7 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.

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.

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 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 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.