174 results about "Decision scheme" patented technology

The invention discloses a multi-vehicle cooperative driving method and apparatus for driverless vehicles based on Internet-of-vehicles. The method includes obtaining the current driving data of a vehicle and road condition information on a real-time basis, receiving shared current driving data and road condition information sent by other driverless vehicles within a predetermined distance, planning the driving decision scheme of the vehicle through analysis according to the current driving data and road condition information of the vehicle and other driverless vehicles, and executing the driving instruction according to the driving decision scheme, wherein the driving decision scheme comprises driving priority and a driving path. The method allows each driverless vehicle to plan a driving decision scheme according to the current driving data and road condition information of the vehicle and other surrounding driverless vehicles on the real-time basis, and the public road utilization rate and driving safety level of each driverless vehicle are improved.

The invention provides a multi-cycle installment decision making method and a multi-cycle installment decision making system. The multi-cycle installment decision making method comprises the steps of: acquiring user credit investigation information of a target user according to an installment request input by a user end or an external trigger, wherein the user credit investigation information comprises anti-fraud information and credit information of the user; applying for anti-fraud scanning based on the anti-fraud information and a called anti-fraud model, so as to obtain risk rating information; applying for credit scanning based on the credit information and a called credit model, so as to obtain credit rating information; and matching the risk rating information with a risk requirement and matching the credit rating information with a credit requirement in installment decision making, so as to output matched installment decisions. The multi-cycle installment decision making method and the multi-cycle installment decision making system can extract effective user information for data processing through classifying and integrating a large amount of user information, and feed back installment decision making schemes timely and accurately.

The invention provides a space-time regulation and emergency guidance system and method for scenic spot tourists. The space-time regulation and emergency guidance system for scenic spot tourists comprises a hardware basis platform and an application software system, wherein the hardware basis platform comprises a tourist flow volume collector, a video monitor, a multimedia service terminal, a TRE server and a control management platform; the application software platform comprises a tourist flow analysis module, a video analysis module, a space-time regulation module, a TRE database, a scenic spot tour guidance module, a flow distribution and emergency guidance module, a flow distribution and emergency monitoring module and a TRE management module, and the tourist flow analysis module is used for judging the saturation condition of the tourist flow volume of a scenic spot and judging whether abnormal phenomena exist in the scenic spot by analyzing the bidirectional tourist flow volume, which is collected by the tourist flow volume collector, of a dispersion point in the scenic spot and the tourist flow real-time state, which is collected by the video monitor, of a scenic spot core area and a dispersion thoroughfare; according to a judgment result, the flow distribution scheme and the emergency decision scheme of each scenic spot are matched according to the relevant setting of the TRE database; information is transferred to tourists by the multimedia service terminal to guide the tourists to choose a touring route; and the situation of excess tourists in certain space time is alleviated.

The invention, which belongs to the virtual simulation technology field, more particularly relates to an integrated traffic simulation system based on interaction usages of macroscopic, mid-scopic and microscopic traffic simulation platforms. The system comprises a macroscopic traffic simulation module, a mid-scopic traffic simulation module, a microscopic traffic simulation module and a data collection and fusion module. The mid-scopic traffic simulation module is connected with the macroscopic traffic simulation module; the microscopic traffic simulation module is connected with the mid-scopic traffic simulation module; and the data collection and fusion module is respectively connected with the macroscopic traffic simulation module, the mid-scopic traffic simulation module and the microscopic traffic simulation module. According to the invention, on the basis of independent simulation of macroscopic, mid-scopic and microscopic traffic simulation platforms, interaction utilization of all layers of simulation systems and various simulation platform data is realized; traffic operation states of traffic flows and pedestrian flows large-scale activities can be comprehensively simulated; therefore, a technological basis can be provided for formulation of various traffic decision schemes of large-scale activities.

The invention discloses a diagnosis and treatment decision-making support system. The system includes a human-computer interaction unit, a processing unit, a decision-making support unit and a database unit, wherein the human-computer interaction unit is used for a user to exchange data with the diagnosis and treatment decision-making support system, the processing unit is connected with the human-machine interaction unit and is used for performing business and data processing, the decision-making support unit is connected with the processing unit and is used for feeding back decision-making schemes according to input data, and the database unit is used for storing medical treatment data to provide a data foundation for the decision-making support unit. The system of the invention can maximally conform to actual clinical diagnosis and treatment processes and provide full-process diagnosis and treatment decision-making services for doctors. With the diagnosis and treatment decision-making support system of the invention adopted, diagnosis and treatment schemes and suggestions can be provided for doctors; the doctors can be assisted to improve decision-making levels; the doctors canbe prompted with potential errors; diagnostic suggestions and decision-making schemes can be provided according to the disease conditions of specific patients, so that the doctors can be assisted to comprehensively understand a wide range of possibilities; the doctors can be assisted to make better decisions, so that a misdiagnosis rate can be reduced; and the system can be combined with the actual diagnosis and treatment processes, so that the actual diagnosis and treatment processes can be standardized.

The invention provides a melon growth management expert system based on the Internet of Things. The melon growth management expert system comprises a main interface module, an expert knowledge base module, a monitoring information module, a growth simulation and prediction module, a decision-making and inference module, an expert consultation module, a personal information module and a backgroundmaintenance module. The melon growth management expert system manages melon real-time growth environment monitoring, growth status monitoring, water and fertilizer amount and environmental temperatureearly-warning as well as pest and disease damage judgment combined with an image recognition technology, realizes melon growth and development simulation and yield quality prediction, and is equippedwith a planting knowledge base and an expert online question answering function. The melon growth management expert system realizes real-time monitoring of environment and plant growth information, is conductive to planting decision-making, reminds the user to improve the management conditions through real-time water and fertilizer amount and environmental temperature early-warning, realizes high-precision simulation of plant growth indexes, fruit quality and yield, and provides real-time water and fertilizer precise decision-making scheme according to comprehensive analysis of real-time environment and plant growth monitoring, data processing based on a machine learning method, plant growth model prediction and the like.

The invention relates to an optimal selection method of an extra-high voltage transformer substation location. The method is characterized by: firstly, establishing an index parameter which is used to plan an extra-high voltage transformer substation location layout; carrying out a system comprehension assessment on the location of the extra-high voltage transformer substation from five aspects of an economic index parameter, a security index parameter, a location area characteristic index parameter, a perspective adaptability index parameter and a coordination index parameter; according to the assessment, providing an extra-high voltage location grey integration optimization selection method based on a moment estimation theory; through the moment estimation theory, considering a subjectivity of a decision maker and objectivity than weight changes as time flies; finally, through the grey integration optimization selection method, carrying out optimization selection of a decision scheme. The method of the invention provides an important theory guidance for the extra-high voltage location program and possesses scientificity and rationality.

The invention relates to an information classification processing system and method based on an urban IoT (Internet of Things), particularly relates to an information classification processing, prediction, decision and automatic learning method, and belongs to the technical field of IoT information processing. The system comprises a sensing layer, a data transmission layer, a data filtering layer,an information definition layer, an information processing layer, a decision supporting layer, a network layer and a decision tree autognosis method based on a self-built database; real-time sensed data is output at regular time by the data transmission layer; and the decision supporting layer carries out analysis statistics according to information uploaded by the information processing layer, combines instant information to carry out comparison with historical information, predicts future information which cannot be obtained in real time by a sensor and event trends, calculates an occurrence probability of an event along with a master variable at a future time point, makes a plurality of suggestion decision schemes, selects an optimal scheme to execute, collects process information andresult information and establishes a decision tree model, and after repeated optimization, the system automatically learns and carries out cognition, so that a decision is gradually made by the system.

The invention discloses a river lake water body quantity-quality coupling self-optimizing simulation regulation and control method which comprises the steps that first, a water body quantity-quality coupling simulation model in a river lake zone to be regulated and controlled is established; second, according to the water body quantity-quality coupling simulation model and a current decision scheme, the simulated results of the water quantity, the water level and the water quality of the river lake zone to be regulated and controlled are obtained; third, the water quantity, the water level and the water quality are used as decision targets, an optimization decision zone of a river lake water body system is established; fourth, whether the simulated results of the decision targets meet the requirement of the river lake water body system at the same time is judged, and the current decision scheme is corrected according to the judging results. According to the method, the water quantity, the water level and the water quality of a river lake water body are regulated and controlled in a combining mode, and accordingly water resource efficient allocation is achieved.

The invention provides a basic sharing platform for Internet of things, which comprises a support platform module, an information source module, an information layer module, a security mechanism module, an information management module, an output layer module and an application layer module, wherein the information source module acquires information from the support platform module and sorts the information, the information layer module transmits the sorted information to the information management module through the security mechanism, the information management module integrates and manages the information and transmits the information to the application layer module through the output layer module, and users can acquire required information resources from the application layer module. The interactive transmission of the information is realized between the support platform module and the information source module as well as between the information management module and the application layer module. The invention establishes a common basic support platform for the cerebral nerve system layer of Internet of things, completes data analysis and decision schemes and realizes the information integration between the human society and the physical system.

The invention relates to the field of risk identification and early warning, in particular to a risk information automatic classification, identification and early warning method and system. The method comprises the steps of S1, receiving information sent by a user and taking the information as a risk target; S2, performing risk information classification and identification processing on the information to obtain a risk type of an environment in which the user is located; S3, outputting a corresponding early warning signal according to the risk type; and S4, providing an emergency decision scheme according to the early warning signal. According to the method, the information sent by the user is subjected to the risk information classification processing firstly, then the corresponding early warning signal is output according to the classification condition, and the corresponding emergency decision scheme is provided according to the early warning signal; and the method integrates risk identification, classification and early warning functions, and can provide countermeasures for the user timely according to the information sent by the user.

The invention belongs to the technical field of emergency plan management and relates to a method for generating a plan based on a cognitive model. The method comprises the following steps of: inputting a bound variable by a decision maker, and calculating the level of the emergency by a system; performing characteristics matching in a case and plan base; if the matching is successful, outputting action sequences in a corresponding plan and a corresponding case, and judging the validity according to a situation; if the matching fails, returning to an initial state; if the generated initial plan decision scheme needs adjusting, performing re-matching on the case and the plan; and if the generated initial plan decision scheme does not need adjusting, obtaining a target plan decision scheme. Due to the adoption of the cognitive model and the plan CSP matching algorithm, the method has higher accuracy and real-time characteristic, and provides effective situation integration information and decision-making information for the decision maker by using the high-performance calculation power of a computer; and simultaneously, the high cognition of the decision maker on the field is fully utilized, and a comprehensive emergency plan is repeatedly studied under the intervention of the decision maker, so higher reality usability is achieved.

The invention relates to an emergency decision-making method of an emergency based on scenario analysis. The purpose of the invention is to solve the problem that the existing emergency response mechanism is unreasonable, Emergency management personnel directly relying on experience or using artificial neural network to carry out emergency decision-making methods cannot shorten the response time,which is not in line with the actual situation, resulting in low efficiency and low accuracy of emergency management. A method for emergency decision-making based on scenario analysis includes the following steps: step 1, constructing a basic scenario database; step 2, extracting feature element knowledge elements of that target scenario from the target scenario, input the feature element knowledge elements of the target scenario into a basic scenario database for searching and matching, and obtaining a corresponding emergency decision scheme; The invention belongs to the field of emergency traffic management.

The invention discloses a dynamic path node positioning method based on direction decision. The method is characterized by adopting a directional antenna to identify the direction of sensor nodes in communication; then, determining the next moving direction of each mobile anchor node by utilizing a direction decision scheme, the moving angle according with the equilateral triangle optimal principle; every time each anchor node moves for a step, broadcasting the coordinate information of the anchor node; after an unknown node receives four anchor node data packets, carrying out self-positioning through a trilateral positioning algorithm selected based on weight; and after each anchor node traverses normal path, carrying out further positioning optimization through a grid-progressively-increasing type optimization algorithm. The positioning method is used for positioning of nodes of a U-type or Z-type wireless sensor network, the distribution of the sensor nodes of which is uneven but continuous; the positioning precision is high; and the path planning is very flexible.

The invention discloses a reconfigurable assembly line multi-target scheduling decision method. The method is characterized by comprising the following steps: 1) constructing an index feature value matrix of a reconfigurable assembly line multi-target scheduling decision; 2) constructing a standardized decision matrix of the reconfigurable assembly line multi-target scheduling decision; 3) computing a grey relational coefficient of a desired reference vector; 4) computing an objective weight through entropy; 5) computing a subjective weight through an AHP (analytic hierarchy process); 6) constructing a non-linear target programming model to compute the combined weight of the objective weight obtained in the step 4) and the subjective weight obtained in the step 5); 7) computing a desired reference vector relevancy according to the combined weight obtained in the step 6) and the grey relevancy coefficient obtained in the step 3); 8) making out the approach degree of a constructed vector and a positive desired reference vector according to the desired reference vector relevancy obtained in the step 7) and the standardized decision matrix obtained in the step 2); 9) selecting a decision scheme with the maximal approach degree as the optimal decision scheme. By using the approach degree as the judgment basis of the decision scheme, the evaluation result is more reliable and credible.

The invention discloses a method for optimizing and determining a disaster-reduction decision scheme, which comprises a server, a database built therein, and a data processing module established for performing operation by using a central processing unit of the server and receiving and outputting data through a terminal connected with the server electrically. Particularly, the database includes an optimization model base providing an optimized reference scheme for a disaster-reduction decision and a scheme and disaster situation information database providing assistant correction information and data for the reference scheme so as to generate the final decision scheme; and the data processing module includes a decision scheme optimizing module, a decision scheme determining module and a decision scheme output module, which are used for generating the optimized reference scheme with a formative requirement of materials, the distribution of the materials and an order of recovery and reconstruction projects, generating the final decision scheme, sending the final decision scheme to a historic case base in the scheme and disaster situation information database in a required mode, and outputting the final decision scheme by the terminal. The method for optimizing and determining the disaster-reduction decision scheme can provide the determined disaster-reduction decision scheme after natural disasters of all kinds occur.

The invention discloses a wide-range power transmission line forest fire emergency disposal optimization intelligent decision making method. The wide-range power transmission line forest fire emergency disposal optimization intelligent decision making method comprises the following steps of 1 obtaining power transmission line warning forest fire point data; 2 calculating a distance between a fire point and a nearby pole tower; 3 predicting the dangerousness degree of the fire point; 4 sequentially arranging extinguishment; 5 searching reserved data of extinguishment facilities; 6 generating a plurality of extinguishment emergency disposal decision schemes; 7 selecting an optimal emergency disposal decision scheme from the extinguishment emergency disposal decision schemes generated in the step 6, namely a wide-range power transmission line forest fire optimal emergency disposal intelligent decision scheme. The method had the advantages that limited extinguishment teams and materials can be utilized to the most degree so as to achieve optimal power transmission line forest fire disposal efficiency and benefit; advanced deployment can be guided, the forest fire disposal capacity of a power grid can be 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.

The invention belongs to the field of multi-attribute decision making, and discloses a method and system for interval intuitionistic fuzzy multiple attribute decision-making base on improved entropy and score function. Aiming at the popular problem of supplier selection, the fuzzy entropy of uncertainty and hesitation is used to determine the weight of each index under the condition that the weight of supplier attribute is completely unknown, and the objective weighting method is used to correct the deviation caused by the agent preference. The new score function is used to sort the scheme set, and the final supplier selection scheme is obtained. The invention utilizes an improved method to calculate the attribute weight according to the contribution degree of the attribute to the decisionscheme. In view of the limitation of the existing score function, a new score function is proposed. The weight of the attribute is correctly and reasonably calculated, and the score function makes upthe problem the other sorting functions fail to sort certain interval numbers to a certain extent. When the invention selects suppliers for enterprises, the invention provides a more objective and reasonable method.