47 results about "Problem space" patented technology

A method of fusing sensor detection probabilities. The fusing of detection probabilities may allow a first force to detect an imminent threat from a second force, with enough time to counter the threat. The detection probabilities may include accuracy probability of one or more sensors and an available time probability of the one or more sensors. The detection probabilities allow a determination of accuracy of intelligence gathered by each of the sensors. Also, the detection probabilities allow a determination of a probable benefit of an additional platform, sensor, or processing method. The detection probabilities allow a system or mission analyst to quickly decompose a problem space and build a detailed analysis of a scenario under different conditions including technology and environmental factors.

A method of deinterleaving parameter descriptor word (PDW) data includes parallel scoring of pulses in an a posteriori search for associating of pulses based on proximity within a multi-parameter problem space. The a posteriori search includes scoring an oldest pulse against all newer pulses, and then scoring a next oldest pulse against all newer pulses. The associating utilizes at least one of a plurality of parallel computation modes, parallel tasks to operate on separate data fields, and multi-threading or multitasking that can implement one of parallel and configuration-overlaid operation, synchronized by events.

A computer implemented method, apparatus, and computer program product for effectively reducing a complicated problem space to enable faster implementation of system management software, and in particular, policy management for security software. The policy management tool of the present invention receives input from a user to configure a policy model, wherein the policy model is configured according to a set of policy requirements. The policy management tool presents a graphical view of a policy model according to the input from the user, wherein the graphical view allows the user to visualize internals of the policy model as a whole. The policy management tool performs validations on the policy model against requirements of the set of policy requirements. A simulation of the policy model may then be performed to determine the validity of the policy model and generate real test results feedback at a time the policy model is configured.

A new paradigm for security analysis is provided by transitioning code analysis reporting from the problem space (the warnings themselves), to a solution space (potential solutions to the identified problems). Thus, instead of reporting raw findings to the user, the automated system as described here outputs proposed solutions to eliminate the defects identified in the security analysis. A consequence of this approach is that the report generated by the analysis tool is much more consumable, and thus much more actionable. Preferably, the report provides the user with one or more candidate location(s) at which to apply a fix to an identified security problem. These locations preferably are identified by processing overlapping nodes to identify one or more solution groupings that represent an API for a sanitization fix. The report also includes one or more recommendations for the fix, and preferably the report is generated on a per-vulnerability type basis.

The invention relates to the enterprise engineering and the information technology field, and discloses an optimization method for the multi-objective enterprise process model parameters, which is based on the genetic algorithm. In the optimization field of the enterprise process model parameters, most optimization methods use the countermeasure weighing principle to combine each sub-goal into a single objective, so as to process an optimization objective, thus, some defects exist in the comprehensive evaluation process. Aiming mainly at various optimal parameters, such as the production rate of the product, the quantities of various resources, the persistent time of each activity and the configuration schemes for the required resources, as well as the scheduling strategies for the selectable resources, the invention comprehensively evaluates a plurality of indexes, such as the running time, the running cost, the final product quality, the utilization rate of the product, the queue length, etc. The invention adopts the method which divides the problem space in a multi-layer way to process the combinatorial constraint relationship among the various optimal parameters, thereby increasing the flexibility of the optimization parameter selection, and avoiding the analysis calculation to the ineffective parameter combination scheme, furthermore facilitating the maintenance of the group diversity.

A system, and method for dynamically creating web applications from data is described. Simple data is transformed into a declarative application data model that is then parsed by a server and compiled into a functional web application. Application functionality is partly determined by rules applied to web application objects in response to user actions. These rules are triggered by various cues, including user actions and relationships among objects in the web applications. A web application is considered an n-dimensional problem space, and relationships among application objects can be modeled using set theory. The status of a particular relationship among objects and user actions can trigger specific application behavior. Additionally application behavior can be triggered in other ways, like conditions in arbitrary scripts or combinations of multiple triggers combined using logical connectives.

The invention discloses an analysis method for the spreading effect of a requirement change, and belongs to the technical field of software development. The analysis method comprises the steps that requirement dependencies are extracted in the software problem analysis process and modeled according to a requirement dependency diagram; the tracing relation among a real world field in a problem space, user requirements and software products in a machine specification-solution space is described through a tracing matrix; software requirement products affected by the requirement change are recognized through horizontal requirement change spreading effect analysis based on the requirement dependency diagram, and software design products and code products affected by the requirement change are recognized through vertical requirement change spreading effect analysis based on the tracing matrix; the software requirement products, the design products and the code products affected by the requirement change are collected to form a soft product set affected by the requirement change. The analysis method has the advantage that the problem that because the spreading effect of the requirement change is not effectively defined, the requirement change workload is difficult to estimate and requirement change management decisions are improper.

The invention discloses a method for predicting and simulating a network public opinion in an emergency based on an SOAR model. The method comprises the steps of based on the SOAR model, taking net citizens as agents, and taking a net citizen group behavior transformation process in the network public opinion as a continuous transformation process of state with time in a public opinion problem space; in combination with network public opinion development and government response related theories, dividing a net citizen group into Me-formers and In-formers, and dividing a network public opinion development phase into generation, bursting, ripening and attenuation; designing working memory, long-term memory, decision-making process and learning mechanisms of the net citizen agent; constructing a net citizen group behavior transformation rule base; and establishing a net citizen group behavior transformation SOAR agent model based on the SOAR model. The attenuation phase in the network public opinion development process is taken as an example, the prediction and simulation for the network public opinion in the emergency are realized, and thus the influence of different government responses on different types of net citizen group behaviors is evaluated by the method.

This invention relates to a method, system and computer program product for selecting an optimised solution in a computerised multiple-constraint problem space, comprising: receiving a linear function for optimization; receiving a set of constraints for the linear function; determining a first optimal solution for the linear function and initial constraints using linear programming solver; creating a new set of constrains using the first optimal solution as a constraint in addition to the initial constraints; creating a new quadratic function by adding a quadratic objective of slack variables to the linear function; and determining a solution to the quadratic function and new constraints using a quadratic programming solver.

The invention discloses a fast convergence ant colony algorithm for satellite network topology generation, comprising the following steps of: establishing a satellite network model; establishing an inter-satellite link; and generating optimization based on the satellite network topology of the improved ant colony algorithm. The ant colony algorithm provided by the invention starts independent solution search at multiple points in the problem space at the same time, which not only increases the reliability of the algorithm, but also makes the algorithm have strong global search capability. Applying the ant colony algorithm to the satellite network can obtain the global optimal topology and enhance the stability of the topology. The invention uses the weight of the inter-satellite link as the pheromone of the ant colony algorithm, taking into account the effects of the inter-satellite link length, the link connection time, and the link capacity on the satellite network topology generation, so that the resulting satellite network topology is more accurate. The invention comprehensively considers three factors affecting the topology generation of the satellite network, and combines thesame to obtain a global optimal solution.

The invention provides an intelligent method for optimizing working procedure of a semiconductor packaging production line, applying particle swarm optimization (PSO) to optimize the working procedure in a semiconductor packaging process, modeling and finding the solution, taking processing center as a unit, building a mapping relation between problem to be solved and particle swarm, using particles to express optional solutions to the problem, and finding the optimized solution under the guidance of corresponding target; each particle swarm optimization subproblem is using processing time of the machine on the production line for different products to encode the particles to determine particle swarm optimization space and making time sequence decoupling on the optimization problem to be solved, obtaining the corresponding subproblem and then dividing the problem space and determining a mapping relation between the divided space and each subproblem to find particle swarm optimization solution of each subproblem, thus obtaining an optimized machine processing time allocating solution and machine occupation ratio. The practice indicates that PSO has the advantages simple concept, convenient implementation, rapid convergence, etc.

The invention provides a method for quickening solving of a mesoscopic scale physical problem by using a graphic processing unit (GPU). The method fully uses characteristics of a many-core processor such as superstrong floating-point calculation capacity and large memory bandwidth owned by the GPU, Hamiltonian matrix initialization calculating work occupying the longest machine hours in mesoscopic scale problem solving is processed by the GPU in assisted mode, traditional matrix diagonalization work is still finished by a central processing unit (CPU) good in serial calculating capacity, and quickening of the mesoscopic scale physical problem solving is achieved. In a calculating process, users use characteristics that Hamiltonian matrix element calculation is independent relatively, simple mapping from a problem space to a GPU thread space is achieved, and therefore usability and high expandability of an algorithm are guaranteed.

The invention relates to a directed graph association rule-based music cloud recommendation algorithm. According to the directed graph association rule-based music cloud recommendation algorithm, data modeling analysis is carried out on music cloud operation data so as to provide technological means and services for the music market analysis and aid decision making of commercial operation departments; by mining the maximum frequent item sets, the mining efficiency can be effectively improved and the scale of a problem solution can be effectively reduced; and the algorithm adopts a depth-first search method, nodes in node sets of directed item set graphs are selected as initial nodes to carry out search, and judgement is carried out on the frequent extension sets of each item set, so that the problem space can be effectively reduced, the number of candidate sets of the to-be-checked maximum frequent item sets can be decreased, and the efficiency of the algorithm can be effectively improved. The efficiency of the algorithm can be further optimized and improved by adjusting the arrangement sequence of the node sets of the directed item set graphs, adjusting the generation sequence of directed edges and designing an effective storage manner for the maximum frequent item sets.

The invention discloses a water quality prediction method combining a divide-and-conquer method and water quality periodicity, and belongs to the technical field of water quality prediction. The water quality prediction method aims to solve the problem that complex change rules of water quality data cannot be sufficiently learnt by a single predictor and accordingly prediction accuracy is poor, a problem decomposition solving frame based on data driving is adopted in the method, the frame can automatically divide problem space according to data characteristics in the learning process, the number of predictors does not need appointing by staff, and better robustness is achieved. Predictor effect evaluation and water quality data periodicity are combined, so that change characteristics of water quality data on the time scale are well utilized, and a more accurate problem decomposition algorithm is obtained. According to frame leaning content, data to be predicted are mapped to a predictor group correspondingly having prediction advantages, a prediction result is obtained through weighting of corresponding predictors, and better accuracy and stability are achieved.

The invention discloses a Q function adaptive learning method based on a multilayer classification network, comprising the following steps: S1, training a multilayer classification network; and S2, using the multilayer classification network for work. Through the establishment of a hierarchical classification network, adaptive partitioning of a problem space is realized. Compared with an unimproved fuzzy adaptive resonance classification network, the partitioning mode is more flexible and can be used to get a better Q value fitting function. The embodiment shows that the method has stronger performance in acquisition of an optimal action strategy.

The present invention uses a Single Instruction Multiple Data (SIMD) architecture to form real time 3D radar images recorded in cylindrical near field scenarios using a wavefront reconstruction approach. A novel interpolation approach is executed in parallel, significantly reducing the reconstruction time without compromising the spatial accuracy and signal to noise ratios of the resulting images. Since each point in the problem space can be processed independently, the proposed technique was implemented using an approach on a General Purpose Graphics Processing Unit (GPGPU) to take advantage of the high performance computing capabilities of this platform.

The invention discloses a method for improving the performance of a differential steering system of tracked vehicle hydraulic machinery, aiming at multiple optimal parameters such as planet row characteristic parameters, hydraulic closed loop system parameters, motor post-transmission ratio, dead axle gear transmission ratio and the like of the differential steering system of hydraulic machinery, multiple evaluation sub-objects such as the steering dynamic property (dynamic factor), the steering flexibility (steering radius), the steering rapidity (steering time) and the like of the tracked vehicle are evaluated comprehensively; the mutual coupling relationships between the optimal parameters are processed by using a layer partitioning problem space method, so that each optimal parameter is enabled to correspond to one layer problem space, thereby the flexibility of optimal parameter selection is increased, the analysis calculation on an ineffective parameter combined scheme during the optimization process is avoided, and the parameter optimization efficiency is improved.

The invention discloses a vector model-based massive spatiotemporal data retrieval method and system. The method comprises the steps of performing vectorization processing on data of event space and problem space to obtain a spatiotemporal data vector; performing dimension reduction processing on the spatiotemporal data vector according to a target condition vector needed to be retrieved; performing vector operation on each dimension of the spatiotemporal data vector subjected to the dimension reduction processing and the target condition vector; and judging vector operation results, screening out the vector operation results meeting a preset condition, and obtaining corresponding retrieval results. The system comprises a spatiotemporal data vector representation module, a spatiotemporal data vector dimension reduction module, a spatiotemporal data vector operation module and a retrieval result judgment module. According to the method and the system, the to-be-queried data volume can be reduced, the calculation complexity is greatly lowered, and the retrieval efficiency is effectively improved. The method and the system can be widely applied to the field of retrieval.

Embodiments of the invention provide a method, system and computer program product for log file reduction according to problem space topology. A method for log file reduction according to problem space topology can include receiving a fault report for a fault in a solution executing in memory of one or more computers of a computer data processing system. The method further can include extracting references to at least two resources of the computer data processing system from the fault report. The method yet further can include filtering a set of all log files for the computer data processing system to only a subset of log files related to the at least two resources. Finally, the method can include displaying the subset of log files in a log file analyzer.

The invention relates to an improved particle swarm-based offshore static target search scheme generation method. The method comprises the steps of establishing a calculation model of an offshore search task success rate; mapping the problem space to an algorithm space, and initializing a population; executing the first stage: performing iterative search in the solution space by utilizing the population through an iterative strategy, and analyzing the form of the solution space; executing a second stage: updating the population iteration strategy according to the solution spatial form, and performing iterative search to obtain a result after the iterative search is updated; and mapping the result after the update iteration search back to the problem space to obtain a search scheme and thetask success rate of the scheme. Historical data obtained by the population in the search process can be effectively utilized, the form of the solution space is analyzed, the search strategy is updated, and finally a high-quality search scheme is generated.

Systems and methods for selecting a neural network for a machine learning problem are disclosed. A method includes accessing an input matrix. The method includes accessing a machine learning problem space associated with a machine learning problem and multiple untrained candidate neural networks for solving the machine learning problem. The method includes computing, for each untrained candidate neural network, at least one expressivity measure capturing an expressivity of the candidate neural network with respect to the machine learning problem. The method includes computing, for each untrained candidate neural network, at least one trainability measure capturing a trainability of the candidate neural network with respect to the machine learning problem. The method includes selecting, based on the at least one expressivity measure and the at least one trainability measure, at least one candidate neural network for solving the machine learning problem.

The present invention provides a non-reductive normalisation based data indexing and search system and method. In one embodiment, a computer-implemented method for indexing raw digital data in a searchable format includes translating raw digital data in a first data format to a second data format using a set of extensible parsers, forming non-reductive normalised data entities from the digital data in the second format using a set of extensible entity builders, indexing each of the non-reductive normalised data entities in one or more indexes using a set of extensible indexers, and searching the one or more indexes containing the non-reductive normalised data entities for digital data based on a search query for the digital data.

A student learning guidance platform that includes a functional module for understanding a problem and formulating solutions for the given problem thus formulating and providing possible paths from the given problem to the solutions; a functional module for monitoring how a student solves the problem when the student processes from a first state to a succeeding state in a problem space; a functional module for figuring out whether there is a gap between the student and a required and finding a reason why; a functional module for providing assistance where necessary and further providing a process for a competent teacher to participate assistance when necessary; and a functional module for building a student model and recommending necessary steps for the student to improve.

The invention relates to a tank-type regenerative incinerator, including a system fan, a reverse blower, a combustion-supporting fan, an airflow reversing valve, a buffer chamber, a regenerator, a combustion chamber, a burner, an electric thermocouple, a high-temperature flue gas valve, a chimney and industrial control system. It overcomes the problem that there is no backflush space in small equipment, resulting in the discharge of untreated waste gas, by setting 12 independent spaces in the regenerator and buffer chamber, which contain a backflush space and an empty space; and by regularly replacing the above spaces, The equipment can also be rested during operation, so as to ensure the repeated operation of the entire equipment, reduce the loss of production stoppage caused by equipment rest and prolong the life of the equipment.