Computational modelling
L. Kanagasabai
Abstract
This work presents Amplified Black Hole Algorithm (ABHA) for solving optimal reactive power problem. In the projected approach ABHA, Gravitational Search Algorithm (GSA) is merged with Black Hole Algorithm (BHA). Power loss reduction is the key objective in the proposed work. The gravitational force ...
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This work presents Amplified Black Hole Algorithm (ABHA) for solving optimal reactive power problem. In the projected approach ABHA, Gravitational Search Algorithm (GSA) is merged with Black Hole Algorithm (BHA). Power loss reduction is the key objective in the proposed work. The gravitational force between stars and the progression of stars to the black hole is attuned while explore the solution space. Assumption made that heavy objects are stars in a gravitational system, which become black holes and the exploitation of GSA is enhanced. During the progression of the projected algorithm, the radius of the black hole diminishes and more objects are included, which assist to stop early convergence. To improve the exploration and exploitation, stars gravity information has been utilized. During the progression of the projected algorithm, the radius of the black hole diminishes, and more objects are included, which assist to stop early convergence. Some of the most excellent objects turn out to be the black hole, affect other objects by their sturdy gravity. The other objects are alienated into two groups: Heavy agents and light agents. Proposed ABHA has been tested in standard IEEE 14, 30, 57, 118, 300 bus test systems and simulation results show the projected algorithm reduced the real power loss comprehensively.
Computational modelling
T. Berhane; M. Adam; G. Awgichew; E. Haile
Abstract
In this paper, we aim at developing a model for option pricing to reduce the risks associated with Ethiopian sesame price fluctuations. The White Humera Gondar Sesame Grade 3 (WHGS3) price, which is recorded from 5 November 2010 to 30 March 2018 at Ethiopia Commodity Exchange (ECX) market, is used to ...
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In this paper, we aim at developing a model for option pricing to reduce the risks associated with Ethiopian sesame price fluctuations. The White Humera Gondar Sesame Grade 3 (WHGS3) price, which is recorded from 5 November 2010 to 30 March 2018 at Ethiopia Commodity Exchange (ECX) market, is used to analyze the price fluctuation. The nature of log-returns of the price is asymmetric (positively skewed) and exhibits high kurtosis. We used jump diffusion models for modeling and option pricing of sesame price. The method of maximum likelihood is applied to estimate the parameters of the models. We used the Root Mean Square Error (RMSE) to test the goodness of fitting for the two models to the data. This test indicates that the models fit the data well. The techniques of analytical and Monte Carlo simulation are used to find the call option pricing of WHGS3 sesame price. From the results, we concluded that Double Exponential Jump Diffusion (DEJD) model is more efficient than Merton’s model for modeling and option pricing of this sesame price.
