A Fuzzy Bat Clustering Method for Ergonomic Screening of Office Workplaces

Khan, K.; Nikov, Alexander; Sahai, Ashok

doi:10.1007/978-3-642-23163-6_9

Cited by 68 publications

(35 citation statements)

References 13 publications

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“…Robustness of the proposal is better than GA. Selim Yilmaz and Ecir U. Kucuksille [13] Improved bat for Continuous Optimization Decrease the lack of exploration and Increase the Local Search capability. Koffka Khan, Alexander Nikov [8] Fuzzy Based Bat Algorithm By change the velocity bats local best found easily to get better solution. Jian Xie, Yongquan Zhou [7] Bat Based Levy flight Trajectory The parameter initialization changes and improve the local search capability.…”

Section: Advancement In Bat Algorithmmentioning

confidence: 99%

Review of Load Balancing is Distributed Computing and Bat Algorithm

Rani¹,

Kaur²

2017

IJARCSSE

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management of the resources in the various workloads is the key factor of the performance of the distributed computing infrastructure such as (cloud computing, cluster computing and grid computing). Maximizing the resource utilization and enhance the overall performance of the distributed computing infrastructure distribute the workload among the available resource. We can say that the performance is also dependent on the policy of load balancing if load balancing policy is good its leads to better performance and maximize the resource utilization. Grid computing is collection of heterogeneous system from the multiple administrative domains which are geographically distributed to preform parallel processing on demand and provide single coherent view to the user. It suffers from three main challenges scalability, adaptability and heterogeneity. In this paper we provides a detailed study of various load balancing techniques used in the distributed computing which provides you better understanding of various load balancing algorithm with the distributed computing infrastructure.Keyword: Load balancing, grid computing, cluster computing, cloud computing, distributed computing. I. INTRODUCTIONDistributed computing is the most favourable area computer science in which the resources are physically distributed and connected via network and perform communication the help of message passing techniques to perform a common goal the user is always unknown about that processing is going on parallel multiple system he always think the process is going on single system because distributed computing provide single coherent view to the user. Applications of the distributed computing are (cloud computing, grid computing, peer to peer and cluster computing).[1] Distributed computing always able to run those applications which is especially written for run in distributed environment we cannot run all the application on distributed infrastructure and message passing is performed for communication with the help of various methods such as RPC (Remote Procedure Call), HTTP and message ques.[2] Challenges in the distributed computing is the maintain various kind of transparency such as location transparency, migration transparency and relocation transparency.Cloud computing is mechanism of providing on demand services for the various purpose such as (storage, processing and infrastructure). It is an application of the distributed computing it is used internet based communication system means user can demand for the service by using internet and cloud computing provides the resource on demand as per the need of the user. Cloud computing is the pool of the resources where all users are sharing the resources transparently they are not aware of that any other user is also using the same resource each user things the resource used by them is only dedicated to them this is due to transparency maintain by the cloud service provider with the help of virtualization and they also offer virtualization on hardware level not only applicatio...

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Section: Advancement In Bat Algorithmmentioning

confidence: 99%

Review of Load Balancing is Distributed Computing and Bat Algorithm

Rani¹,

Kaur²

2017

IJARCSSE

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“…Later, many variations of Bat algorithms were put forth by many researchers. A Binary Bat Algorithm logic Bat algorithm [12] etc. Even though there are many variants of Bat algorithm designed to solve various applications the basic working principle remains the same.…”

Section: Bat Algorithmmentioning

confidence: 99%

A Binary Bat Inspired Algorithm for the Classification of Breast Cancer Data

Doreswamy¹,

M²

2016

IJSCAI

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Advancement in information and technology has made a major impact on medical science where the researchers come up with new ideas for improving the classification rate of various diseases. Breast cancer is one such disease killing large number of people around the world. Diagnosing the disease at its earliest instance makes a huge impact on its treatment. The authors propose a Binary Bat Algorithm (BBA) based Feedforward Neural Network (FNN) hybrid model, where the advantages of BBA and efficiency of FNN is exploited for the classification of three benchmark breast cancer datasets into malignant and benign cases.Here BBA is used to generate a V-shaped hyperbolic tangent function for training the network and a fitness function is used for error minimization. FNNBBA based classification produces 92.61% accuracy for training data and 89.95% for testing data.

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“…Presented by Yang [17] in 2010, the bat algorithm (BA) was inspired by the bat echolocation behavior. Its applications can be seen on several different research domains, such as clustering [29], engineering optimization [30], and multi-objective optimization [31]. To enhance the performance of BA, Khan et al [29] combined BA with the fuzzy concept to solve the clustering problem.…”

mentioning

confidence: 99%

“…Its applications can be seen on several different research domains, such as clustering [29], engineering optimization [30], and multi-objective optimization [31]. To enhance the performance of BA, Khan et al [29] combined BA with the fuzzy concept to solve the clustering problem. In a later study [30], Yang and Gandomi pointed out that the convergence rate and the result of BA will be affected by the setting of the loudness i A and pulse emission rate i r of bats [32].…”

mentioning

confidence: 99%

Recent Development of Metaheuristics for Clustering

Tsai

Huang

Chiang

2014

Lecture Notes in Electrical Engineering

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Abstract. Metaheuristics have been successfully applied to quite a lot of services, systems, and products frequently found in our daily life. Until now, none of the metaheuristics ever proposed are perfect for all the optimization problems; rather, each algorithm has its pros and cons. Although several highperformance metaheuristics exist, there is still plenty of room to improve the final result they produce and the computation time they take. Since 2001, quite a few number of novel metaheuristics have been developed to provide a better way for solving the optimization problems. A brief review for eight of these novel metaheuristics is given in this paper. To evaluate the performance of these algorithms, we apply them to a well-known combinatorial optimization problem, data clustering, and the results are analyzed and discussed.

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A Fuzzy Bat Clustering Method for Ergonomic Screening of Office Workplaces

Cited by 68 publications

References 13 publications

Review of Load Balancing is Distributed Computing and Bat Algorithm

Review of Load Balancing is Distributed Computing and Bat Algorithm

A Binary Bat Inspired Algorithm for the Classification of Breast Cancer Data

Recent Development of Metaheuristics for Clustering

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