Proposed algorithm

对于提出的算法，我们可以从引用中得到一些信息。该引用提到了一个名为“Path Recorder Directed Acyclic Graph (PRDAG)”模型和一个名为“Path Recorder Algorithm (PRA)”的新颖算法。这些算法被提出来高效处理大规模的最长公共子序列（MLCS）问题。然而，引用没有提供更多关于这些算法的详细信息。

此外，从引用中可以了解到，该论文提出了一个用于去雾的简单、快速、强大的算法。该算法通过饱和度推导了介质透射率，而饱和度则使用了一种简单的拉伸方法进行估计。这种方法不假设透射率在小区域内是恒定的，因此可以为每个像素估计不同的介质透射率。此外，该论文还提出了一种去除颜色偏差的算法，该算法使用了白平衡技术，对于具有细小或黄尘的图像特别有用。该算法无需训练、先验知识或精化过程，并且在计算复杂性和去雾效果方面优于现有的去雾方法。

总结起来，提出的算法可能涉及到“Path Recorder Directed Acyclic Graph (PRDAG)”模型和“Path Recorder Algorithm (PRA)”以及一种用于去雾的简单、快速、强大的算法。然而，由于缺乏具体细节，我们无法提供更多关于这些算法的信息。

相关问题

Abstract—In heterogeneous networks (HetNets), user association approaches should be able to achieve load balancing among base stations (BSs). This paper investigates the joint optimization of user association and resource allocation in Backhaul-constrained HetNets for capacity enhancements. We consider two major limitations in HetNets: the backhaul bottleneck of BSs and the capability of user equipment (UE). We establish a framework based on a multi-leader multi-follower Stackelberg game, in which resource allocation is formulated as a follower-level game and user association is cast as a leader-level game. Because of the backhaul bottleneck of small BSs, the given preference order of users renders the final association result unstable. Thus, the resident-oriented GaleShapley (GS) algorithm is included in the proposed framework to obtain a stable single-BS association. Furthermore, congestion factors are introduced to reflect the relative backhaul congestion degrees of BSs, which enables load balancing among the small BSs in the proposed algorithm. The study considers user association and resource allocation with and without limitations on the number of serving users for small BSs in HetNets. Extensive simulation results suggest that the proposed algorithm can adaptively respond to a wide variety of network situations.中文

在异构网络（HetNets）中，用户关联方法应该能够实现基站（BS）之间的负载平衡。本文研究了在受限于回程链路的HetNets中，用户关联和资源分配的联合优化问题，以增强系统容量。我们考虑了HetNets中的两个主要限制：BS的回程瓶颈和用户设备（UE）的能力。我们建立了一个基于多领导者-多追随者Stackelberg博弈的框架，其中资源分配被形式化为追随者级别的博弈，用户关联被视为领导者级别的博弈。由于小型BS的回程瓶颈，给定的用户优先顺序导致最终关联结果不稳定。因此，该提出的框架中包括了面向居民的Gale-Shapley（GS）算法，以获得稳定的单BS关联。此外，引入了拥塞因子来反映BS的相对回程拥塞程度，从而实现了提出算法中小型BS之间的负载平衡。本研究考虑了HetNets中限制小型BS服务用户数量和不限制的用户关联和资源分配。广泛的仿真结果表明，该提出的算法能够适应各种网络情况。

In the proposed algorithm, the access prices of BSs are adjusted according to incomes and load situations in the leaderlevel game, and each UE independently chooses the BS that maximizes its payoff (or minimizes its payment) in the follower-level game. Thus, the algorithm achieves optimization in a distributed manner. When a small BS is overloaded, the price will increase to ensure that the offloaded UE has a higher access payment. For the design of the price, a particle swarm optimization-based pricing strategy (PSO-PS) is proposed to maximize the BS revenue. Finally, we use the resident-oriented Gale-Shapley (GS) algorithm to obtain a stable single-BS association. The main contributions of this paper can be summarized as follows:翻译

在所提出的算法中，基站的接入价格根据领导者层次博弈中的收入和负载情况进行调整，而每个UE在追随者层次博弈中独立选择使其效益最大化（或支付最小化）的基站。因此，该算法以分布式的方式实现了优化。当小型基站超载时，价格将增加，以确保离载的UE具有更高的接入支付。在价格设计方面，提出了一种基于粒子群优化（PSO-PS）的定价策略，以最大化基站的收入。最后，我们使用面向居民的Gale-Shapley（GS）算法来获得稳定的单基站关联。本文的主要贡献可以总结如下：