Effectiveness of approximation strategy in surrogate-assisted fireworks algorithm
نویسندگان
چکیده
منابع مشابه
Effectiveness of approximation strategy in surrogate-assisted fireworks algorithm
We investigate the effectiveness of approximation strategy in a surrogate-assisted fireworks algorithm, which obtains the elite from approximate fitness landscape to enhance its optimization performance. We study the effectiveness of approximation strategy from the aspects of approximation method, sampling data selection method and sampling size. We discuss and analyse the optimization performa...
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رشد انفجاری تکنولوژی فرصت های آموزشی مهیج و جدیدی را پیش روی فراگیران و آموزش دهندگان گذاشته است. امروزه معلمان برای اینکه در امر آموزش زبان بروز باشند باید روش هایی را اتخاذ نمایند که درآن ها از تکنولوژی جهت کمک در یادگیری زبان دوم و چندم استفاده شده باشد. با در نظر گرفتن تحولاتی که رشته ی آموزش زبان در حال رخ دادن است هم اکنون زمان مناسبی برای ارزشیابی نگرش های موجود نسبت به تکنولوژی های جدید...
15 صفحه اولIntroduction to Fireworks Algorithm
Inspired by fireworks explosion at night, conventional fireworks algorithm (FWA) was developed in 2010. Since then, several improvements and some applications were proposed to improve the efficiency of FWA. In this paper, the conventional fireworks algorithm is first summarized and reviewed and then three improved fireworks algorithms are provided. By changing the ways of calculating numbers an...
متن کاملFireworks Algorithm for Optimization
Inspired by observing fireworks explosion, a novel swarm intelligence algorithm, called Fireworks Algorithm (FA), is proposed for global optimization of complex functions. In the proposed FA, two types of explosion (search) processes are employed, and the mechanisms for keeping diversity of sparks are also well designed. In order to demonstrate the validation of the FA, a number of experiments ...
متن کاملAn Adaptive Surrogate-Assisted Strategy for Multi-Objective Optimization
1. Abstract A sequential metamodel-based optimization method is proposed for multi-objective optimization problems. The algorithm, designated as Pareto Domain Reduction, is an adaptive sampling method and an extension of the classical Domain Reduction approach (also known as the Sequential Response Surface Method). In addition to standard benchmark examples, a Multidisciplinary Design Optimizat...
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ژورنال
عنوان ژورنال: International Journal of Machine Learning and Cybernetics
سال: 2015
ISSN: 1868-8071,1868-808X
DOI: 10.1007/s13042-015-0388-8