system and method based on computer vision and heuristic search algorithms. The system comprises a monitoring subsystem, a computer control subsystem, a single-chip microcomputer control circuit and a splicing type escape indication board; the monitoring subsystem is composed of a camera set, a smoke alarm set and a manual fire alarm; the computer control subsystem is composed of a building channel layout database, a computer vision algorithm module and a heuristic path search algorithm module; the single-chip microcomputer control circuitis composed of a single-chip microcomputer, a latch, a decoder and an alarm whistle; a plurality of escape indicating lamps are controlled at the same time under the indication of the computer control subsystem, and an alarm device is immediately controlled to give an alarm when a fire is discovered; and the splicing type escape indication board is composed of a splicing type external structure,a decoder, a logic chip and a light emitting diode. The technical scheme of evacuating crowded people by intelligently planning a secondary short escape route is realized.

The invention reveals an electric quantity balancing method and system for a battery pack, and the method comprises the steps: enabling a control system to calculate the electric quantity of each battery of the battery pack in real time; selecting the first battery for transferring the electric quantity to the second battery, and searching the shortest path for the electric quantity transfer between the first battery and the second battery through a heuristic search algorithm; and transferring the electric quantity of the first battery to the second battery through the shortest path. The method searches the shortest path for the electric quantity transfer between the first battery and the second battery through the heuristic search algorithm, greatly improves the efficiency through the directed searching, achieves the quick transfer of electric quantity from the battery with the higher electric quantity to the battery with the lower electric quantity, balances the electricity quantity in the battery pack, and improves the performance of the battery pack.

The invention discloses a test strategy rapid generation method based on a fault decision network. The test strategy rapid generation method comprises the steps: building a fault dependence matrix andthe fault decision network of a to-be-tested system, generating an optimal test point through a heuristic search algorithm, obtaining an optimal test strategy, and isolating a fault in the network through an optimal search path. Therefore, the heuristic function value is accurately estimated by combining the influence of the dependence information on the generation of the optimal strategy, and the deviation of heuristic function estimation and search strategy decision in application is reduced, and meanwhile, the optimal solution upper limit is set for each search by setting the opportunity cost, so that the search process is controlled, and the purpose of improving the efficiency is achieved.

The invention provides a bank transportation distribution line planning method and device, equipment and a medium. The method comprises the steps: obtaining basic data of a to-be-distributed service outlet; classifying to-be-delivered service network points according to the basic data; and utilizing a heuristic search algorithm to carry out distribution route planning on various to-be-distributedservice websites. Through classifying to-be-delivered service websites and employing a heuristic search algorithm for carrying out distribution route planning on various to-be-distributed service network points, the factors such as business time requirements, escort route congestion conditions and service network point geographic position distribution can be comprehensively considered according tothe classification of the service network points, and the route with the optimal cost and meeting the business management requirements is reasonably planned.

The invention aims to provide a scheme for optimizing camera deployment. According to the scheme, basic parameters of a camera are acquired firstly, a coverage rate model of the camera is establishedbased on the basic parameters, then a camera deployment optimization model is established, a set of candidate cameras is determined, and finally an optimal subset covering a target spatial point rangeis determined from the set of candidate cameras based on a heuristic search algorithm. Compared with the prior art, a heuristic search algorithm is combined with the height and the position of the camera and the area needing to be monitored, the target area is monitored by using the least number of cameras, the deployment cost of the cameras is saved, and the utilization rate and the utilizationrate of the cameras are improved.