8results about How to "Avoid local optimum problems" patented technology

This invention relates to the field of intelligent battery swapping recommendation technology, and discloses an intelligent battery swapping recommendation method and system based on historical battery data. The method includes: a vehicle central control system identifying the vehicle from a user-triggered battery swapping request signal to obtain parameter information of the current vehicle; querying historical battery matching data corresponding to the parameter information from a cloud database, and calculating the compatibility score between each battery model and the current vehicle; a battery swapping cabinet control system performing multi-objective collaborative recommendation decision-making with the compatibility score and the inventory batteries to obtain the optimal recommended battery identifier; and the battery swapping cabinet opening the corresponding compartment door according to the optimal recommended battery identifier to execute the battery swapping process and generate a battery swapping operation record. This invention improves the accuracy of battery compatibility assessment, can discover performance correlations between different battery models, and thus improves the automation and intelligence level of the entire battery swapping process.

The application relates to a large language model assisted cross-layer optical network routing optimization method. The method comprises the following steps: constructing the architecture of the cross-layer optical network, collecting network physical node composition, link resource parameters and service request characteristics; designing an auxiliary graph model, converting the cross-layer network routing optimization problem into a minimum cost path calculation problem in a virtual topology; building a large language model enabled auxiliary graph model weight optimization framework, and preliminarily generating the edge weight of the auxiliary graph model by the large language model; calculating the minimum cost path based on the initial edge weight of the auxiliary graph, evaluating the network performance index corresponding to the path, inputting the evaluation result into the large language model as feedback data, iteratively adjusting the edge weight until the performance index converges to the optimum; and completing the routing planning and wavelength allocation of all service requests in the auxiliary graph model according to the optimal edge weight. The application combines the large language model and the auxiliary graph model framework, improves the flexibility and multi-objective adaptation capability of the routing optimization, and realizes global optimization.

The application relates to the technical field of clean room air conditioner air outlet design, in particular to a clean room air conditioner air outlet optimization design method based on fluid dynamics; through construction of a multi-physical field coupling simulation model based on a fluid dynamics model, accurate prediction of a temperature field, a flow velocity field and a pollutant concentration field in the clean room is realized; the method takes Reynolds average NS equations and a discrete phase model as cores, combines a Standard k-epsilon turbulent flow model and a wall surface function method, effectively captures complex air flow organization and particle diffusion behavior in the clean room, provides a high-precision data basis for subsequent multi-target optimization, minimizes energy consumption under the premise of guaranteeing air quality, and has important engineering application value; and the technical problem that existing clean room air conditioner air outlet design methods mainly depend on experience and industry standards or focus on optimization of a single parameter and fail to fully consider the action of multiple factors is solved.

This invention relates to a dual-modal flexible temperature-strain sensor and its fabrication method. The sensor achieves efficient detection of temperature and strain signals by combining direct ink writing and screen printing processes. The sensor features a unique design, comprising a rigid substrate and a flexible substrate, housing a thermal resistance temperature sensor and a piezoresistive strain sensor respectively, ensuring effective separation and accurate measurement of temperature and strain signals. The use of flexible materials and a FA-BP neural network algorithm based on an improved firefly algorithm enhances stability and measurement accuracy under varying environments. Furthermore, the sensor can still operate normally at high temperatures, outperforming common flexible thin-film materials on the market. This sensor demonstrates significant application potential in smart wearable devices, health monitoring, and industrial automation, providing a new solution for achieving high-precision and high-stability temperature and strain monitoring.

The invention provides an underwater unmanned platform path planning method based on adaptive step length deviation sampling, and relates to the technical field of path planning. The method comprises the following steps: firstly, constructing two bidirectional sampling trees, and selecting beacon points according to a current underwater unmanned platform path planning state; determining sampling points according to the selection mode of beacon points; after the sampling point is determined, firstly, a point closest to the sampling point is found in a sampling tree, and after the point extends to the sampling point, a new sampling point to be added to the sampling tree is obtained; judging whether the new sampling point is added to the sampling tree or not according to whether an obstacle exists between the new sampling point and a point closest to the original sampling point or not, deleting unnecessary sampling points from the currently constructed sampling tree, and selecting a new beacon point; repeating the above process until K times of sampling are executed to obtain two sampling trees; and finally, determining the shortest path from the starting point to the target point in the two sampling trees as the planned path of the underwater unmanned platform.

This invention belongs to the field of virtual reality technology, specifically relating to an XR task planning and instruction issuance method for brewing automation, comprising the following steps: Step 1: Collecting operator demonstration action sequences and voice process descriptions of the brewing production line in an extended reality environment to obtain a hierarchical task graph consisting of process layers and action layers; Step 2: Marking the execution devices corresponding to each action layer node in the hierarchical task graph as game participants, and the global coordination strategy includes the coordinated movement path scheme and rhythm allocation scheme of all execution devices; Step 3: Constructing a flexible Petri net model of the brewing production line based on the global coordination strategy, replacing the original strategy corresponding to the local subnet in the flexible Petri net model with the local replanning scheme, and continuing to issue instructions. This invention achieves formalized automatic mapping from process semantics to equipment actions, improving the programming efficiency, coordination quality, and anomaly response capability of the brewing production line.

The invention provides a method, device and equipment for determining a thickening CO2 flooding development scheme, a medium and a product, and relates to the technical field of oil and gas development. The method comprises the steps of obtaining a plurality of initial development schemes of a target oil reservoir, wherein the initial development schemes are obtained by permutation and combination of a plurality of preset values corresponding to a plurality of development characteristic parameters; inputting each initial development scheme into a pre-trained development dynamic prediction learning model to obtain development dynamic data corresponding to each initial development scheme; adopting a preset multi-target mathematical model to calculate a plurality of index values corresponding to each initial development scheme; determining a candidate development scheme set by adopting a multi-objective collaborative optimization algorithm according to the plurality of index values corresponding to each initial development scheme; and determining a thickening CO2 flooding target development scheme of the target oil reservoir based on the preset weight threshold values corresponding to the indexes. According to the method, through fusion of the preset multi-target mathematical model and the multi-target collaborative optimization algorithm, the optimization efficiency and precision of the thickening CO2 flooding development scheme are remarkably improved.

This invention discloses an optimization method for a natural gas pressure energy system based on a multi-objective frost algorithm, relating to the field of energy utilization technology. The specific steps are as follows: A comprehensive optimization model is established for the natural gas pressure energy system from three aspects: system efficiency, economic benefits, and environmental benefits. Then, algorithm parameters are initialized and the population is uniformly initialized. Next, a neighborhood structure is constructed by calculating Euclidean distance, and the fitness of each individual is calculated using a weighted sum decomposition method. The quality of local solutions is optimized by combining a frost neighborhood perturbation mechanism. In the stage of generating new individuals, simulated binary crossover and polynomial mutation operators are used, and a hard frost puncture mechanism is introduced to avoid local optima. Subsequently, the population and solution set are updated, retaining non-dominated solutions and maintaining the convergence and diversity of the solution set. Finally, the optimal result is selected by comprehensively evaluating the optimized solution set using the analytic hierarchy process (AHP)-fuzzy decision method. This invention can optimize and improve the performance of a natural gas pressure energy system.