Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model

Ahmad, Iftikhar; Raja, Muhammad Asif Zahoor; Bilal, Muhammad; Ashraf, Farooq

doi:10.1007/s00521-016-2400-y

Cited by 112 publications

(37 citation statements)

References 64 publications

(55 reference statements)

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“…In future, such techniques of FC can be implemented to all variants of PSO [21,58] and other hybrid algorithms to enhance the memory effect and convergence rate. The designed FPSOGSA looks further promising to be exploited/explored for finding the solution of stiff/non-stiff nonlinear models arising in broad application of applied science and technology such as intelligent systems, electromagnetism, electronics, modeling and identification, telecommunications, irreversibility, physics, control systems [38][39][40][41], fluid dynamics [61][62], astrophysics models [63][64], differential equation based electric circuit theory [65][66], bioinformatics studies [67][68] and atomic physics models [69][70].…”

Section: Discussionmentioning

confidence: 99%

Design of Fractional Particle Swarm Optimization Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problems

et al. 2020

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In fact, optimal RPD is one of the most critical optimization matters related to electrical power stability and operation. The minimization of overall real power losses is obtained by adjusting the power systems control variables, for instance; generator voltage, compensated reactive power and tap changing of the transformer. In this search, a new heuristic computing method named as fractional particle swarm optimization gravitational search algorithm (FPSOGSA) is presented by introducing fractional derivative of velocity term in standard optimization mechanism. The designed FPSOGSA is implemented for the optimal RPD problems with IEEE-30 and IEEE-57 standards by attaining the near finest outcome sets of control variables along with minimization of two fitness objectives; active power transmission line losses (Ploss, MW) and voltage deviation (VD). The superior performance of the proposed FPSOGSA is verified for both single and multiple runs through comparative study with state of art counterparts for each scenario of optimal RPD problems.

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Section: Discussionmentioning

confidence: 99%

Design of Fractional Particle Swarm Optimization Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problems

et al. 2020

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“…Using contact geometry, we have immediately obtained a "Hamiltonisation" of all the dynamical systems of the form (1). This fact should not be underestimated: a Hamiltonian structure for all such systems allows us to benefit from the theory of Hamiltonian systems (extended to the contact case) and its powerful analytical and numerical tools.…”

Section: Contact Hamiltonian Systemsmentioning

confidence: 97%

Numerical integration in Celestial Mechanics: a case for contact geometry

Bravetti

Seri

Vermeeren

et al. 2020

Celest Mech Dyn Astr

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Several dynamical systems of interest in celestial mechanics can be written in the formqFor instance, the modified Kepler problem, the spin-orbit model and the Lane-Emden equation all belong to this class. In this work we start an investigation of these models from the point of view of contact geometry. In particular we focus on the (contact) Hamiltonisation of these models and on the construction of the corresponding geometric integrators.

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“…They are utilized in recognition/generation/ classification. They have permanent I/P's and O/P's Ahmad et al (2017).…”

Section: B Feed Forward Annmentioning

confidence: 99%

Location-Aware Mobile Cloud using Artificial Intelligence

Vishal*¹,

Kaur²,

Jangra³

2019

IJITEE

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Mobile cloud computing is a rapidly evolving technology these days and it faces major problems of load imbalance due to the high demand for mobile applications. There are many techniques to solve the problem, but the user can improve load by using a more optimized solution. This research deals with the VM allocation and migration by means of location awareness. The research paper also presents a user authentication and server load management system to reduce the overload of the server. A captcha based authentication mechanism is also presented for user verification. The concept of Feedback is also introduced for the mobile servers. This concept makes the selection of mobile server for the job list. ANN (Artificial neural network) is used for location awareness judgment. ANN is a machine learning approach, which is used to minimize the human effort and also minimize the processing time to allocate job to an accurate server with minimum SLA violation. MBFD (Mobile best fit decreasing) algorithm is used for the VM allocation and selection policy. This research has considered SLA (Service level agreement) violation and energy consumption to compute the performance of the work with an aim of reducing energy consumption with maximized resource efficiency. The proposed work model is also compared with the work presented by Xiong in the same area.

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Neural network methods to solve the Lane–Emden type equations arising in thermodynamic studies of the spherical gas cloud model

Cited by 112 publications

References 64 publications

Design of Fractional Particle Swarm Optimization Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problems

Design of Fractional Particle Swarm Optimization Gravitational Search Algorithm for Optimal Reactive Power Dispatch Problems

Numerical integration in Celestial Mechanics: a case for contact geometry

Location-Aware Mobile Cloud using Artificial Intelligence

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