3 results about "Curve smoothing" patented technology

This invention discloses a Marchenko multiple suppression method for tracking wave impedance interfaces, belonging to the field of seismic data processing technology. The method includes the following steps: S1, obtaining wave impedance inversion results across the entire depth domain based on surface observation seismic data and the background velocity field; S2, extracting the location information of strong wave impedance interfaces and identifying several key locations between these interfaces; S3, using a Bezier curve smoothing method to obtain the spatial location of the focal point that maximizes the penetration of the strong wave impedance interface; S4, determining the ascending and descending Green's functions for the spatial location of the focal point; S5, predicting interlayer multiples using seismic interferometry; and S6, obtaining the seismic shot gather for suppressing interlayer multiples through adaptive matched filtering. This invention does not require a precise velocity model, relying only on a macroscopic velocity model, and can obtain deep-domain strong wave impedance geological information, accurately predicting and suppressing interlayer multiples by combining wave impedance information.

The application discloses a method for solving the multi-objective optimization problem, comprising the following steps: S1), designing a target function, constructing a weighted single-target function to realize collaborative optimization; S2), an initialization stage: adopting refraction reverse learning and an elite selection strategy; S3), a rolling ball stage: fusing a Pareto guide and an Osprey search thought; S4), a breeding dung beetle stage: introducing an adaptive t-distribution disturbance mechanism; S5), a foraging dung beetle stage; S6), a stealing dung beetle stage: fusing a multi-objective collaborative sharing mechanism of the Pareto guide; S7), merging offspring and parent populations and updating an external solution set; and S8), after iteration termination, outputting an optimal track. The application has excellent performance in path search and obstacle avoidance ability under complex terrain, and introduces an adaptive t-distribution disturbance and a Jacobian curve smoothing mechanism, which significantly enhances global jumping and local fine search, and guarantees the smoothness of the planned track and the multi-objective convergence quality.

This invention discloses a path planning method for UAV swarms in complex environments based on an improved GBNN algorithm. It constructs a 3D grid map of the complex environment by quantifying environmental complex factors such as restricted areas and performance degradation areas. Combining the flight characteristics of UAV swarms, it sets individual UAV constraints and collision avoidance constraints within the swarm, establishing a multi-objective optimization function with total path length, risk, and safety as its core. Based on the improved GBNN algorithm, it filters candidate neighborhood subsets and performs multi-step linear prediction. The optimal path is selected through path intersection detection and length-turning cost filtering. After cubic B-spline curve smoothing, the optimal flight path that satisfies the constraints is output. This invention can effectively reduce the path risk of UAV swarms in complex environments, improve path safety and real-time planning, while simultaneously considering path length optimization and collision avoidance capabilities, thereby improving the efficiency of swarm task execution.