4results about How to "Solution feasibility" patented technology

The application provides a paper folding design method and system based on a diffusion model and a physical information neural network, and belongs to the technical field of paper folding structures, and comprises the following steps: obtaining point cloud data of a target three-dimensional paper folding shape and corresponding text description information; generating a two-dimensional crease pattern by using a graph diffusion model according to the point cloud data and the text description information, and ensuring that the crease pattern conforms to a specified three-dimensional shape by using conditional coding; and optimizing the two-dimensional crease pattern by using a physical information neural network to obtain a final two-dimensional paper folding diagram. By combining the diffusion model and the physical constraint neural network, high-precision modeling of the crease pattern is realized, it is ensured that the generated pattern can be folded in geometry and physics, and therefore the design efficiency and accuracy are improved.

The invention discloses a monorail crane shape design optimization method and system based on generative artificial intelligence, and relates to the field of intelligent human aided design. The problems that in an existing monorail crane appearance design, concept creativity and engineering feasibility are disjointed, the design period is long, and the iteration cost is high are solved. The method comprises the following steps: constructing a monorail crane multi-dimensional semantic association network; generating a conceptual design drawing based on a coal mine knowledge pre-trained vertical large language model and the semantic network; performing multi-dimensional comparison on the concept design drawing, the user demand text and the existing product image, wherein the multi-dimensional comparison comprises semantic consistency comparison and engineering feasibility comparison; based on a comparison result, iteratively optimizing parameters for driving image generation by adopting a particle swarm algorithm until the concept design drawing meets a comprehensive evaluation index; and finally, outputting an optimization scheme through the subjective and objective evaluation modules. The method is also suitable for the application fields of common environment mine monorail crane appearances, extreme environment mine monorail crane appearances and the like.

The application provides a kind of embedded decorative ceramic tile curtain wall plate construction method, first install main column and main beam, then install ceramic tile keel, form curtain wall skeleton structure, then install indoor aluminum plate, outdoor aluminum plate, fill thermal insulation rock wool, then install string hanging rod on curtain wall skeleton, realize multilayer ceramic tile string hanging assembly with connecting rod and threaded connecting rod.The application solves the feasibility and operability of ceramic tile curtain wall embedded construction, so that the ceramic tile curtain wall can interact with adjacent surrounding other material form curtain wall, and coordinate a variety of facade effects, and the embedded installation method of the application avoids the problem of hollowing and cracking of the facade ceramic tile decoration, and is convenient and fast to install, with short construction period.

The invention provides an aircraft, cable and boat consistency cross-domain cooperative control method and system based on model prediction, and relates to the technical field of cross-domain unmanned system cooperative control, and the method comprises the steps: constructing an unmanned aerial vehicle-water supply cable-unmanned boat cross-domain cooperative prediction model; acquiring system operation state information; generating dynamic compensation information through a neural network to correct the prediction model; constructing a consistency error state; building a model prediction control optimization problem based on the corrected model and the error state, and solving the problem to obtain an optimal control instruction; and outputting an instruction to an execution mechanism to realize collaborative movement. According to the method, the neural network is introduced to carry out online compensation on uncertain items of the model, and rolling optimization is carried out under a multi-constraint condition by utilizing model prediction control, so that the technical problems of low cooperative consistency control precision and insufficient robustness of a cross-domain heterogeneous platform in a complex environment are solved; and the cooperative control precision and the operation safety of the cable boat system are obviously improved.