The scaling equation is the most popular mathematical modeling of asphaltene precipitation as a problematic issue in petroleum industry. There are eight adjustable coefficients in the scaling equation that govern the ...
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The scaling equation is the most popular mathematical modeling of asphaltene precipitation as a problematic issue in petroleum industry. There are eight adjustable coefficients in the scaling equation that govern the quality of the fit between titration data and the scaling equation model. In this study, a hybrid genetic algorithm-pattern search (GA-PS) tool was employed to extract optimal values of the involved coefficients in the scaling equation through the stochastic search. For better performance of the GA-PS tool, dimensionality of the problem was broken into two simpler parts using the divide-and-conquer principle by introducing two fitness functions. The renovated scaling equation was compared with previous works;it was shown that the proposed method outperforms previous works.
The divide-and-conquer principle is a technique to obtain solutions for a large-scale problem by dividing it into smaller and manageable subproblems and by integrating these subsolutions. In engineering design, the pr...
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ISBN:
(纸本)9781904670223
The divide-and-conquer principle is a technique to obtain solutions for a large-scale problem by dividing it into smaller and manageable subproblems and by integrating these subsolutions. In engineering design, the principle is often used not just as a complexity management method but also as an embodiment method, although its formalization is unclear if not non-existing. This paper attempts to formalize the principle in the context of design of complex multi-disciplinary systems such as mechatronics systems. It proposes a theory of decomposition in conceptual design (system architecting), which extends the decomposition theory in traditional engineering design based on functional decomposition. The theory is applicable to system decomposition processes, in which building blocks necessary for decomposition are not available or must be newly designed during the processes. The theory uses parameter relations governed by physical phenomena realizing functions. A case study of system architecting of a printer is illustrated as a demonstration of the theory.
In this paper, a new neural-network model called GROUPSTRON is, proposed to identify the k groups' elements from a data set. Based on both the divide-and-conquer principle and the coarse-and-fine competition, GROU...
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In this paper, a new neural-network model called GROUPSTRON is, proposed to identify the k groups' elements from a data set. Based on both the divide-and-conquer principle and the coarse-and-fine competition, GROUPSTRON divides the identification process into k rounds and then sequentially identifies each group's elements from the data set. All the elements in the first group are larger than those, in the second group and this relationship holds for the successive groups. The proof that GROUPSTRON converges to the correct state in every situation is also given in this paper. Moreover, the convergence rates of GROUPSTRON for three special data distributions are deduced. Finally, simulation results are given to demonstrate the effectiveness and design philosophy of GROUPSTRON.
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