Evaluations of certain Euler type integrals

Khan, Subuhi; Agrawal, Babita; Pathan, M. A.; Mohammad, Fahim

doi:10.1016/j.amc.2006.12.073

Cited by 8 publications

(2 citation statements)

References 9 publications

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“…In recent years, a number of authors have established a list of integral formulas associated with different kinds of special functions (see, for details, [1]- [5], [7]- [12] and the references cited therein). In order to extend the abovementioned literature, we present in this paper a new class of beta-type integral operators associated with the multi-index Mittag-Leffler function and a generating function of two variables.…”

Section: Introductionmentioning

confidence: 99%

Generalized Beta-type integral operators

Ali¹,

Ghayasuddin²,

Paris³

2020

Preprint

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This research note deals with the evaluation of some generalized beta-type integral operators involving the multi-index Mittag-Leffler function E ǫ i ),(ω i ) (z). Further, we derive a new family of beta-type integrals involving the product of a multi-index Mittag-Leffler function and a generating function of two variables. Some concluding remarks regarding our present investigation are briefly discussed in the last section.

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Section: Introductionmentioning

confidence: 99%

Generalized Beta-type integral operators

Ali¹,

Ghayasuddin²,

Paris³

2020

Preprint

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“…Chaos plays the important role in the optimization calculations [10,11]. Chaos has the randomicity and ergodicity, which helps the algorithm get over the local minimum.…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Based on Chaos Optimization

Xiu

Cheng

2010

KEM

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A hybrid genetic algorithm is proposed based on chaos optimization. The optimization process can be divided into two stages every iteration, one is genetic coarse searching and the other is chaos elaborate searching. Genetic algorithm searches the global solutions in the origin space. An elaborate space near the center of superior individuals is divided from the origin space, which is searched by chaos optimization adequately to generate new better superior individuals for genetic operation. The elaborate space can be compressed quickly to accelerate searching rate and enhance the searching efficiency. In this way, the algorithm has global searching ability and fast convergence rate. The simulation results prove that the algorithm can give satisfied results to function optimization problems.

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