The paper presents the application of the newly developed method of the solution of nonlinear equations to the adaptive modelling and computer simulation. The approach is suitable when the system of equations can be arranged in such a way that it consists of a large number of linear equations and a smaller number of nonlinear equations. This situation occurs in the case of adaptive modelling of mechanical systems using finite elements or finite differences techniques. In this case the classical least square method becomes very effective. The paper presents several examples of the application of the method. A solution to the, so called, “black box” problem is also presented.
The focus of this paper is to propose a method for prioritizing knowledge and technology
factor in companies’ business strategy. The data has been gathered and analyzed from
Malaysian-owned company of medium size type industry, employing around 250 employees
and listed in the Malaysian Bourse Stock of Exchange, since 2000. Sense and respond model
is used to determine competitive priorities of the firms. Then knowledge and technology
part of sense and respond questionnaire is used to calculate the variability coefficient i.e. the
uncertainty caused by technology and knowledge factor. The results show that the company
is not leading in term of technology (spear head technology share is around 33%). Therefore,
the enhancement of technology and knowledge to SCA values is not significantly seen in
this study. The usage of the core technologies is around 41% and it might seem relatively
enough. In terms of basic technology, while its share is the lowest (around 25%), it has the
highest source of uncertainties among technology types. In this case, the proposed model
helped to have a clear and precise improvement plan towards prioritizing technology and
knowledge focus.