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检索条件"主题词=BAT algorithm"

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Hybridizing bat algorithm with Modified Pitch Adjustment Operator for Numerical Optimization Problems 1

Hybridizing Bat Algorithm with Modified Pitch Adjustment Ope...

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1st International Conference on Computer Science and Engineering (COMPSE)

作者： Ghanem, Waheed Ali H. M. Jantan, Aman Univ Sains Malaysia Sch Comp Sci Gelugor Penang Malaysia Univ Aden Fac Educ Saber Aden Yemen Univ Aden Fac Engn Aden Yemen Univ Sains Malaysia Sch Comp Sci Gelugor Penang Malaysia

ISBN: (纸本)9783319705422;9783319705415

This article introduces a new metaheuristic approach that is a hybrid of two known algorithms, for solving global optimization problems. The proposed algorithm is based on the bat algorithm (BA), which is inspired by the micro-bat echolocation phenomenon, and addresses the problems of local-optima trapping and low precision using an adjusted mutation operator from the Harmony Search (HS) algorithm. The proposed Hybrid bat Harmony (HBH) algorithm attempts to balance the good exploitation process of BA with a fast exploration feature inspired by HS. The design of HBH is introduced and its performance is evaluated against fourteen of the standard benchmark functions, and compared to that of the standard BA and HS algorithms and to another recent hybrid algorithm (HS/BA). The obtained results show that the new HBH method is indeed a promising addition to the arsenal of metaheuristic algorithms and can outperform the original BA and HS algorithms.

关键词： bat algorithm Global optimization problem Harmony search algorithm Pitch adjustment operator

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Integrating bat algorithm to Ordinal Optimization for Solving the Facility-Sizing Problem 10

Integrating Bat Algorithm to Ordinal Optimization for Solvin...

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10th International Conference on Knowledge and Smart Technology (KST) - Cybernetics in the Next Decades

作者： Horng, Shih-Cheng Lin, Shieh-Shing Chaoyang Univ Technol Dept Comp Sci & Informat Engn Taichung Taiwan St Johns Univ Dept Elect Engn Taipei Taiwan

ISBN: (纸本)9781538640159

Facility-sizing is more essential on small sites due to limitations on the space and the effects of imprecise judgement of facility size. The aim of facility-sizing problem is to efficiently install the facility to minimize the cost of installation and lower the probability of violating demand. In this work, an approach integrating hat algorithm (BA) to ordinal optimization (OO) is developed to find an optimal facility size for minimizing the cost of installation in manufacturing facilities. The solution method has two phases. The first phase utilizes the BA aided with a crude evaluation to construct a selected subset of candidate solutions. The second phase is to identify a near-optimal solution among the selected subset using the optimal computing budget allocation (OCBA) technique. The proposed approach has been tested on an example with m=10 facilities. Test results demonstrate that the proposed approach can yield a near-optimal solution within a reasonable computing time.

关键词： facility-sizing problem ordinal optimization bat algorithm optimal computing budget allocation facility installation cost

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A Novel bat algorithm based on Collaborative and Dynamic Learning of Opposite Population 22

A Novel Bat Algorithm based on Collaborative and Dynamic Lea...

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22nd IEEE International Conference on Computer Supported Cooperative Work in Design (CSCWD)

作者： Yong, Jiashi He, Fazhi Li, Haoran Zhou, Weiqing Wuhan Univ State Key Lab Software Engn Wuhan Hubei Peoples R China Wuhan Univ Sch Comp Sci & Technolgy Wuhan Hubei Peoples R China Sch Comp Sci & Technolgy Wuhan Hubei Peoples R China

ISBN: (纸本)9781538614822

As a new kind of swarm intelligence algorithms, bat algorithm is inspired by the bat's echolocation model to search an optimization solution. In this paper, we propose a novel bat algorithm based on collaborative and dynamic learning of opposite population. The proposed algorithm adapts a collaborative strategy to generate the opposite population. Therefore more possible opposite individuals can be dynamically learned and added to the population. We also present elite choices for the current and the opposite population. In this way, the search diversity and search intensity can be achieved. The experimental results of 8 typical test functions show that the proposed algorithm has the characteristics of fast convergence and avoiding falling into local optimal solution.

关键词： bat algorithm Opposition-based Learning Function optimization Swarm Intelligence algorithm

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Novel bat algorithm for Position Estimation of A GPS Receiver Located in Coastal Region of Southern India 8

Novel BAT Algorithm for Position Estimation of A GPS Receive...

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8th International Conference on Advances in Computing & Communications (ICACC)

作者： Kumar, Ashok N. Rao, G. Sasibhushana Lavanya, B. Andhra Univ Coll Engn A Dept Elect & Commun Engn Visakhapatnam Andhra Pradesh India

Based on the echo location principle used by bats, the bat algorithm (BA) has been developed. By introducing foraging of bats and doppler effect in the bat algorithm leads to generate Novel bat algorithm (NBA). In this paper, the NBA is implemented to estimate the position of a GPS receiver located in the coastal area of Southern India. The estimated results are compared with the original survey coordinates of the GPS receiver. The result shows that the Novel bat algorithm is a better metaheuristic bioevolutionary algorithm for GPS receiver position estimation. This algorithm can be useful to apply in RADAR, SONAR, and Indian Regional Navigational Satellite System (IRNSS) for Navigation, Tracking, and Positioning. (C) 2018 The Authors. Published by Elsevier B.V.

关键词： bat algorithm Doppler Effect foraging GPS metaheuristic

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Simplex bat algorithm for Solving System of Non-linear Equations 14th

Simplex Bat Algorithm for Solving System of Non-linear Equat...

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14th International Conference on Intelligent Computing (ICIC)

作者： Ge, Gengyu Ruan, Xuexian Chen, Pingping Ouyang, Aijia Zunyi Normal Univ Sch Informat Engn Zunyi 563006 Guizhou Peoples R China

ISBN: (纸本)9783319959290;9783319959306

In consideration of the fact that bat algorithm (BA) is sensitive to the initial values and simplex algorithm (SA) could often easily fall into local optimal, simplex - bat algorithm is put forward in this paper to solve system of non-linear equations based on the respective advantages of both algorithms. Such a combined algorithm does not only give full play to BAs global searching ability but also make full use of SA local searching ability. The results of simulation experiments show that this combined algorithm can be used to find the roots of all sorts of systems of non-linear equations with high accuracy, and moreover, with strong robustness and fast convergence rate, and therefore, it is indeed an effective method to solve system of non-linear equations.

关键词： System of non-linear equations Simplex algorithm bat algorithm Hybrid algorithm Optimization

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An Approach to Segment Computed Tomography Images using bat algorithm

An Approach to Segment Computed Tomography Images using Bat ...

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IEEE International Conference on Recent Trends in Electrical, Control and Communication (RTECC)

作者： Priyadharshini, F. R. Amirtha Hariprasad, N. Asvitha, S. Anandhi, V Priyadarshini, A. P. Swetha St Josephs Coll Engn Dept Elect & Instrumentat Engn Chennai 600119 Tamil Nadu India

ISBN: (纸本)9781538643105

Image evaluation actions are extensively applied to inspect a class of medical pictures recorded with a dedicated imaging approach. This work presents an automated computer assisted technique to mine and assess the Region of Interest (ROI) of Computed Tomography (CT) images. In this work, combination of multi-thresholding and the segmentation scheme is implemented to extract the ROI from Brain and Lung CT images. The multi-thresholding is implemented using bat algorithm (BA) and the Kapur's function and the segmentation is implemented with the level set (DRLS). After extracting the ROI from the CT pictures, the region properties of the ROI is evaluated using the GLCM features. The experimental result of this study confirms that, proposed approach is very efficient in extracting the ROI from the considered CT images. In future, this methodology can be used in hospitals to examine the real CT images.

关键词： CT image bat algorithm Kapur's entropy DRLS GLCM feature

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Novel Fitness Function for 3D Image reconstruction using bat algorithm based Autoencoder 18

Novel Fitness Function for 3D Image reconstruction using Bat...

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23rd ACM International Conference on 3D Web Technology

作者： Kuppili, Venkatanareshbabu Edla, Damodar Reddy Bablani, Annushree Natl Inst Technol Goa Farmagudi Goa India

ISBN: (纸本)9781450358002

With a view to investigate, examine and analyze the performance of 3D medical image compression based on Autoencoder neural networks, a novel algorithm named autoimage reconstruct algorithm is developed, which is based on recent bat bioinspired algorithm with a novel fitness function as Mean Square Error. It is observed that proposed algorithm outperforms existing algorithms like wavelet-based encoding and decoding for image compression and reconstruction in terms of Mean Square Error, Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR).

关键词： Image Reconstruction Autoencoder bat algorithm

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MOBA: Multi Objective bat algorithm for Combinatorial Optimization in VLSI 6

MOBA: Multi Objective Bat Algorithm for Combinatorial Optimi...

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6th International Conference on Smart Computing and Communications (ICSCC)

作者： Laudis, Lalin L. Shyam, Shilpa Jemila, Caroline Suresh, V Mar Ephraem Coll Engn & Technol Sch Elect & Commun Engn Elavuvilai India

It has to be conceded that the complexity of any integrated chip gets abated despite of the increased complexity. Notwithstanding, the perplexity of computing escalates exponentially. Thus computational optimization scores in the scene wherein several conflicting objectives has to be optimized without any compromise. Several years, scientists have solved any optimization problem by cogitating and considering it to be a Single Objective Optimization Problem (SOOP). However, mathematics has eulogized Multi Objective Optimization (MOO) methodologies to solve the conflicting tradeoffs. Besides, there is an instigation to converge our research to biologically inspired metaheuristics to solve optimization problems as it is evident from the anthologies and research archive that these heuristics perpetually doing well in solving optimization problems and that too in extension MOO problems. Researchers are captivated in the field to observe the perplexed processes of nature and mimic it solve optimization problems. In this research work, we have contemplated on the Multi Objective bat algorithm (MOBA) a biologically inspired metaheuristics and have successfully applied to solve the problem of floorplanning in VLSI design. The peculiar character of echolocation of microbats are being mimicked and applied to solve the problems in VLSI design. The intriguing attributes of bats;how it strives to take up its prey, are fathomed out and been adopted in problem solving. The problem is considered as a MOO problem wherein equal importance were given to wirelength minimization and dead space minimization. The results are discussed and rivalled with several other bio-inspired algorithms and are portrayed. To comprehend, the MOBA worked well in VLSI floorplanning optimization wherein the problems were considered with a single objective and multi objective fashion. (C) 2018 The Authors. Published by Elsevier B.V.

关键词： VLSI Floorplanning bat algorithm Combinatorial Optimization

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Modified Shuffled Multi-Population bat algorithm 7

Modified Shuffled Multi-Population Bat Algorithm

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7th International Conference on Computing, Communications and Informatics (ICACCI)

作者： Chaudhary, Reshu Banati, Hema Univ Delhi Dept Comp Sci Delhi India Univ Delhi Dyal Singh Coll Delhi India

ISBN: (纸本)9781538653142

Shuffled Multi-Population bat algorithm (SMPbat) is a recently proposed hybrid variant of bat algorithm. It incorporates the strengths of two recent variants of bat algorithm-Enhanced Shuffled bat algorithm and bat algorithm with Ring Master-Slave strategy. SMPbat hybridizes the sub-population generation and manipulation mechanism of the two algorithms to device an enhanced variant of BA. There are multiple parameters controlling the flow of execution of SMPbat. These parameters are set at the beginning of the execution of the algorithm. This paper proposes incorporation of multiparameter setting into SMPbat, where different sub-populations work with different sets of parameter values. Additionally, the impact of a refined search mechanism is also studied. The proposed variants are tested over 20 benchmark functions and a real-world optimization problem. Results establish the robustness of the proposed work.

关键词： bat algorithm Multi-Population algorithms Multi-Parameter Swarm algorithms Numerical optimization

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Cognitive decision engine design for CR based IoTs using Differential Evolution and bat algorithm 5

Cognitive decision engine design for CR based IoTs using Dif...

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5th International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Kaur, Avneet Kaur, Ashmeet Sharma, Surbhi TIET Dept Elect & Commun Engn Patiala Punjab India

ISBN: (纸本)9781538630457

Current research efforts in communication technology are shifting towards new paradigm namely, Internet of Things (IoTs). There is a strong need to tackle the challenge of introduction of massive data into network by IoT supported applications. For this, Cognitive Radio networks (CRNs) are seen as a potential solution. Enabling IoT objects with Cognitive radio features has led to new research dimension of CR based IoTs. Real time tuning of transmission parameters by Cognitive decision engine as per user needs and dynamic environment conditions is one of the important tasks. Determination of optimal value of transmission parameters becomes even more challenging for a multicarrier system because of high dimensionality as there are large number of decision variables to be optimized. Nature inspired metaheuristic optimization techniques offer an efficient and simple solution to the aforementioned problem. In this paper, comparative performance analysis of Differential evolution (DE) and bat algorithm has been done for the parameter tuning problem. The results demonstrate that the parameter adaptation by DE based engine outperforms the bat based implementation in terms of fitness score for the five different transmission modes supported by CR based IoTs.

关键词： bat algorithm cognitive decision engine differential evolution metaheuristic optimization

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