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1.
In this paper we present novel ensemble classifier architectures and investigate their influence for offline cursive character recognition. Cursive characters are represented by feature sets that portray different aspects of character images for recognition purposes. The recognition accuracy can be improved by training ensemble of classifiers on the feature sets. Given the feature sets and the base classifiers, we have developed multiple ensemble classifier compositions under four architectures. The first three architectures are based on the use of multiple feature sets whereas the fourth architecture is based on the use of a unique feature set. Type-1 architecture is composed of homogeneous base classifiers and Type-2 architecture is constructed using heterogeneous base classifiers. Type-3 architecture is based on hierarchical fusion of decisions. In Type-4 architecture a unique feature set is learned by a set of homogeneous base classifiers with different learning parameters. The experimental results demonstrate that the recognition accuracy achieved using the proposed ensemble classifier (with best composition of base classifiers and feature sets) is better than the existing recognition accuracies for offline cursive character recognition. 相似文献
2.
《Information processing & management》2019,56(4):1300-1316
Dynamic Ensemble Selection (DES) strategy is one of the most common and effective techniques in machine learning to deal with classification problems. DES systems aim to construct an ensemble consisting of the most appropriate classifiers selected from the candidate classifier pool according to the competence level of the individual classifier. Since several classifiers are selected, their combination becomes crucial. However, most of current DES approaches focus on the combination of the selected classifiers while ignoring the local information surrounding the query sample needed to be classified. In order to boost the performance of DES-based classification systems, we in this paper propose a dynamic weighting framework for the classifier fusion during obtaining the final output of an DES system. In particular, the proposed method first employs a DES approach to obtain a group of classifiers for a query sample. Then, the hypothesis vector of the selected ensemble is obtained based on the analysis of consensus. Finally, a distance-based weighting scheme is developed to adjust the hypothesis vector depending on the closeness of the query sample to each class. The proposed method is tested on 30 real-world datasets with six well-known DES approaches based on both homogeneous and heterogeneous ensemble. The obtained results, supported by proper statistical tests, show that our method outperforms, both in terms of accuracy and kappa measures, the original DES framework. 相似文献
3.
本文在研究传统的DV-Hop3D算法基础上提出了一种新无线传感器网络定位算法。新算法在算法的第一阶段设置了跳数阈值参数以减小通信开销,并且在算法的第二阶段用可选择的平均跳距代替固定的平均跳距来计算未知节点到锚节点的距离,最后用Matlab7.1进行了仿真。仿真结果表明,该改进算法可明显提高节点定位精度,并且能有效降低网络通信量。 相似文献
4.
In the application of 2-D adaptive filters, a large amount of data must be processed and real-time processing is often required. In this paper, a new parallel-form realization of 2-D adaptive separable-denominator state-space filters suitable for high-speed processing is proposed. First, the 2-D local state-space model suitable for parallel processing is introduced. Next, the adaptive algorithm for this model is developed. This algorithm is based on the delayed least mean square (DLMS) method. In addition, the computation time required for the update of the coefficients is investigated. Finally, the proposed technique is applied to the design of 2-D digital filters in the spatial domain. 相似文献
5.
《Journal of The Franklin Institute》2022,359(4):1655-1676
This paper presents a privacy-preserving average consensus algorithm for a discrete-time network with heterogeneous dynamic nodes in the presence of Gaussian privacy noises. Rényi divergence is used to measure the privacy, and a distributed algorithm is proposed for each node in the network to protect the initial output state and ensure consensus almost surely. The convergence rate of the proposed algorithm relates to the communication topology, dynamics of systems, and decaying rates of privacy noises. Moreover, by increasing neighbors of nodes in the network, the proposed algorithm can strengthen preservation. To demonstrate the theoretical results, a numerical example is carried out on a network of one hundred nodes. 相似文献
6.
《Journal of The Franklin Institute》2023,360(12):7645-7675
Recently, the augmented complex-valued normalized subband adaptive filtering (ACNSAF) algorithm has been proposed to process colored non-circular signals. However, its performance will deteriorate severely under impulsive noise interference. To overcome this issue, a robust augmented complex-valued normalized M-estimate subband adaptive filtering (ACNMSAF) algorithm is proposed, which is obtained by modifying the subband constraints of the ACNSAF algorithm using the complex-valued modified Huber (MH) function and is derived based on CR calculus and Lagrange multipliers. In order to improve both the convergence speed and steady-state accuracy of the fixed step size ACNMSAF algorithm, a variable step size (VSS) strategy based on the minimum mean squared deviation (MSD) criterion is devised, which allocates individual adaptive step size to each subband, fully exploiting the structural advantages of SAF and significantly improving the convergence performance of the ACNMSAF algorithm as well as its tracking capability in non-stationary environment. Then, the stability, transient and steady-state MSD performance of the ACNMSAF algorithm in the presence of colored non-circular inputs and impulsive noise are analyzed, and the stability conditions, transient and steady-state MSD formulas are also derived. Computer simulations in impulsive noise environments verify the accuracy of theoretical analysis results and the effectiveness of the proposed algorithms compared to other existing complex-valued adaptive algorithms. 相似文献
7.
作为一种新兴的交通方式,高铁对旅游业有着重大的影响。"高铁旅游时代"已不再是一个陌生的词汇。本文以闽浙地区的高铁为例,分析高铁的发展给沿线地区旅游业带来的资源、客源、服务、营销等方面影响,并在此基础上提出高铁沿线地区旅游发展的新措施,以促进区域旅游的进一步提高。最后,本文对区域旅游的发展前景进行了展望,提出了未来旅游发展的目标。 相似文献
8.
基于二跳生成树的可扩展分簇定位算法 总被引：1，自引：0，他引：1
着重设计了一种基于二跳生成树的可扩展分簇定位算法.首先对传感器网络进行分簇、并利用簇头节点构造一个二跳生成树;在此基础上,由簇头计算各簇成员节点的局部坐标;最后,从生成树根节点开始,自顶向下合并各簇,生成所有节点的全局坐标,完成节点的相对定位. 理论分析与实验表明,本算法相对于现有的SDGPSN算法,能够有效提高定位覆盖率和定位精度,减少时间和通信开销,并具有更好的可扩展性. 相似文献
9.
《Journal of The Franklin Institute》2021,358(14):7221-7236
This paper researches the output consensus problem of heterogeneous linear multi-agent systems with cooperative and antagonistic interactions. Two fixed-time state compensator control approaches, one static dynamic and the other distributed adaptive dynamic, are considered for heterogeneous systems subject to logarithmic quantization. Then, a fixed-time output regulation control protocol is constructed to cope with the problem of bipartite output consensus and adaptive fixed-time output consensus of heterogeneous systems which is fully distributed without any global information. Besides, the fully distributed adaptive algorithm is employed to calculate the system matrix of leader and it’s also effectively eliminated the harmful chattering. Finally, two simulations are carried out to testify the feasibility of theoretical results. 相似文献
10.
以我国制造业上市公司为样本数据,用支持向量机作为基分类器的集成学习方法来预测企业的财务危机,通过具体实验分析可知:集成学习比单个基分类器的预测准确率提高了4个百分点,且稳定性更高,有效地提高了模型的预测精度,使得模型更具有准确性和应用性。基于支持向量机的集成学习方法在构建我国制造业上市公司财务危机预警模型上是有效的,且达到一定的财务危机预警效果。 相似文献
11.
《Information processing & management》2020,57(2):102180
Search task success rate is an important indicator to measure the performance of search engines. In contrast to most of the previous approaches that rely on labeled search tasks provided by users or third-party editors, this paper attempts to improve the performance of search task success evaluation by exploiting unlabeled search tasks that are existing in search logs as well as a small amount of labeled ones. Concretely, the Multi-view Active Semi-Supervised Search task Success Evaluation (MA4SE) approach is proposed, which exploits labeled data and unlabeled data by integrating the advantages of both semi-supervised learning and active learning with the multi-view mechanism. In the semi-supervised learning part of MA4SE, we employ a multi-view semi-supervised learning approach that utilizes different parameter configurations to achieve the disagreement between base classifiers. The base classifiers are trained separately from the pre-defined action and time views. In the active learning part of MA4SE, each classifier received from semi-supervised learning is applied to unlabeled search tasks, and the search tasks that need to be manually annotated are selected based on both the degree of disagreement between base classifiers and a regional density measurement. We evaluate the proposed approach on open datasets with two different definitions of search tasks success. The experimental results show that MA4SE outperforms the state-of-the-art semi-supervised search task success evaluation approach. 相似文献
12.
《Journal of The Franklin Institute》2022,359(8):3366-3388
This paper studies the cooperative fault-tolerant formation control problem of tracking a dynamic leader for heterogeneous multiagent systems consisting of multipile unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) with actuator faults under switching directed interaction topologies. Based on local neighborhood formation information, the distributed fault-tolerant formation controllers are constructed to ensure that all follower UAVs and UGVs can accomplish the demanding formation configuration in the state space and track the dynamic leader’s trajectory. By incorporating the sliding mode control and adaptive control technique, the actuator faults and unknown parameters of follower agents can be compensated. Through the theoretical analysis, it is proved that the cooperatively semiglobally uniformly ultimately boundedness of the closed-loop system is guaranteed, and the formation tracking errors converge to a small adjustable neighborhood of the origin. A simulation example is introduced to show the validity of the proposed distributed fault-tolerant formation control algorithm. 相似文献
13.
14.
《Journal of The Franklin Institute》2023,360(12):8936-8953
This work considers a distributed adaptive output feedback control problem for nonlinear constrained multi-agent systems (MAS) in the prescribed finite time. To begin with, a state observer is constructed to estimate the unmeasurable state. Then, we develop a novel observer based distributed adaptive prescribed finite time output feedback control algorithm by incorporating the prescribed finite-time control technique into the backstepping design method. Through Lyapunov stability theory, it can be shown that all signals of MASs are bounded, the tracking errors converge to the adjustable regions around the origin within the pre-given error accuracy and settling time, and all states keep in the prescribed constraint regions. Finally, a simulation example verifies the efficacy of the obtained theoretical results. 相似文献
15.
《Information processing & management》2022,59(5):103005
In real-life applications, resources in construction projects are always limited. It is of great practical importance to shorten the project duration by using intelligent models (i.e., evolutionary computations such as genetic algorithm (GA) and particle swarm optimization (PSO) to make the construction process reasonable considering the limited resources. However, in the general EC-based model, for example, PSO easily falls into a local optimum when solving the problem of limited resources and the shortest period in scheduling a large network. This paper proposes two PSO-based models, which are resource-constrained adaptive particle swarm optimization (RC-APSO) and an input-adaptive particle swarm optimization (iRC-APSO) to respectively solve the static and dynamic situations of resource-constraint problems. The RC-APSO uses adaptive heuristic particle swarm optimization (AHPSO) to solve the limited resource and shortest duration problem based on the analysis of the constraints of process resources, time limits, and logic. The iRC-APSO method is a combination of AHPSO and network scheduling and is used to solve the proposed dynamic resource minimum duration problem model. From the experimental results, the probability of obtaining the shortest duration of the RC-APSO is higher than that of the genetic PSO and GA models, and the accuracy and stability of the algorithm are significantly improved compared with the other two algorithms, providing a new method for solving the resource-constrained shortest duration problem. In addition, the computational results show that iRC-APSO can obtain the shortest time constraint and the design scheme after each delay, which is more valuable than the static problem for practical project planning. 相似文献
16.
Jiuwen Cao Tianlei Wang Luming Shang Xiaoping Lai Chi-Man Vong Badong Chen 《Journal of The Franklin Institute》2018,355(4):1539-1558
Earth surface vibrations generated by passing vehicles, excavation equipment, footsteps, etc., attract increasing attentions in the research community due to their wide applications. In this paper, we investigate the periodic vibration source localization problem, which has recently shown significance in excavation device detection and localization for urban underground pipeline network protection. An intelligent propagation distance estimation algorithm based on a novel fundamental frequency energy distribution (FBED) feature is developed for periodic vibration signal localization. Contributions of the paper lie in three aspects: 1) a novel frequency band energy distribution (FBED) feature is developed to characterize the property of vibrations at different propagation distances; 2) an intelligent propagation distance estimation model built on the FBED feature with machine learning algorithms is proposed, where for comparisons, the support vector machine (SVM) for regression and regularized extreme learning machine (RELM) are used; 3) a localization algorithm based on the distance-of-arrival (DisOA) estimation using three piezoelectric transducer sensors is given for source position estimation. To testify the effectiveness of the proposed algorithms, case studies on real collected periodic vibration signals generated by two electric hammers with different fundamental frequencies are presented in the paper. The transmission medium is the cement road and experiments on vibration signals recorded at different propagation distances are conducted. 相似文献
17.
常规粒子群算法(SPSO)在优化过程中易陷入局部最优,本文分析了常规粒子群算法陷入局部最优的原因,提出采用一种自适应粒子群算法(APSO)避免陷入局部最优,改善算法的收敛性和精度。最后用自适应粒子群算法设计宽带阶梯阻抗变换器,结果表明,与常规粒子群算法相比,自适应粒子群算法全局速度快、成功率和精度也有显著提高。 相似文献
18.
《Journal of The Franklin Institute》2023,360(4):3189-3207
This article investigates the rendezvous problem of heterogeneous multi-agent systems against Denial-of-Service attacks with preserving initial connectivity under a dynamic communication topology. The algorithm of resisting Denial-of-Service attack is first introduced to connectivity-preserving rendezvous problem of heterogeneous multi-agent systems. First of all, in order to observe the information of the leader, the distributed observers are designed to estimate the state of the leader with the communication network in the presence of Denial-of-Service attack by adaptive algorithm. Then, a switching system model is constructed by taking into account the influence of Denial-of-Service attacks. By means of the obtained model combined with a artificial potential function technique, the proposed distributed control algorithm allows all agents to accomplish rendezvous assignment with connectivity preservation as well as resisting Denial-of-Service attacks. Finally, detailed simulation validates the effectiveness of the proposed distributed observer and controller algorithm. 相似文献
19.
Kenneth Abend 《Journal of The Franklin Institute》2002,339(3):283-294
The Franklin Institute, Philadelphia, Pennsylvania, awarded the Benjamin Franklin Medal in Engineering to Bernard Widrow, Professor of Electrical Engineering at Stanford University, for pioneering work in adaptive signal processing. Adaptive systems have the ability to learn and improve their behavior through interaction with their environments. Dr. Widrow developed the least mean squared (LMS) algorithm, which is a computationally facile means of finding the optimal weight vector for suppressing unknown noise. For example, every high-speed modem contains an adaptive filter or automatic equalizer based on the Widrow-Hoff LMS algorithm. Such a telephone channel equalizer makes it possible for computers to communicate at high speed (such as for the internet) over regular telephone lines, which were never intended for this purpose. Dr. Widrow was amongst the first to publish a general theory of adaptive antennas, including space-time processing. His adaptive learning algorithms made artificial neural networks possible. His latest invention is a directional hearing aid. 相似文献
20.
《Journal of The Franklin Institute》2017,354(11):4457-4480
Due to the hopeful application of gathering information from unreachable position, wireless sensor network creates an immense challenge for data routing to maximize the communication with more energy efficiency. In order to design the energy efficient routing, the optimization based clustering protocols are more preferred in wireless sensor network. In this paper, we have proposed competent optimization based algorithm called Fractional lion (FLION) clustering algorithm for creating the energy efficient routing path. Here, the proposed clustering algorithm is used to increase the energy and lifetime of the network nodes by selecting the rapid cluster head. In addition, we have proposed multi-objective FLION clustering algorithm to develop the new fitness function based on the five objectives like intra-cluster distance, inter-cluster distance, cluster head energy, normal nodes energy and delay. Here, the proposed fitness function is used to find the rapid cluster centroid for an efficient routing path. Finally, the performance of the proposed clustering algorithm is compared with the existing clustering algorithms such as low energy adaptive clustering hierarchy (LEACH), particle swarm optimization (PSO), artificial bee colony (ABC) and Fractional ABC clustering algorithm. The results proved that the lifetime of the wireless sensor nodes is maximized by the proposed FLION based multi-objective clustering algorithm as compared with existing protocols. 相似文献