The purpose of this paper is to employ an alternative approach to reconstruct the standard variational iteration algorithm II proposed by He, including Lagrange multiplier, and to give a simpler formulation of Adomian decomposition and modified Adomian decomposition method in terms of newly proposed variational iteration method-II (VIM). Through careful investigation of the earlier variational ...

Configuration was one of the first tasks successfully approached via AI techniques. However, solving configuration problems can be computationally expensive. In this work, we show that the decomposition of a configuration problem into a set of simpler and mutually independent subproblems can decrease the computational cost of solving it. In particular, we describe a decomposition technique expl...

We show that a cooperative game may be decomposed into a sum of component games, one for each player, using the combinatorial Hodge decomposition on a graph. This decomposition is shown to satisfy certain efficiency, null-player, symmetry, and linearity properties. Consequently, we obtain a new characterization of the classical Shapley value as the value of the grand coalition in each player’s ...

A numerical method is proposed to solve the full-Eulerian time-dependent Vlasov-Poisson system in high dimension. The algorithm relies on the construction of a tensor decomposition of the solution whose rank is adapted at each time step. This decomposition is obtained through the use of an efficient modified Progressive Generalized Decomposition (PGD) method, whose convergence is proved. We sug...

A crucial issue in parallel programming (both for distributed and shared memory architectures) is work decomposition. Work decomposition task can be accomplished without large programming effort with use of high-level parallel programming languages, such as OpenMP. Anyway particular care must still be payed on achieving performance goals. In this paper we introduce and compare two decomposition...

Images decomposition attracts much attention in recent years. Many variational methods were proposed. The most famous variational decomposition model is OSV model because of its concise expression. However, the OSV model suffers from many drawbacks. One is that the discretization of the EularLagrange equation is hard because the 4th order term was introduced. The other drawback is that the effe...

To solve task decomposition of multi-expert system, agent-based task decomposition model and algorithm based on dependency is introduced. Firstly, AND/OR dependency graph for operation set is presented. Formal description of task decomposition based on With AND/OR dependency graph, is proposed. Secondly, task decomposition algorithm based on operation dependency is analyzed to solve communicati...

The particle size control of drug is one of the most important factors affecting the efficiency of the nano-drug production in confined liquid impinging jets. In the present research, for this investigation the confined liquid impinging jet was used to produce nanoparticles of Carbamazepine. The effects of several parameters such as concentration, solution and anti-solvent flow rate and solvent...

In this paper, the Adomian decomposition method with Green’s function (Standard Adomian and Modified Technique) is applied to solve linear and nonlinear tenth-order boundary value problems with boundary conditions defined at any order derivatives. The numerical results obtained with a small amount of computation are compared with the exact solutions to show the efficiency of the method. The res...

In this paper, the modified Adomian s decomposition method for calculating a numerical solution of the one-dimensional quasi-linear, the Burgers equation, is presented. Time discretization has been used in decomposition, without using any transformation in the Burgers equation such as Hopf–Cole transformation. The numerical results obtained by this way for various values of viscosity have been ...