The Combination of Fuzzy Min–Max Neural Network and Semi-supervised Learning in Solving Liver Disease Diagnosis Support Problem

Tran, Thi Ngan; Vu, Dinh Minh; Tran, Manh Tuan; Le, Ba Dung

doi:10.1007/s13369-018-3351-7

Cited by 9 publications

(1 citation statement)

References 20 publications

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“…Heuristic algorithms are often used to provide suitable solutions to such problems [5]. Min-Min [6] algorithm, Max-Min [7] algorithm, and Heterogeneous Earliest-Finish-Time (HEFT) [8] algorithm are all such algorithms. Min-Min first calculates the minimum expected finish time of all tasks on all resources, then forms the expected finish matrix of these tasks.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Objective Cloud Workflow Scheduling Strategy Based on the Modified HEFT Algorithm

Wang

Deng

2023

J. Phys.: Conf. Ser.

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Aiming at the issues of poor system resource utilization and the challenge of ensuring the quality of service (QoS) in scientific workflow scheduling in the current cloud computing environment. By combining the existing IaaS cloud resource model with the scientific workflow task model, the article proposed a cloud workflow scheduling model framework. Firstly, proposed multi-objective QoS constraints based on the execution time and costs in scientific workflow scheduling. Then, modified the HEFT algorithm which was a typical scientific workflow scheduling algorithm. Based on the modified HEFT algorithm makes full use of the idle time of resources and maximizes the multi-objective QoS requirements of users. The comparative experiments show that the scheduling strategy of the modified HEFT algorithm can effectively optimize the costs and execution time of scientific workflow scheduling and achieve higher system resource utilization.

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