Security is a critical problem in implementing mobile ad hoc networks (MANETs) because of their vulnerability to routing attacks. Although providing authentication to packets at each stage can reduce the risk, routing...
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ISBN:
(纸本)9783030009793;9783030009786
Security is a critical problem in implementing mobile ad hoc networks (MANETs) because of their vulnerability to routing attacks. Although providing authentication to packets at each stage can reduce the risk, routing attacks may still occur due to the delay in time of reporting and analyzing the packets. Therefore, this authentication process must be further investigated to develop efficient security techniques. This paper proposes a solution for detecting black hole attacks on MANET by using harmony search algorithm (DBHSA), which uses harmony search algorithm (HSA) to mitigate the lateness problem caused by cooperative bait detection scheme (CBDS). Data are simulated and analyzed using MATLAB. The simulation results of HSA, DSR, and CBDS-DSR are provided. This study also evaluates the manner through which HSA can reduce the inherent delay of CBDS. The proposed approach detects and prevents malicious nodes, such as black hole attacks that are launched in MANETs. The results further confirm that the HSA performs better than CBDS and DSR.
In existing system-optimal traffic-responsive signal strategies, the individual driver's interest is always neglected. In order to make a compromise between user equilibrium (individual delay) and system optimalit...
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ISBN:
(纸本)9781728111643
In existing system-optimal traffic-responsive signal strategies, the individual driver's interest is always neglected. In order to make a compromise between user equilibrium (individual delay) and system optimality (total delay), a traffic signal scheduling strategy with consideration of drivers' unhappiness is firstly developed based on the cell transmission model (CTM). The exponential function is adopted to delineate the driver's anxiety according to their waiting time, which leads to the assignment of the traffic signals is dominated by drivers' waiting time but not the total volume demand. By adopting the discrete harmony search algorithm (DHS), numerical simulation results illustrate the effectiveness of our real-time traffic light scheduling. Secondly, in order to satisfy the trade-off between the proposed cost (drivers' unhappiness) and the common traffic performance (network delay), a bi-objective urban traffic light scheduling problem by minimizing both the drivers' unhappiness and the total network delay is proposed, which is solved by the non-dominated sorting genetic algorithm II (NSGA-II) and non-dominated sorting harmony search algorithm (NSHS). Experiments are carried out to compare the efficiency of both algorithms.
Over the last few decades, multiple advances have been done for the classification of vegetation area through land cover, and land use. However, classification problem is one of the most complicated and contradicting ...
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Over the last few decades, multiple advances have been done for the classification of vegetation area through land cover, and land use. However, classification problem is one of the most complicated and contradicting problems that has received considerable attention. Therefore, to tackle this problem, this paper proposes a new Firefly-harmonysearch based Deep Belief Neural Network method (FHS-DBN) for the classification of land cover, and land use. The segmentation process is done using Bayesian Fuzzy Clustering,and the feature matrix is developed. The feature matrix is given to the proposed FHS-DBN method that distinguishes the land coverfrom the land use in the multispectral satellite images, for analyzing the vegetation area. The proposed FHS-DBN method is designedby training the DBN using the FHS algorithm, which is developed by the combination of Firefly algorithm (FA) and harmonysearch (HS) algorithm. The performance of the FHS-DBN model is evaluated using three metrics, such as Accuracy, True Positive Rate (TPR), and False Positive Rate (FPR). From the experimental analysis, it is concludedthat the proposed FHS-DBN model achieves ahigh classification accuracy of 0.9381, 0.9488, 0.9497, and 0.9477 usingIndian Pine, Salinas scene, Pavia Centre and university, and Pavia University scene dataset.
To improve the optimization performance of harmony search algorithm, an improved novel global harmonysearch (INGHS) algorithm with new improvisation process is proposed in this paper. INGHS algorithm is presented to ...
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ISBN:
(纸本)9781538612446
To improve the optimization performance of harmony search algorithm, an improved novel global harmonysearch (INGHS) algorithm with new improvisation process is proposed in this paper. INGHS algorithm is presented to address robust pole assignment for descriptor system With all the finite poles restrict in an arbitrary specified circular region. The object is converted into a nonlinear optimization problem with constraints for the transient performance request. In terms of the robust circular region stability constraints, the upper hound of the spectral norm for the perturbation or the uncertainty is optimized such that the desired poles of the closed-loop system and the state feedback controller can be optimized simultaneously. To evaluate the performance of the proposed INGHS algorithm, comparison with other harmonysearch variants algorithm for the problem is carried out. Finally, the simulation results illustrate the effectiveness of the proposed method.
Aiming at overcoming the shortcomings of common telecommunication customer churn prediction models as single model and poor classification performance, a gradient decision tree integration model (GBDT) prediction mode...
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ISBN:
(纸本)9789811513770;9789811513763
Aiming at overcoming the shortcomings of common telecommunication customer churn prediction models as single model and poor classification performance, a gradient decision tree integration model (GBDT) prediction model is proposed, and the important parameters are searched by harmonic searchalgorithm (HS). We built a telecom customer churn prediction model based on HS-GBDT algorithm. This model compares the parameter combinations to be optimized in the GBDT algorithm into the synthesized harmony in the HS algorithm, and seeks the optimal parameter combination of the GBDT model through continuous iteration of the harmony. The experimental results show that the combined model has higher classification accuracy than Logistic regression, support vector machine and random forest, and can provide good decision support for major telecom operators in the process of customer churn management.
In this paper, the optimal distribution model of hydropower load is proposed and the operation constraints of wind power and hydropower are taken into consideration. In the process of sending power to the provincial n...
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In this paper, the optimal distribution model of hydropower load is proposed and the operation constraints of wind power and hydropower are taken into consideration. In the process of sending power to the provincial network, the harmonic searchalgorithm is introduced to optimize the maximum power generation target, and the validity of the model is verified in the case of central China regional power grid. (C) 2019 The Authors. Published by Elsevier Ltd.
Aim to improve the default of harmonysearch(HS) algorithm which is easily trapping into local optima while doing global *** improved optimization algorithm presented in this *** historical iteration information to ...
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Aim to improve the default of harmonysearch(HS) algorithm which is easily trapping into local optima while doing global *** improved optimization algorithm presented in this *** historical iteration information to set up an instructive dataset,then the global search mechanism is combined with a local search *** that,an integer planning study based on distance strategy and the fuzzy constraint processing in spatial division of solution *** proposed model combines with FCM applied in image *** experimental results show that the proposed method can get more accuracy and less CPU operation time versus FCM and s-FCM.
This paper proposes the use of series FACTS devices to relieve congestion and enhance the security in restructured power system. harmony search algorithm as a novel heuristic algorithm is employed for optimal locating...
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This paper proposes the use of series FACTS devices to relieve congestion and enhance the security in restructured power system. harmony search algorithm as a novel heuristic algorithm is employed for optimal locating and sizing of series FACTS devices. In order to reduce the solution space and to pinpoint the lines which are more suitable for FACTS device placement line outage sensitivity factors is employed. Two different objective functions are considered in the optimization problem, the first one is the total congestion cost and the other is total generation cost. To validate the effectiveness of the proposed method and show its efficiency, the simulations are carried out on IEEE 14-bus test system. The results of the proposed method are compared with those obtained by particle swarm optimization and with those obtained by congestion rent contribution method.
Wireless sensor networks (WSNs) is one of the most important technologies in this century. As sensor nodes have limited energy resources, designing energy-efficient routing algorithms for WSNs has become the research ...
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Wireless sensor networks (WSNs) is one of the most important technologies in this century. As sensor nodes have limited energy resources, designing energy-efficient routing algorithms for WSNs has become the research focus. And because WSNs routing for maximizing the network lifetime is a NP-hard problem, many researchers try to optimize it with meta-heuristics. However, due to the uncertain variable number and strong constraints of WSNs routing problem, most meta-heuristics are inappropriate in designing routing algorithms for WSNs. This paper proposes an Improved harmonysearch Based Energy Efficient Routing algorithm (IHSBEER) for WSNs, which is based on harmonysearch (HS) algorithm (a meta-heuristic). To address the WSNs routing problem with HS algorithm, several key improvements have been put forward: First of all, the encoding of harmony memory has been improved based on the characteristics of routing in WSNs. Secondly, the improvisation of a new harmony has also been improved. We have introduced dynamic adaptation for the parameter HMCR to avoid the prematurity in early generations and strengthen its local search ability in late generations. Meanwhile, the adjustment process of HS algorithm has been discarded to make the proposed routing algorithm containing less parameters. Thirdly, an effective local search strategy is proposed to enhance the local search ability, so as to improve the convergence speed and the accuracy of routing algorithm. In addition, an objective function model that considers both the energy consumption and the length of path is developed. The detailed descriptions and performance test results of the proposed approach are included. The experimental results clearly show the advantages of the proposed routing algorithm for WSNs. (C) 2015 Elsevier B.V. All rights reserved.
In this paper, We propose a memetic based framework called Optimized Symmetric Partial Facegraphs (OSPF) to recognize faces prone to adverse conditions such as facial occlusions, expression and illumination variations...
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In this paper, We propose a memetic based framework called Optimized Symmetric Partial Facegraphs (OSPF) to recognize faces prone to adverse conditions such as facial occlusions, expression and illumination variations. Faces are initially segmented into facial components and optimal landmarks are automatically generated by exploiting the bilateral symmetrical property of human faces. The proposed approach combines an improved harmony search algorithm and an intelligent single particle optimizer to take advantage of their global and local search capabilities. Basically, the hybridization version aids to compute the optimal landmarks. These landmarks further serve as the building blocks to intuitively construct the partial facegraphs. The efficiency of the proposed approach has been investigated in addressing the facial occlusion problem when only one exemplar face image per subject is available using comprehensive experimental validations. The proposed approach yields improved recognition rates when compared to recent state-of-the-art techniques. (C) 2017 Elsevier Inc. All rights reserved.
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