The problems of hot spot and energy consumption of nodes in wireless sensor networks (WSNs) have been tackled by the adoption of hybrid energy efficient distributed (HEED) and unequal clustering algorithm to prolong t...
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The problems of hot spot and energy consumption of nodes in wireless sensor networks (WSNs) have been tackled by the adoption of hybrid energy efficient distributed (HEED) and unequal clustering algorithm to prolong the network lifetime (UCAPN) protocols. These have involved the implementation of unequally sized clusters that are based on the distance of cluster head (CH) from the base station (BS). The BS partitions the network area into several radially divided zones depending on the distance from centre of the field and CHs are independently selected in each zone. Clustering, on the other hand, controls how data are transmitted and allows for aggregation in the clusters. However, whereas these topologies have been able to improve network life time, the problem of network void still persists. To address this, a radially optimized zone-divided energy-aware WSN protocol using bat algorithm is proposed. This protocol considers not only the distance from the BS, but also the angle at which the WSN develops. It gives a unique and equal opportunity for each sensor network to have ambience area for communicating and sensing necessary for its routing operations. Besides, it divides the sensing area into radial zones and employs the unequal clustering method in these zones to resolve the hot-spot problem. Based on the merits of zone-divided networks, CHs with great residual energy present in the high-energy regions are selected as the relay node in the inter-cluster multi-hop routing stage. Simulation results show that the proposed technique outperforms both HEED and UCAPN protocols. bat algorithm is capable of predicting most critical nodes and generates a scalable and feasible energy-efficient routing technique for radially optimized zone-divided energy-aware WSN. By exploiting the angle at which the WSN develops, this protocol avails equal opportunity for each sensor network to have enough fields for communicating and sensing necessary for its routing operations. Using
In this paper, we propose a novel image thresholding method based on the interval type-2 fuzzy set (IT2FS). The interval type-2 fuzzy membership function (IT2FMF) is generated from a bag of type-1 fuzzy membership fun...
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In this paper, we propose a novel image thresholding method based on the interval type-2 fuzzy set (IT2FS). The interval type-2 fuzzy membership function (IT2FMF) is generated from a bag of type-1 fuzzy membership functions (T1FMFs) chosen adaptively based on the image characteristics for a given problem. An evolutionary algorithm called bat algorithm is used to enhance the computational efficiency of the proposed thresholding technique. It is expected that the IT2FS based threshold technique will be better than that of the methods based on type-1 fuzzy set due to superior uncertainty handling capacity of the former technique. This fact is experimentally verified using benchmark dataset. The performance and robustness of the proposed method under different noise corruptions are measured statistically on the dataset by modified Cramer-Rao bound. The segmentation performance of the proposed method is compared experimentally with that of the state-of-the-art methods based on fuzzy and non-fuzzy frameworks. It is observed that the proposed method can achieve a higher segmentation accuracy in comparison to other state-of-the-art methods when they are benchmarked against the Modified Cramer-Rao Bound. Also, on average the misclassification error (ME) of the proposed method in segmentation is found to be minimum in comparison to the state-of-the-art methods. (C) 2017 Elsevier B.V. All rights reserved.
The problem of node localization in wireless sensor networks aims to assign th e geographical coordinates to each device with unknown position, in the deployment area. In this paper the meta heuristic optimization alg...
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The problem of node localization in wireless sensor networks aims to assign th e geographical coordinates to each device with unknown position, in the deployment area. In this paper the meta heuristic optimization algorithm known as bat algorithm is described in order to evaluate the precision of node localization problem in wireless sensor networks. Meanwhile the existing bat algorithm has also been modified by using the bacterial foraging strategies of bacterial foraging optimization algorithm. Compared with the existing bat algorithm, the proposed modified bat algorithm is shown through simulations to perform constantly better not only in increasing localization success ratios and fast convergence speed but also enhance its robustness.
As the development of photovoltaic (PV) power generation continuously accelerated the total installed capacity of PV, the traditional static load model is difficult to meet the needs of the power grid with the increas...
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As the development of photovoltaic (PV) power generation continuously accelerated the total installed capacity of PV, the traditional static load model is difficult to meet the needs of the power grid with the increasing penetration of PV. And the dynamic model of grid-connected PV power generation is complicated and there are plenty parameters need to be identified, so the dynamic model of grid-connected PV power generation are extremely challenging to apply in wide-area power system. In this paper, a discrete-time equivalent model of PV (PDEM) is established based on the third-order dynamic differential equation of the PV power generation system and the parameters of the PDEM are identified using the least squares (LS) and the bat algorithm (BA). Besides, the dynamic characteristics of the PV power generation grid connected system with different permeability and the fitting residuals of the two methods is analyzed in the IEEE14-bus system incorporated into the PV system. The applicability of the PDEM is verified by setting short circuit grounding fault and changing the PV permeability and voltage dip. The simulation results demonstrate that the PDEM has a strong adaptability and good applicability in the case of high PV permeability with a wide application. And the applicability of the BA in identification of PDEM are given in this paper. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
This paper presents a current sharing method to actively balance the output currents of a parallel dc-dc converters' (PDCC) system regarding the demanded power. First, the operating principle of the PDCC system wi...
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This paper presents a current sharing method to actively balance the output currents of a parallel dc-dc converters' (PDCC) system regarding the demanded power. First, the operating principle of the PDCC system with parallel-connected bidirectional converters is studied. To regulate the output voltage in dc bus and share the output currents of the individual converters, a dual-loop control architecture comprising an outer voltage control loop and multiple inner current control loops is designed based on the automatic master-slave control scheme. Moreover, a feedback-type two-degree-of-freedom proportional-integral-derivative (FB2PID) controller is introduced to obtain the pulse-width modulation control signals for the converters. In order to improve the dynamic response and robustness of the active current-sharing control performances of the FB2PID controlled PDCC system, a bat algorithm (BA)-optimized FB2PID control system is further proposed to concurrently and dynamically optimize the control parameters of the FB2PID controller in the current control loop. Thus, the output current of each converter can be controlled to share the demand power equally in the presence of uncertainties. Finally, the simulation and experimental results reveal that the proposed BA-optimized FB2PID control system outperforms the conventional PID and FB2PID control systems with regard to the voltage regulation and current sharing performances under the time-varying electric load condition.
The bat algorithm is one of the recent nature-inspired algorithms, which has been emerged as a powerful search method for solving continuous as well as discrete problems. The quadratic assignment problem is a well-kno...
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The bat algorithm is one of the recent nature-inspired algorithms, which has been emerged as a powerful search method for solving continuous as well as discrete problems. The quadratic assignment problem is a well-known NP-hard problem in combinatorial optimization. The goal of this problem is to assign n facilities to n locations in such a way as to minimize the assignment cost. For that purpose, this paper introduces a novel discrete variant of bat algorithm to deal with this combinatorial optimization problem. The proposed algorithm was evaluated on a set of benchmark instances from the QAPLIB library and the performance was compared to other algorithms. The empirical results of exhaustive experiments were promising and illustrated the efficacy of the suggested approach. (C) 2017 Production and hosting by Elsevier B.V. on behalf of Faculty of Computers and Information, Cairo University. This is an open access article under the CC BY-NC-ND license.
A novel bat algorithm (NBA) is proposed for optimization in this paper, which focuses on further mimicking the bats' behaviors and improving bat algorithm (BA) in view of biology. The proposed algorithm incorporat...
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A novel bat algorithm (NBA) is proposed for optimization in this paper, which focuses on further mimicking the bats' behaviors and improving bat algorithm (BA) in view of biology. The proposed algorithm incorporates the bats' habitat selection and their self-adaptive compensation for Doppler effect in echoes into the basic BA. The bats' habitat selection is modeled as the selection between their quantum behaviors and mechanical behaviors. Having considered the bats' self-adaptive compensation for Doppler effect in echoes and the individual's difference in the compensation rate, the echolocation characteristics of bats can be further simulated in NBA. A self-adaptive local search strategy is also embedded into NBA. Simulations and comparisons based on twenty benchmark problems and four real-world engineering designs demonstrate the effectiveness, efficiency and stability of NBA compared with the basic BA and some well-known algorithms, and suggest that to improve algorithm based on biological basis should be very efficient. Further research topics are also discussed. (C) 2015 Elsevier Ltd. All rights reserved.
All task scheduling applications need to ensure that resources are optimally used,performance is enhanced,and costs are *** purpose of this paper is to discuss how to Fitness Calculate Values(FCVs)to provide applicati...
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All task scheduling applications need to ensure that resources are optimally used,performance is enhanced,and costs are *** purpose of this paper is to discuss how to Fitness Calculate Values(FCVs)to provide application software with a reliable solution during the initial stages of load *** cloud computing environment is the subject of this *** consists of both physical and logical components(most notably cloud infrastructure and cloud storage)(in particular cloud services and cloud platforms).This intricate structure is interconnected to provide services to users and improve the overall system’s *** case study is one of the most important segments of cloud computing,i.e.,Load *** paper aims to introduce a new approach to balance the load among Virtual Machines(VM’s)of the cloud computing *** proposed method led to the proposal and implementation of an algorithm inspired by the bat algorithm(BA).This proposed Modified bat algorithm(MBA)allows balancing the load among virtual *** proposed algorithm works in two variants:MBA with Overloaded Optimal Virtual Machine(MBAOOVM)and Modified bat algorithm with Balanced Virtual Machine(MBABVM).MBA generates cost-effective solutions and the strengths of MBA are finally validated by comparing it with bat algorithm.
bat algorithm (BA) is a recent metaheuristic optimization algorithm proposed by Yang. In the present study, we have introduced chaos into BA so as to increase its global search mobility for robust global optimization....
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bat algorithm (BA) is a recent metaheuristic optimization algorithm proposed by Yang. In the present study, we have introduced chaos into BA so as to increase its global search mobility for robust global optimization. Detailed studies have been carried out on benchmark problems with different chaotic maps. Here, four different variants of chaotic BA are introduced and thirteen different chaotic maps are utilized for validating each of these four variants. The results show that some variants of chaotic BAs can clearly outperform the standard BA for these benchmarks. (C) 2013 Elsevier B.V. All rights reserved.
In this work, minimum weight optimization of laminated composite is performed using a newly developed enhanced bat algorithm (EBA). bat algorithm (BA) is a recently developed swarm-based optimization technique which i...
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In this work, minimum weight optimization of laminated composite is performed using a newly developed enhanced bat algorithm (EBA). bat algorithm (BA) is a recently developed swarm-based optimization technique which is inspired by the echolocation behavior of bats. The standard BA shows premature convergence and reduced convergence speeds under some conditions. So, the EBA is used to perform the design optimization of laminated composites. The laminate analysis based on classical laminate theory is utilized for the stress calculations. Tsai-Wu failure curve is considered as the constraint in this constrained optimization problem. Number of plies at each orientation angle are considered as the design variables. The design optimization has been carried out for both conventional and unconventional (dispersed plies) stacking sequences considering different loading configurations: uniaxial tension, biaxial tension with and without shear loadings. Ply angles dispersed in the range of 5 circle\-85 circle 25 circle-65 circle and 0 circle\-90 circle} at intervals of 5 circle are considered for the unconventional stacking sequence to increase damage tolerance. In addition, a new mathematical function is proposed to measure the dispersion of ply angles in the laminate called the dispersion function. Also, the performance of EBA is compared with standard BA in the optimum weight design of composite laminates.
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