4198 results about "Optimization problem" patented technology

A system and a method of maximizing the manufacturing yield of integrated circuit (“IC”) design using IC fabrication process simulation driven layout optimization is described. An IC design layout is automatically modified through formulation of a layout optimization problem utilizing the results of layout fabrication process compliance analysis tools. The modification of layout is performed adaptively and iteratively to make an IC layout less susceptible to yield issues while maintaining design rule correctness and minimal circuit performance impact.

A method and apparatus for end-to-end retail store one-stop site configuration integrates multiple data sources, identifying key customers, forecasting merchandise demand. Site configuration is formulated as a mathematical optimization problem with both in-store and external data as input to the problem whose solution provides proper suggestions for retail store transformation.

Privacy is defined in the context of a guessing game based on the so-called guessing inequality. The privacy of a sanitized record, i.e., guessing anonymity, is defined by the number of guesses an attacker needs to correctly guess an original record used to generate a sanitized record. Using this definition, optimization problems are formulated that optimize a second anonymization parameter (privacy or data distortion) given constraints on a first anonymization parameter (data distortion or privacy, respectively). Optimization is performed across a spectrum of possible values for at least one noise parameter within a noise model. Noise is then generated based on the noise parameter value(s) and applied to the data, which may comprise real and / or categorical data. Prior to anonymization, the data may have identifiers suppressed, whereas outlier data values in the noise perturbed data may be likewise modified to further ensure privacy.

An information retrieval system that deals with the problems of synonymy, polysemy, and retrieval by concept by allowing for a wide margin of uncertainty in the initial choice of keywords in a query. For each input query vector and an information matrix, the disclosed system solves an optimization problem which maximizes the stability of a solution at a given level of misfit. The disclosed system may include a decomposition of the information matrix in terms of orthogonal basis functions. Each basis encodes groups of conceptually related keywords. The bases are arranged in order of decreasing statistical relevance to a query. The disclosed search engine approximates the input query with a weighted sum of the first few bases. Other commercial applications than the disclosed search engine can also be built on the disclosed techniques.

An optimization problem models the dynamic placement of applications on servers under two types of simultaneous resource requirements, those that are dependent on the loads placed on the applications and those that are independent. The demand (load) for applications changes over time and the goal is to satisfy all the demand while changing the solution (assignment of applications to servers) as little as possible.

A beam and power allocation method for a MIMO system transmitting multiple data streams from a transmitter having a plurality of transmit antennas to a receiver having at least two receive antennas, the transmit antennas being grouped based on feedback information from the receiver, includes obtaining covariance matrices for respective transmit antenna group, and allocating beam and power to the transmit antenna groups according to the covariance matrices of the respective antenna groups. The power allocation method can be adapted to various partial beamforming techniques by generalizing the optimization problem as a function of transmit covariance matrices.

This invention relates generally to medical imaging and, in particular, to a method and system for reconstructing a model path through a branched tubular organ. Novel methodologies and systems segment and define accurate endoluminal surfaces in airway trees, including small peripheral bronchi. An automatic algorithm is described that searches the entire lung volume for airway branches and poses airway-tree segmentation as a global graph-theoretic optimization problem. A suite of interactive segmentation tools for cleaning and extending critical areas of the automatically segmented result is disclosed. A model path is reconstructed through the airway tree.

Method for determining one or more optimal well trajectories and a drill center location for hydrocarbon production. A well path and drill center optimization problem (55) is solved in which one constraint is that a well trajectory must intersect a finite size target region (61) in each formation of interest, or in different parts of the same formation. The finite target size provides flexibility for the optimization problem to arrive at a more advantageous solution. Typical well path optimization constraints are also applied, such as anti-collision constraints and surface site constraints (62).

Dynamical methods for obtaining the global optimal solution of general optimization problems having closed form or black box objective functions, including the steps of first finding, in a deterministic manner, one local optimal solution starting from an initial point, and then finding another local optimal solution starting from the previously found one until all the local optimal solutions starting from any initial point are found, and then finding from said points the global optimal solution.

The invention discloses a regional integrated energy system operation robust optimization method considering electricity-to-gas conversion and uncertainty, and the method comprises the steps: carryingout the detailed modeling of an electricity-to-gas conversion process according to the principle of an electrochemical reaction, and analyzing the coupling relation between different energy forms ina matrix mode based on an energy center model; establishing a regional comprehensive energy system operation optimization model considering the uncertainty of various load prediction powers, and establishing a two-stage robust optimization model according to a polyhedral uncertain interval; and decomposing the two-stage robust optimization model into a main problem and a sub-problem, converting the sub-problem into an optimization problem of a single target, and carrying out iterative solution to obtain a comprehensive energy system robust optimization scheme. According to the method, the potential of complementary mutual relief and flexible scheduling among multiple energy forms is fully excavated, wind curtailment can be reduced, and the operation economy and flexibility of the comprehensive energy system are improved; and the contradiction between the operation risk and the cost can be coordinated according to the actual condition of the regional integrated energy system.

The particle swarm optimization method for microgrids formulates a control problem as an optimization problem and PSO is used to search the solution space for optimal parameter settings in each mode. The procedure models optimal design of an LC filter, controller parameters and damping resistance in grid-connected mode. Moreover, the procedure optimizes controller parameters and power sharing coefficients in autonomous mode. The method uses particular nonlinear time-domain-based and eigenvalue-based objective functions to minimize the error in the measured power, and also to enhance the damping characteristics, respectively.

In accordance with the principles of the present invention, a beaconing device transmits a radio signal that can be detected by a plurality of wireless receivers positioned at various known locations. The receivers form nodes of a wireless network that further includes a control node with which the receivers can communicate. Each receiver that receives the signal from the beaconing device records the signal strength at which it receives the signal from the beaconing device and sends that information to the control node. The control node processes the signal strength information received from all of the receivers and uses it to estimate the location of the beaconing device. Particularly, the controller solves an optimization problem for the coordinates of the beaconing device by determining the set of coordinates for the beaconing device that minimizes the squared error over all of the receivers that receive the signal from the beaconing device between (1) the Euclidian distance between the known coordinates of the receiving device and the estimated coordinates of the beaconing device and (2) the estimated distance between the beaconing device and the particular receiver based on signal strength at that receiver.

A control system for a wind turbine comprises: a sensor arrangement for capturing measures related to the turbine operation and fatigue accumulation; an upper level controller, which, on the basis of a statistical treatment of said measures, calculates optimized control settings at discrete points of time; a measurement module which processes said measures into instantaneous values; and a lower level controller that receives said control settings and said instantaneous values and calculates instantaneous optimal commands to control turbine actuators. The lower level controller comprises a continuous-time damage model which calculates the rate at which damage is accumulated at any time, and an optimal controller which controls operational states of the turbine, either by directly giving feedback of the instantaneous values to the actuators, or by generating a turbine performance objective function which is continuously optimized by repeatedly solving a receding horizon optimization problem.

A sensor network routing is formulated as a joint optimization problem taking into account routing cost and information aggregation. Information gain is used explicitly to optimize the routing path. The optimization approach involves a shortest path algorithm in a modified network graph. A method is provided that routes queries from an arbitrary entry point to high activity network sensor regions using inputs from sensor nodes along the path to refine the message. The multiple step look-ahead approach provides deadlock avoidance and routing around sensor network holes. For point-to-point query routing, a method based on real-time A* (RTA*) search is provided to find a path which takes detours efficiently to maximize information aggregation. Future information expected to be gained along the path from an arbitrary node to an exit node may be estimated to allow the selection of a successor sensor node.

Systems and methods of friendly jamming for securing wireless communications at the physical layer are presented. Under the assumption of exact knowledge of the eavesdropping channel, a resource-efficient distributed approach is used to improve the secrecy sum-rate of a multi-link network with one or more eavesdroppers while satisfying an information-rate constraint for all links. A method based on mixed strategic games can offer robust solutions to the distributed secrecy sum-rate maximization. In addition, a block fading broadcast channel with a multi-antenna transmitter, sending two or more independent confidential data streams to two or more respective users in the presence of a passive eavesdropper is considered. Lastly, a per-link strategy is considered and an optimization problem is formulated, which aims at jointly optimizing the power allocation and placement of the friendly jamming devices for a given link under secrecy constraints.

A method and apparatus are proposed for allocating a plurality of human intelligence tasks (HIT) to corresponding human workers. An optimization problem is formulated which incorporates the objectives of reducing the time taken for the HITs to be completed, and of improving the quality of HIT results. The method and apparatus are able to provide solutions to the optimization problem in polynomial time, and to provide theoretical guarantees on the optimality of the solution. The optimization problem is formulated using a measure of a target workload for each worker and a measure of each worker's current situation.

A method and apparatus that allow business users to dynamically add, modify, and delete business rules and associated constraints, and then to apply these changes in a very efficient manner without needing to recompile and / or restart e-business applications, is disclosed. According to one embodiment, hybrid use of the business rules and constraints with multiple decision-support engines provides the practical solution for the described problems. Rules are used to define the generic search space only, without needing to describe all special cases. Then an optimization (not rule-based) engine can automatically create and analyze all possible branches of the tree specified by the rules to select the best one. Because one universal rule engine is not sufficient to handle online decision support, in one embodiment there is a family of intelligent engines (including the rule engine) that can resolve the optimization problem generated automatically based on the applicable dynamic rules.

A natural language processing (“NLP”) manager is provided that manages NLP model training. An unlabeled corpus of multilingual documents is provided that span a plurality of target languages. A multilingual embedding is trained on the corpus of multilingual documents as input training data, the multilingual embedding being generalized across the target languages by modifying the input training data and / or transforming multilingual dictionaries into constraints in an underlying optimization problem. An NLP model is trained on training data for a first language of the target languages, using word embeddings of the trained multilingual embedding as features. The trained NLP model is applied for data from a second of the target languages, the first and second languages being different.

A mechanism for determining a data link path in a managed network between a source device and a destination device is disclosed. To determine the data link path, a mechanism determines the topology of the network. Information on the topology is needed in order to create a Connected Group space based on the topology. By creating a Connected Group space, the problem of determining a data link path is reduced to an optimization problem of finding the shortest path between the source device and destination device in the managed network. The shortest path is then transformed back into the topology space to reveal the data link path network between the source device and the destination device.

Proposed is a method, implemented in software, for estimating fault state of an apparatus outfitted with sensors. At each execution period the method processes sensor data from the apparatus to obtain a set of parity parameters, which are further used for estimating fault state. The estimation method formulates a convex optimization problem for each fault hypothesis and employs a convex solver to compute fault parameter estimates and fault likelihoods for each fault hypothesis. The highest likelihoods and corresponding parameter estimates are transmitted to a display device or an automated decision and control system. The obtained accurate estimate of fault state can be used to improve safety, performance, or maintenance processes for the apparatus.

The invention relates to a wind-power adsorption connected large-power-grid scheduling rolling planning method, comprising the following steps: obtaining ahead planned output data of all conventional units from an ahead power-generation planning system; building an intraday rolling model of a wind-power adsorption connected power grid based on the ahead plan; obtaining a current system load predicted value and a total wind-power output predicted value through intraday rolling expansion short-term prediction and refreshing the output data of residual time intervals of all the conventional units in an online manner according to the system loading predicted value and the total wind-power output predicted value; and updating processing data of a single machine in optimization problems in a unit output plan. The method can well solve the effect of wind-power connection on the operation of the power grid, and the safety and economic property for power grid operation are improved while cleanenergy sources are fully utilized.

The invention discloses a D2D user resource allocation method based on a deep reinforcement learning DDPG algorithm. According to the invention, cellular users and D2D user related information are utilized; an optimal D2D user channel allocation and transmitting power combined optimization strategy is obtained by utilizing a deep reinforcement learning method; D2D users select appropriate transmitting power and distribution channels to reduce interference to cellular users and maximize own information rate, efficient resource distribution is achieved under the condition that QoS of the cellular users is not affected, the throughput of a cellular network is improved, and the requirement for green communication is met. The DDPG algorithm effectively solves the joint optimization problem of D2D user channel distribution and power control; t the method is stable in performance in optimization of a series of continuous action spaces, the time step required for solving the optimal solution is far less than that required by DQN, and compared with a DRL method based on a value function, the deep strategy gradient method based on the AC framework is higher in strategy optimization efficiency and higher in solving speed.

The invention belongs to the field of path planning technology and specifically relates to a three-dimensional multi-UAV coordinated path planning method based on SAS. The method comprises the following steps: carrying out modeling on a path planning environment; initializing multi-target SAS calculation parameters consisting of the length of a minimum path section, a maximum turning angle, a maximum angle of climb / glide, a minimum safe distance of UAVs and a minimum flight altitude of UAVs; initializing the positions of the UAVs, wherein each UAV represents a path; updating the positions of the UAVs; expanding a current node; determining whether a path section collides with other path sections; updating a node table of the path section; executing a step (8) if minimum path cost set in the step (2) is met, and otherwise, executing the step (3); determining a cooperated planned optimal path so as to complete path planning. The method overcomes multi-objective optimization problems, has versatility, provides a reasonable optimal solution for a decision maker and better accords with practical needs.

A microgrid including a renewable power source is optimized by treating the renewable source as operating in an isochronous mode, and by decomposing the optimization process. A renewable capability is defined for the renewable source to enable treatment of the renewable source as operating in an isochronous mode. The renewable capability may be based on a power rating of the renewable source. An objective function of the microgrid optimization problem may then be optimized while treating the renewable source as operating in an isochronous mode. A penalty factor may be applied to avoid power shortage.

Mobile edge computing (MEC) provides the advantages of low delay, low power consumption and high reliability based on a mobile network edge through provision of an IT service environment and cloud computing capacity, so the mobile edge computing becomes a hotspot of future 5G research. The invention discloses a task unloading and resource allocation scheme based on MEC. The scheme comprises the steps of setting an unloading decision and resource allocation joint optimization problem; optimizing an unloading decision through adoption of a coordinate descent method; carrying out subchannel allocation on users when user delay conditions are satisfied through adoption of an improved Hungarian algorithm and greedy algorithm; and converting energy consumption minimization problem into a power minimization problem, and converting the power minimization problem into a convex optimization problem, thereby obtaining the optimum sending powers of the users. According to the scheme, different delay requirements of different users can be satisfied, system total energy consumption can be minimized, and system performance can be effectively improved.