Mobile cloud computing : architectures, algorithms and applications

اختصاصی از حامی فایل Mobile cloud computing : architectures, algorithms and applications دانلود با لینک مستقیم و پر سرعت .

Mobile cloud computing : architectures, algorithms and applications Volume: Author(s): De, Debashis Series: A Chapman & Hall book; CRCnetBase Periodical: Publisher: CRC Press, Taylor & Francis Group City: London, New York, Boca Raton Year: 2016 Edition: Language: English Pages (biblio\tech): 368\0 ISBN: 978-1-4822-4284-3, 1482242842 ID: 1444672 Time added: 2016-01-24 03:00:00 Time modified: 2016-03-20 07:50:50 Library: Library issue: Size: 34 MB (35869762 bytes) Extension: pdf

مقاله هوش مصنوعی Complexity of and Algorithms for Borda Manipulation

اختصاصی از حامی فایل مقاله هوش مصنوعی Complexity of and Algorithms for Borda Manipulation دانلود با لینک مستقیم و پر سرعت .

Distributed Algorithms

اختصاصی از حامی فایل Distributed Algorithms دانلود با لینک مستقیم و پر سرعت .

In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers.

اختصاصی از حامی فایل Ranking and comparing evolutionary algorithms with Hellinger-TOPSIS دانلود با لینک مستقیم و پر سرعت .

Ranking and comparing evolutionary algorithms with Hellinger-TOPSIS

ژورنال: Applied Soft Computing

سال: December 2015

قیمت اصلی:35.95$

Abstract

When multiple algorithms are applied to multiple benchmarks as it is common in evolutionary computation, a typical issue rises, how can we rank the algorithms? It is a common practice in evolutionary computation to execute the algorithms several times and then the mean value and the standard deviation are calculated. In order to compare the algorithms performance it is very common to use statistical hypothesis tests. In this paper, we propose a novel alternative method based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to support the performance comparisons. In this case, the alternatives are the algorithms and the criteria are the benchmarks. Since the standard TOPSIS is not able to handle the stochastic nature of evolutionary algorithms, we apply the Hellinger-TOPSIS, which uses the Hellinger distance, for algorithm comparisons. Case studies are used to illustrate the method for evolutionary algorithms but the approach is general. The simulation results show the feasibility of the Hellinger-TOPSIS to find out the ranking of algorithms under evaluation.

---

Graphical abstract

Keywords

• Algorithms comparison, TOPSIS, Hellinger TOPSIS, Hellinger distance