110 results about "Dynamic decision-making" patented technology

An active collaboration technology in an open architectural framework that delivers information and decision support tools in a timely, contextual and role sensitive manner to present a collaborative dynamic decision making capability to a community of role players within a supply chain process. Such a comprehensive collaborative dynamic decision making capability is made possible through the integration of the business process, the organization of role players and relevant business applications.

The present invention relates to utilizing identity and context-sensitive decision-making for handling communications, including, channel selection, routing, and rescheduling operations. The systems and methods provide a service that allows users to assess preferences regarding real-time call handling and performs dynamic decision-making about the best timing and channel for interpersonal communication. This service can be based on various cost-benefit analyses (e.g., basic and extended) that consider cost of interruption and preferences of contactors and contactees to guide communications, and/or on decision-making under uncertainty. Statistical models that are learned from data are joined with user preferences to generate expected costs of interruption for office activity and over time, based on a user's activities, locations, calendar information and preference assessments. In addition, statistical forecasting provides presence and availability predictions. The foregoing can provide an enhanced interpersonal communication system that can maximize the value and minimize the cost of communication among people.

The invention discloses a no-signal intersection vehicle intelligent cooperative passage method based on a CPS (Cyber-Physical System), aiming to overcome the shortcomings of green light zero passage and low passage efficiency caused by fixed traffic light time control, and lack of information interaction among vehicles in the intersection passage management of prior art. Based on the deep fusion of the 3C (computing, communication and control) technology in a CPS, and supported by the GPS technology, vehicle-vehicle communication technology and speed intelligent control technology, the method is provided and comprises three steps of vehicle passage data acquisition, information processing and communication, and decision control; vehicles close to an intersection continuously obtain the passage information of local vehicles, and perform communication interaction with vehicles in other directions so as to percept surrounding environments in real time, and on the basis, the method performs dynamic decision making and control, i.e., the method analyzes whether the local vehicles and other vehicles exist potential bump risks according to the passage information of surrounding vehicles, cuts the risks, considers vehicle passage priorities, controls speeds and ensures vehicle safe and efficient passage.

The invention discloses a multipath parallel transmission dynamic decision-making method based on path quality. In consideration of the influence on the whole network transmission performance by the path quality difference, the method comprises the following steps: firstly sending a detection data packet to measure four parameters for deciding the path quality in real time: delay, jittering, packet loss probability and cache occupation rate, feeding back the measured data to a sending end, and processing the measured data through a TOPSIS method in a sending end cache area, selecting out the most appropriate path combination for data transmission, and then sending the to-be-transmitted data packet, when the data packet arrives the receiving end, sending the selected path with the minimum delay to a feedback ACK to a receiving end. The design disclosed by the invention sufficiently gives full play to the advantage of the dynamic decision-making path, the network throughput out is improved, and the efficient data transmission is realized.

The invention relates to the technical field of artificial intelligence, and provides a ten-thousand-level intention classification method and device, a storage medium and electronic equipment. The ten-thousand-level intention classification method comprises the steps of obtaining a dialogue statement of at least one round of dialogue with a user; performing context analysis on the dialogue statement to complement the context information of the dialogue; performing semantic analysis on the dialogue statement to obtain a plurality of candidate intentions of the user; and based on the pluralityof candidate intentions and the complemented dialogue context information, determining a real intention of the user by utilizing an intention decision model constructed based on a reinforcement learning algorithm. The method is realized based on a brand-new three-layer man-machine conversation technology framework. According to the method, the plurality of candidate intentions are obtained throughsemantic analysis on a semantic understanding layer, complemented context information is obtained through context analysis on a logical reasoning layer, dynamic decision making is conducted on a decision judgment layer through an intention decision making model according to the candidate intentions and the complemented context information, and the accuracy of intention classification through themethod is high.

The invention discloses a security policy dynamic acquisition method of a process control system based on an attack-defense game. The method comprises an offline process and an online process; the method comprises the following steps: firstly, analyzing the process control system and establishing a Bayesian network; secondly, building a defense strategy model; thirdly, screening a potential attack strategy set and a potential defense strategy set; fourthly, quantizing an attack-defense payoff matrix; and finally, according to the attack-defense payoff matrix, establishing an equation solution and acquiring an optimal security strategy. The method of the invention comprehensively considers various consequences caused by the attack-defense strategy, and performs uniform scale quantization; an idea of an attack-defense game theory is introduced to a solving process of the optimal security strategy, so that the problems that the traditional dynamic strategy decision is excessive responsive, and the response mode of a dynamic decision response method is fixed and easily exploited by attackers are solved; and besides, the Bayesian network and the attack-defense strategy model are used for screening the potential attack-defense strategy, so that the number of alternative attack-defense strategies can be greatly reduced, thereby reducing the computing time of cost-benefit quantification of the attack-defense strategies, and improving the real-time performance of a dynamic decision.

A method of updating prices, includes automatically and continually adjusting prices of goods and services provided by a company through local outlets located across a geographic area, including activating trigger sources, the trigger sources including static and dynamic causes, inputting additional parameters, the parameters including a competitor's name, location, price of an item, a time and date, and an observed popularity of an item, storing the additional parameters in a historical database, making dynamic decisions for adjusting the prices across the local outlets based on the trigger sources and the additional parameters, the making dynamic decisions being based on the trigger sources, the additional parameters, and company selected criteria, which includes revenue targets, market conditions, market forecasts, and historical data, automatically adjusting a price of goods and services provided by the company.

The invention provides a power distribution network state estimation method based on a firefly algorithm. The method comprises steps as follows: Step 1, generating a power distribution network node admittance matrix; Step 2, initializing fluorescein and dynamic decision domains of fireflies; Step 3, updating the fluorescein of the fireflies; Step 4, calculating the distance between the fireflies to acquire neighborhoods; Step 5, calculating the movement probability of the fireflies; Step 6, updating positions of the fireflies; Step 7, updating the dynamic decision domains of the fireflies; Step 8, judging whether a convergence condition is satisfied or not, if the convergence condition is satisfied, ending the process, executing Step 9, and otherwise, executing Step 3; Step 9, outputting an optimal solution. According to the method, node voltage is used as a state variable, the node injection power is calculated, an objective function value of the least square method is taken as a firefly fitness function value and converted into the fluorescein of the fireflies, the state variable is updated continuously, and the firefly position with the highest fluorescein is taken as the optimal state estimation result. Experiments indicate that the method has good accuracy and adaptability.

Processing provides a high level of automated decision support using COTS computing software and hardware. By combining information gathered from multiple structured and unstructured data sources and converting to a common protocol shared with the conditional decision logic, the operator is freed from the task of continually monitoring the situation for compliance with pre-established rules. By organizing the conditional and simulation logic of the system in a hierarchical manner, rules are applied to data-based entities, their interactions, and the overall operational situation, and then to established procedures. The hierarchical organization of the conditional logic permits a high level of control over aggregated complex rule-based processing, and provides dynamic behavior, allowing modifications of the entire system processing to be based on the simplest human interaction or a single change in the state of one data item gathered by the system.

The invention relates to a method for dynamically updating a rule set during a changing process of an attribute set in a rough set. According to the method provided by the invention, a dynamic change rule of a decision rule set is discussed in the aspect of dynamic change of an approximation set, simultaneously a change rule for the decision rule set when a conditional attribute set and a decision attribute set are simultaneously changed is provided, and a method for dynamically updating increment of the decision rule set when a conditional attribution is increased or deleted is provided. The technical scheme is as follows: when the attribute set in a dynamic decision information system changes, a change trend of the dynamic rule is analyzed, a dynamic rule updating algorithm while changing the attribute set is provided, and the correctness of the dynamic rule updating algorithm is verified by virtue of examples. Subsequent main work comprises testing performance of a rule increment updating algorithm by virtue of experiment and simulation, analyzing and expanding dynamic change of the rule set while changing the attribute set in a rough set model, and updating rule increment as well as assisting in making a better decision in each application field.

The invention provides a backward learning-based dynamic multi-attribute service selecting method. The method comprises the following steps: 1, user preferential learning based on backward learning: initializing a service set, a user set, a service evaluation level set and a user non-functional attribute evaluation link (UQEL) table; calling service several times and giving evaluation by a user, mapping the user evaluation on service to evaluation on corresponding non-function attribute, adding to the UQEL table of the user to acquire a user preferential table finally; and 2, weight-based dynamic multi-attribute service selection: generating a candidate service set according to user requirement to acquire a user preferential set, calculating the weight of each non-functional attribute to generate a dynamic decision matrix sequence, calculating weight included angle cosine of a user preferential vector and a candidate non-functional attribute vector, the weight of each observation time, and the weight cosine sum of each candidate service in all observation times, and recommending the service with the maximum weight sum to the user. The method is used for realizing adaptive service selection without more participation of users, is convenient to use, and has good service selection adaptability.

The invention relates to a method and a system for predicting a state of charge of a power battery of a pure electric vehicle. The method for predicting the state of charge comprises the following steps of S1, acquiring external characteristic parameters of the power battery; S2, performing data mining on the external characteristic parameters; and S3, establishing a multi-input parameter combination type multiple dynamic decision tree model to obtain a predicted value of the state of charge. According to the method and the system for predicting the state of charge of the battery, the external characteristic parameters are mined by adopting the multiple dynamic decision tree model to obtain effective data, and useless data is removed, so that data redundancy is avoided and the prediction time is shortened; and especially under the condition of considering energy feedback of the battery and continuously changed working condition, the value of the state of charge of the battery still can be predicted accurately in real time, so that the practicality and validity are high.

The invention discloses a layered cooperative control and dynamic decision-making method for large-scale power transmission network frame restoration. The method comprises steps as follows: step one, a power transmission network frame is divided into a main network frame layer and a regional layer which are connected through power receiving points, and the power receiving points have attributes of load and a power supply in the main network frame layer and the regional layer respectively; step two, index values of the power receiving points are determined; step three, a commitment and agreement based restoration cooperative mechanism is established, and commitment values of the power receiving points are updated according to system state change; step four, the restoration optimization of the main network frame layer and the regional layer is taken as a lower-level problem, optimization of the commitment values of the power receiving points is taken as an upper-level problem, a bi-level planning power transmission network frame restoration decision-making model is established and solved, and an integral decision-making method is obtained. The problem about coordination and cooperation of all-level and all-region scheduling in response to layered and divisional multi-process restoration is solved, independent parallel restoration of subprocesses can be realized, the operation safety is guaranteed, and the restoration efficiency is improved.

The invention provides a virtual machine migration decision method and device. The method comprises the following steps: acquiring network traffic statistics information of a physical node and network traffic occupation information of virtual machines in the physical node; judging whether the network traffic statistics information of the physical node satisfies threshold information or not, wherein the threshold information is traffic information of the physical node under normal work; if the network traffic statistics information of the physical node does not satisfy the threshold information, determining difference values between the network traffic occupation information and traffic occupation information of the virtual machines respectively according to preset traffic occupation information of the virtual machines; and migrating the virtual machines according to the difference values. Through the technical scheme, the problems that network congestion occurs and a dynamic decision cannot be made due to virtual machine migration in an existing scheme are solved. Whether the virtual machines need to be migrated or not is judged according to the network traffic statistics information of the physical node and the network traffic occupation information of the virtual machines in the physical node; migration of the virtual machines is decided dynamically; and the human participation degree of system maintenance is lowered.

Method includes executing a dynamic decision-making process that includes (a) receiving environmental data and (b) determining a fused ensemble based on the environmental data and a state parameters of a current state of a machine assembly. The fused ensemble includes communications from a system interface to the operator for the state parameters. The communications inform an operator about the state parameters and includes at least one of a visual signal, an audible signal, or a tactile signal from the system interface. The decision-making process also includes (c) communicating the fused ensemble to the operator through the system interface and (d) repeating (a)-(c) while the machine assembly is in the current state. The fused ensemble is configured to change based on changes in the environmental data.

The invention discloses a dynamic decision-making method and device for ozone pollution prevention and control. According to the method and the device, an ozone pollution prevention and control dynamic decision-making technical route of monitoring and early warning, ozone source analysis, decision-making evaluation and standard reaching and performance is realized. And establishing a measure library according to the emission list, and continuously evaluating and optimizing the measure library through the effect of scene simulation. The local list and the regional list are fused to realize refined and quick source tracing of ozone and precursors thereof; multi-dimensional comprehensive source analysis of models, observations and lists is realized, and key emission areas and key pollution industries are accurately judged; and quick evaluation and dynamic optimization of ozone pollution standard reaching planning are realized. By means of three-dimensional monitoring, emission lists, numerical simulation, emergency emission reduction technologies and the like, ozone pollution sources are subjected to multi-dimensional analysis, source contributions of local areas, surrounding areas and pollution industries are quantitatively analyzed, and key causes of urban ozone pollution are recognized.

A system and method are disclosed for utilizing a Z slope test to select polygons that may be candidates for multiple storage methods. The method may calculate the absolute Z slope from vertex data and compare the calculated value with a specified threshold value. In some embodiments, for polygons that have an absolute Z slope less than the threshold value, parameter values may be rendered for only one sample position of multiple neighboring sample positions. The parameter values rendered for the one sample position may then be stored in multiple memory locations that correspond to the multiple neighboring sample positions. In some embodiments, storing parameter values in multiple memory locations may be achieved in a single write transaction. In some embodiments, utilization of the Z slope test method may be subject to user input and in other embodiments may be a dynamic decision controlled by the graphics system.