A model simplification approach was followed, starting with a beyond optimal model, which included fixed effects and interactions considered to be of potential significance in the optimal model (Zuur et al. 2009).
A model simplification approach is presented, allowing the reduction of computational times and the investigation of multiple Pareto-optimal solutions with a multiobjective genetic algorithm.
In the present study, a molecular simplification approach was employed to design novel bicyclic pyrazolo[3,4-d]pyrimidine (PP) derivatives from tricyclic pyrazolo[4,3-e]-1,2,4-triazolo-[1,5-c]pyrimidines (PTP) as promising human A3 adenosine receptor (hA3AR) antagonists.
Models were compared using a model simplification approach based on the removal of the least significant terms, using Wald statistics, until only significant terms remained.
Therefore, a new kind of simplification approach based on geometrical parametric study is suggested in this paper.
Given a point-based 3D model which is defined by a point set P (P= {pa∈R3}) and a desired reduced number of output samples ns, the simplification approach finds a point set Ps which (i) satisfies |Ps|= ns (|Ps| being the cardinality of Ps) and (ii) minimizes the difference of the corresponding surface Ss (defined by Ps) and the original surface S (defined by P).
Depending on the lead structure's size and on its degree of complexity, the strategy may involve a simplification (disjunctive approach), conservation of the same level of complexity (analogical approach), or enlargement through additional elements (conjunctive approach).
In addition, an application example of the proposed simplification approach for structural health monitoring in a hollow sphere structure is provided.
The relationship between climatic variables and survival and/or recapture parameters was tested using a capture-recapture model selection and simplification approach [5].
Because of the number of higher-order interactions with five main effects, we applied a modified version [37] of the typical model simplification approach, in which one starts with the full model and removes least significant highest-order terms (e.g., the five-way interaction) singly in a stepwise manner [38].
