14 results about "Computer optimization" patented technology

The invention discloses an image segmentation optimization method, system, equipment and medium, and relates to the technical field of computer optimization algorithms, and the method comprises the steps: constructing a two-dimensional histogram for an original gray level image, employing a two-dimensional Renyi entropy as a target function for evaluating the segmentation quality of the two-dimensional histogram, finding a group of optimal threshold combinations, and carrying out the segmentation of the two-dimensional histogram through the optimal threshold combinations; the problem of searching the optimal threshold value combination is converted into an optimization problem to be solved, the found optimal threshold value combination is used for segmenting the original image, and a final segmentation result image is generated; when an optimization problem is solved, operating individuals in the population by adopting a differential variation strategy so as to generate a first group of candidate solutions, and executing a Rime optimization mechanism and a randomized step size covariance matrix adaptive mechanism in parallel on each individual in the population so as to generate a second group of candidate solutions; and updating the population according to a greedy selection mechanism. The algorithm premature convergence can be effectively prevented, and the method can be applied to complex optimization tasks such as image segmentation and engineering design.

The present invention discloses a device and method for compensating radial runout components of a magnetically suspended rotor position. These devices relate to the technical field of high-speed magnetically suspended motors and include a hardware-in-the-loop (HIL) simulation system. The HIL simulation system comprises a high-speed magnetically suspended motor and its control system, which together constitute the physical "hardware" system of the HIL simulation system. Furthermore, the HIL system comprises a dynamic mathematical model of the high-speed magnetically suspended motor and its control system, which forms a simulation system within a computer digital space. The high-speed magnetically suspended motor comprises a magnetically suspended rotor assembly, radial / axial electromagnetic bearings, radial / axial displacement sensors for the rotor assembly, a three-phase motor stator, and an angular displacement sensor for the magnetically suspended rotor assembly. The present invention utilizes HIL simulation and artificial intelligence computer optimization to determine the Fourier coefficient parameters of each harmonic of the radial runout component in a virtual digital space. The obtained Fourier coefficient parameters are then used in the actual system to reversely reconstruct the radial runout to offset the adverse effects of the actual radial runout component.

A computer-implemented method (100) for optimizing a given topology (2) of a modular plant (1) that is to perform a given industrial process according to a given engineering recipe (3), the method (100) comprising: • for at least one process module (21-23) in the given topology (2), obtaining (110) an amount of at least one resource and / or performance (21a-23a) of the process module (21-23) that is utilized when the process is performed according to the recipe (3), and dividing the amount by a maximum amount of the respective resource and / or performance (21a-23a) that the process module (21-23) is capable of providing, thereby obtaining a theoretical utilization (21b-23b) of the resource and / or performance (21a-23a) as a theoretical utilization of the process module (21-23); • searching (120) in a pool (6) of available process modules (24-27) for candidate process modules (24-27) that are capable of replacing at least one process module (21-23) in the execution of the given recipe (3) and that fit the given topology (2); • for each candidate process module (24-27), obtaining (130) a theoretical utilization (24b-27b) of a corresponding resource and / or performance (24a-27a) of the candidate process module (24-27) that would ensue if the at least one process module (21-23) were to be replaced by the candidate process module (24-27), and assigning the theoretical utilization (24b-27b) to the candidate process module (24-27); and • generating an optimized topology (2) of the plant (1) from the given topology (2) by replacing at least one process module (21-23) by a candidate process module (24-27) that has the same or a higher theoretical utilization (24b-27b) than the at least one process module (21-23) * ).

1. Name of the designed product: computer-optimized graphical user interface for electronic device. 2. Use of the designed product: for an electronic device. 3. Design points of the designed product: in the graphical user interface. 4. Picture or photo that best shows the design points: front view. 5. Other views are conventional designs, and other views are omitted. 6. Use of the graphical user interface: the interface is used for computer optimization. The front view is the initial interface. Interface change state diagram 1 is the interface presented after clicking "optimize now" in the front view. Interface change state diagram 2 is the interface presented after optimization is complete in interface change state diagram 1.

A method of computer operation may include (a) providing a first computer and a second computer; (b) operating the second computer; (c) modifying settings of the second computer; (d) monitoring, via the first computer, changes to a plurality of operational parameters of the second computer after the settings are modified to identify a plurality of covariant parameters of the plurality of operational parameters; and / or (e) controlling, via the first computer, operation of the second computers according to the identified plurality of covariant parameters to increase computational efficiency of the second computer.

This invention provides a coal blending optimization method for segmented planned load and switching mill vector coupling, relating to the field of power plant energy conservation and environmental protection technology. The method first determines the objective function of the coupled blending optimization model between segmented planned load and switching mill vector based on optimal coal blending cost, and introduces constraints. Then, the established coupled blending optimization model is transformed into a standard form and a canonical form. For the canonical form, a two-stage simplex method is used to obtain the coal blending scheme. Finally, an inversion method is used to calculate the upper bound of the sulfur constraint, and an improved stochastic configuration network is established based on a historical blending case database to perform feedforward compensation on the sulfur constraint boundary. The historical blending case database is updated based on each real-time coal blending data. This method establishes the coupling relationship between segmented planned load and the blending optimization model through the switching mill vector of the coal mill unit, realizing digital blending primarily based on a computer optimization model.

The invention discloses a GPU (graphics processing unit) parallel computing optimization system for high-performance computing, which relates to the technical field of computer optimization and comprises a memory partition unit, an efficiency analysis unit, a task partitioning unit, a frequency analysis unit and a dynamic storage unit. The dynamic storage unit is used for obtaining priority storage indexes of the data blocks by obtaining the values and the sizes of the data blocks in the high-frequency database and combining the application frequency indexes, sorting the priority storage indexes, and respectively storing the data blocks into a high-speed calling area, a low-speed calling area and a host memory according to a sorting result; according to the method, a dynamic storage unit is used for generating priority storage indexes through multi-dimensional calculation of value, size and application frequency indexes, the priority storage indexes are sorted, high-value and high-frequency data are preferentially stored in a high-speed calling area, after the high-speed calling area is full, the high-speed calling area is sequentially stored in a low-speed calling area and a host memory, and in the GPU parallel computing process, the high-speed calling area and the low-speed calling area are subjected to multi-dimensional calculation; and the data calling is more efficient.

The invention discloses a CCUS source-sink matching network optimization method considering uncertainty, and belongs to the field of energy system planning and computer optimization algorithms. According to the invention, a discrete-continuous complete decoupling double-layer optimization architecture is constructed. According to the method, the objective function of the upper-layer simulated annealing module is innovatively reconstructed, so that solving of the optimal static cost of the source-sink network is converted into solving of the optimal dynamic stability; meanwhile, an intermediate uncertainty module is introduced, optimization is executed based on an information gap decision theory (IGDT), and a robustness boundary and an opportunity threshold of the system are directly quantified by constructing an extreme parameter set; and finally, establishing a feature feedback mechanism based on adaptive weight, and dynamically guiding the algorithm to efficiently converge by using the key topological features of the high-quality scheme. According to the method, curse of dimensionality of large-scale planning is effectively avoided, and adaptive dynamic risk decision support is provided for transformation of a CCUS project from a starting period to a mature period.

A computer-implemented method (100) for optimizing a given topology (2) of a modular plant (1) that is to execute a given industrial process according to a given engineered recipe (3), the method (100) comprising: • obtaining (110), for at least one process module (21-23) in the given topology (2), the amount of at least one resource and / or capability (21a-23a) of the process module (21-23) that is utilized when the process is executed according to the recipe (3), and dividing this amount by the maximum amount of the respective resource and / or capability (21a-23a) that this process module (21-23) is able to provide, thereby obtaining a theoretical utilization (21b-23b) of the resource and / or capability (21a-23a) as the theoretical utilization of the process module (21-23); • searching (120), in a pool (6) of available process modules (24-27), for candidate process modules (24-27) that are able to take the place of the at least one process module (21-23) in the execution of the given recipe (3) and fit into the given topology (2); • obtaining (130), for each candidate process module (24-27), the theoretical utilization (24b-27b) of the corresponding resource and / or capability (24a- 27a) of this candidate process module (24-27) that would ensue if the at least one process module (21-23) were to be replaced by this candidate process module (24-27), and assigning this theoretical utilization (24b-27b) to this candidate process module (24-27); and • generating (140) an optimized topology (2*) of the plant (1) from the given topology (2) by replacing the at least one process module (21-23) with a candidate process module (24-27) that has a same or a higher theoretical utilization (24b-27b) than the at least one process module (21-23).

The invention relates to an optimised mass storage device (100) for a computer with limited resources. It comprises a housing (110) with a connector (120), a non-volatile memory (130), a dedicated complete operating system and an integrated co-processor (140). A high-speed communication protocol allows the co-processor (140) to handle intensive tasks, reducing the load on the host processor. An AI module (150) supervises use of resources and predicts the optimal task distribution, allowing the co-processor (140) to adjust the communication protocol dynamically. The mass storage device (100) thus continuously adapts to the profile of its use, so as to provide a high level of performance despite the limitations of the host computer.

The application discloses a kind of high-precision dynamic balance correction device and method of magnetic suspension rotor, and the application relates to the technical field of high-speed magnetic suspension motor, including hardware-in-the-loop simulation system.The hardware-in-the-loop simulation system includes high-speed magnetic suspension motor and its magnetic suspension motor controller constitute the physically existing hardware system of the hardware-in-the-loop simulation system, further including magnetic suspension motor dynamic mathematical model, magnetic suspension control system and dynamic unbalance parameter computer optimization algorithm constitute the simulation system existing in computer digital space in the hardware-in-the-loop system;With the mechanical, electromagnetic and control system structure of high-speed magnetic suspension motor itself, the equivalent dynamic unbalance parameter of magnetic suspension motor rotor assembly is determined by signal acquisition, system simulation and computer artificial intelligence parameter optimization method to realize the dynamic balance correction of rotor assembly, improve the efficiency of turbine compressor, and simultaneously reduce the effect of production cost.

The invention provides a BDS double-antenna / INS combined attitude determination method based on a factor graph. The device is provided with a high-precision receiving antenna, a Beidou receiver positioning and orientation module, an IMU inertial navigation module and an upper computer optimization system. In a complex environment, satellite signals can be shielded to generate a multi-path effect, so that the traditional combined positioning attitude measurement precision is insufficient, and therefore, a rotation difference value between a measured course angle observation value and a predicted value is used as a constraint increment, and a course angle is introduced as a strong constraint factor to perform motion constraint on a vehicle-mounted system; and updating and iterating the state estimation value through a graph optimization method to obtain an optimal estimation value. The graph optimization model adopts a Shule complement sliding window graph optimization model method, and specifically, epoch constraint information sliding out of a window is superposed to form a priori factor to ensure that information of historical state nodes is not lost. The constraint factor in the window is converted into a nonlinear least square problem, and the initial observation value is iteratively solved until the convergence condition is reached, so that the optimal position and attitude estimation value of the carrier can be output. According to the method, the multi-path effect of GNSS signals in complex environments such as urban canyons and shades is effectively solved, and a reliable solution is provided for realizing continuous and stable attitude determination.

The invention provides a coal blending combustion optimization method for segmented planned load and switching mill vector coupling, and relates to the technical field of power plant energy conservation and environmental protection. The method comprises the following steps: firstly, determining an objective function of a coupling distribution combustion optimization model between a segmented plan load and a switching mill vector according to the optimal coal blending cost, and introducing a constraint condition; converting the established coupling combustion optimization model into a standard type and a model type; aiming at the model, adopting two-stage simplex solution to obtain a coal blending scheme; and finally, calculating a sulfur constraint upper bound by adopting an inversion method, and establishing an improved random configuration network to carry out feed-forward compensation on the sulfur constraint bound based on a historical burning case database. And based on the real-time coal blending data each time, updating the historical blending combustion case database. According to the method, the coupling relation between the segmented planned load and the distribution combustion optimization model is established through the switching mill vector of the coal mill unit, and digital distribution combustion based on the computer optimization model is achieved.

The invention relates to a mass storage device (100) optimized for resource-constrained computers. It comprises a housing (110) with a connector (120), non-volatile memory (130), a dedicated operating system, and an integrated coprocessor (140). A high-speed communication protocol allows the coprocessor (140) to handle heavy tasks, reducing the load on the host processor. An AI module (150) monitors resource utilization and predicts the optimal task allocation, enabling the coprocessor (140) to dynamically adjust the communication protocol. The mass storage device (100) thus continuously adapts to the usage profile to provide a high level of performance despite the limitations of the host computer. Figure to be published with the abstract: Figure 1