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在分类规则学习的领域中,许多问题都可以看作是优化问题,它们既可以用经典的分类规则算法进行求解,也可以用蚁群算法中的蚂蚁矿工算法来解决.利用蚁群算法中的自适应,并行分布式处理等特性可在整个分类规则学习中寻找到最优解,通过对一个分类规则问题实例的计算,表明该方法也是解决此类问题的一种有效途径. 相似文献
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文中对多传感器航迹融合技术的基本原理和信息流程等进行了介绍,并对航迹融合技术在指挥自动化系统中的应用做了进一步分析与说明。根据多传感器航迹融合后的锯齿状特点,提出了通过滤波技术进行航迹处理的方法,实现了融合后航迹的平滑。多传感器航迹融合技术为指挥自动化系统中的指挥决策提供了丰富的情报信息,提高了决策效率。 相似文献
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提出一种密集杂波环境下雷达目标航迹起始方法,将高阶相关航迹起始方法与贝叶斯规则相结合,给出联合航迹起始规则,在保证航迹起始率的前提下,有效地降低了杂波环境中的虚假航迹起始概率.蒙特卡罗仿真实验表明,该方法在保留了高阶相关法较高的真实航迹起始概率的优点,同时显著地降低了虚假航迹起始概率,证明了该方法的有效性及优越性. 相似文献
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利用雷达测量中的目标速度、加速度等属性信息, 基于跳转马尔科夫系统模型高斯混合概率假设密度滤波算法, 提出了一种多目标联合检测、跟踪与分类方法.该方法在进行雷达多目标测量信息处理的多模型混合高斯概率假设密度滤波过程中, 对各高斯项编号, 进行航迹提取, 在滤波处理的同时形成带有航迹编号的明确航迹, 并进行航迹管理; 同时, 根据目标运动模型, 联合利用目标加速度控制输入与速度估计进行多目标分类.仿真试验验证了该方法能够在检测、跟踪的同时, 对目标航迹进行有效类型识别. 相似文献
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作为多目标航迹处理中的首要问题,航迹起始的好与坏直接影响着后续航迹的处理.现有的航迹起始算法主要分为顺序处理技术和批处理两大类,包括直观法、逻辑法、Hough变换法、修正的Hough变换法等.本文对几种航迹起始算法的性能进行了仿真分析,并在此基础上研究了一种基于逻辑法的航迹起始算法,工程应用表明这是一种适用于多频连续波体制雷达的航迹起始算法. 相似文献
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Wireless Sensor Network (WSN) is an emerging lower cost and resourceful solution, which enables controlled observation of the environment. The high amount of energy is required in wireless networks during the transmission of data. Here, Golden Ant Lion Whale Optimization (GALWO) and Golden Taylor Sea Lion Optimization (GTSLnO) techniques are presented for cluster head (CH) selection and prediction of neighbor nodes' age. The six stages performed in this work are setup, steady-state, prediction, power transfer, communication or route discovery, and route maintenance stages. In the setup level, CH selection is carried out by GALWO, which is the combination of Ant Lion Whale Optimization (ALWO) with Golden Search Optimization (GSO). Moreover, ALWO is an integration of Ant Lion Optimizer (ALO) with the Whale Optimization Algorithm (WOA). In the steady state, the distance, energy, delay, throughput, and trust update are considered as objective functions. In the prediction stage, the Deep Convolutional Neural Network (Deep CNN) is utilized for age prediction of neighbor nodes, wherein Deep CNN is tuned by employing GTSLnO. The GTSLnO is an incorporation of GSO and Taylor series with Sea Lion Optimization (SLnO). Then, the power transfer stage is done utilizing simultaneous wireless information and power transmission (SWIPT). Thereafter, the communication/route discovery stage is conducted for path selection through neighbor node, and lastly, the route maintenance stage is carried out. The GTSLnO–Deep CNN achieved a minimal delay of 0.089 s, maximal residual energy, throughput, and trust of 0.500 J, 98,843 kbps, and 0.452 for DoS attack. 相似文献
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蚁群优化是一种模拟蚂蚁觅食的群集智能搜索算法,基本蚁群算法收敛性较差,易陷入局部最优解。本文在基本蚁群算法的基础上,提出一种新的蚁群优化算法,通过在信息素局部更新中引入信息素扩散模型,在信息素全局更新中引入随机扰动机制,发挥蚂蚁之间的协同合作能力,提高了算法的收敛速度。以TSP为例的仿真实验表明,该算法具有较强的寻优能力、较好的鲁棒性和有效性。 相似文献
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本文提出了一种自动提取模糊規则集的新方法。本方法首先利用CCM分析闭环模糊系统在某一规则集控制下的全局动态行为,根据控制目标对该规则集进行评价得其性能指标。然后利用GA根据这个性能指标对规则集进行逐代更新和优化,最后得到一个满足要求的规则集。本文以复杂非线性系统倒摆系统为例,介绍用本文的方法提取模糊规则的具体过程,仿真结果表明了本方法的有效性和通用性。 相似文献
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从稳定匹配的角度研究多属性双边匹配问题,介绍多属性双边稳定匹配问题的概念和定义,给出多属性匹配度的定义和排序方法,建立了针对稳定匹配结果的评价函数和评价规则,在此基础上提出了蚁群算法求解此问题的思路及适合此类问题求解的蚂蚁状态转移策略和信息素更新策略,同时给出算法步骤。仿真结果表明,改进的蚁群算法能够有效求解传统稳定匹配问题以及多属性双边稳定匹配问题。 相似文献
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Palaniappan Rajarajeswari Chandrasekaran Shyamala Shivashankar Mohana 《International Journal of Communication Systems》2023,36(6):e5444
Wireless sensor networks (WSNs) plays an indispensable role in the human life by supporting a diversified number of applications that includes military, environment monitoring, manufacturing, education, agriculture, etc. However, the sensor node batteries cannot be replaced under its deployment in an unattended or remote area due to their wireless existence. Cluster-based routing is significant in handling the issue of energy stability and network lifetime. The meta-heuristic algorithms-based cluster head (CH) selection is determined to be highly promising for attaining the objective of CH selection that results in acquiring an optimal network performance. In this paper, a Hybrid Grasshopper and Improved Cat Swarm Optimization Algorithm (HGICSOA)-based clustering scheme is proposed for attaining potential CH selection and guarantee significant sink mobility-based data transmission. The capability of GHOA that controls the rate of exploitation and exploration degree is utilized for CH selection. It specifically adopted OBL-based GHOA for optimal CH selection based on the objective function, which is formulated using node density, residual energy, and distance between sensor node and sink. It incorporated new CSOA for mobility-based data transmission for increasing population diversity. It also utilized the benefits of ICSOA with a predominant local search strategy for achieving better sink mobility-based data transmission. Simulation and statistical results confirmed that the proposed HGICSOA is better in attaining maximum energy stability by 17.21% and improved network lifetime by 23.82%, compared to the benchmarked schemes used for investigation. Moreover, the prevention rate of worst sensor nodes selected as CH is improved by 21.38%, better than baseline approaches. 相似文献
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针对正则化正交匹配追踪(ROMP)算法在压缩感知(C S)重构中需预估稀疏度导致重构精度不稳定的问题,提出一种改进的 ROMP算法。由于观测信号能够继承原始信号特征,在选择候选集原子过程中引入自适应弱 选择标准,依 据观测信号的信息量设定弱选择标准,实现稀疏度自适应调整。将改进ROMA的算法应用于CS 框架下的医学图 像融合,并提出一种结合观测信号结构相似度的融合规则,当待融合的观测信号之间结构相 似度较高时, 说明待融合的原始信号之间同样具有相似性,以两者信息量的加权作为融合规则。同理,当 待融合的观测 信号结构相似度较低时,选择信息量较大的观测信号作为融合后的观测信号。实验结果表明 ,改进ROMP 算法的重构图像质量优于OMP、ROMP、SAMP等算法,其峰值信噪比(PSNR )提高了2~3dB。应用于医学图像 融合时,得到融合图像具有较好的人类视觉特效,保留了源图像中大部分特征信息,可在较 短时间内得到优质的融合结果。 相似文献
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Gu Linyue Zhang Liming 《电子科学学刊(英文版)》1996,13(4):296-302
A method of automatically extracting and optimizing fuzzy rule base is presented in this paper. Firstly, it applies the method of CCM (cell-to-cell mapping) to analyze the evolving trend and global behavior of a fuzzy dynamical system based on a cell state space, which is characterized by equilibrium, cost and their domain of attractions. Secondly, each rule base is evaluated to determine a performance index based on the information of the system obtained by CCM. Thirdly, CA (Genetic Algorithm) optimizes the coded rule bases according to the performance index generation by generation. The method presented in this paper can be applied to various systems (linear or nonlinear, continuous or discrete) to automatically obtain optimal rule base, for it fuses the advantages of GA and CCM. As an example, a complicated nonlinear system-an inverted pendulum is simulated to demonstrate the validity of the method. 相似文献