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ACADF: Ant Colony Unified with Adaptive Dragonfly Algorithm Enabled with Fitness Function for Model Transformation

机译:ACADF:蚁群与自适应蜻蜓算法统一,并带有适应度函数,可用于模型转换

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Model transformation is a key factor in the software project management. Model and its transformation is a key factor of software project process. This can be adapted by using some new transformation language. This paper aims to convert a class diagram (CLD) to Relational Schema (RS). Which include different perspective like, blocks, fitness function, and algorithm. Model transformation contribute major role in Model Driven Engineering (MDE). So transformation is perspective for the agile software development methodology. Transformation is part of agile methodology, which makes a better result for whole transformation process. For the same different algorithm are requiring for calculating the concern value for fitness function. This research work refer a optimization algorithm for phase 1 and phase 2 module and try to get a better output as compare to other algorithm like DA, PSO, ADF. This work will consider the Ant Colony optimization (ACO) algorithm integrated with dragonfly algorithm (ACADF) for the model transformation. These model transformations also consider the fitness function accordingly. Further it evaluate and analyzed using Automatic correctness (AC) and related fitness function, which pave the blocks for better result.
机译:模型转换是软件项目管理中的关键因素。模型及其转换是软件项目过程的关键因素。这可以通过使用一些新的转换语言进行调整。本文旨在将类图(CLD)转换为关系模式(RS)。其中包括不同的视角,例如块,适应度函数和算法。模型转换在模型驱动工程(MDE)中起主要作用。因此,转换是敏捷软件开发方法的前景。转换是敏捷方法论的一部分,可以为整个转换过程带来更好的结果。对于同一个,需要不同的算法来计算适应度函数的关注值。这项研究工作参考了阶段1和阶段2模块的优化算法,并试图与DA,PSO,ADF等其他算法相比获得更好的输出。这项工作将考虑与蜻蜓算法(ACADF)集成的蚁群优化(ACO)算法进行模型转换。这些模型转换也相应地考虑了适应度函数。进一步,它使用自动校正(AC)和相关的适应度函数进行评估和分析,为取得更好的结果铺平了道路。

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