Sentence examples for multiple genetic programming from inspiring English sources

One is our newly introduced multiple genetic programming (MGP) and the other is statistical multivariate analysis including principal component analysis and multivariate regression.

That such a system exists is evidenced by recent experiments that identify QS-dependent alterations of multiple genetic programs, epithelial cells, and immune effector cells in patients [ 6].

The majority of cells in an adult organism primarily exist in a quiescent state that is actively maintained by multiple genetic programs [ 1- 3].

Although this does not exclude the possibility that the s-LNvs are still present, it nevertheless implies that at least multiple genetic programs are severely impaired in the s-LNvs.

The grouping of regulons with information-related, stress response, and plastid-related functions in dense regions of the transcriptional network indicates that genes in these dense regions may participate in multiple related genetic programs that under some subsets of conditions are coexpressed.

Performance of the GEP-GA was compared to that of classic genetic programming (GP), GEP, multiple linear regression and GEP-linear regression models developed in the present study as the benchmarks.

In this paper, a hybrid genetic programming (GP) with multiple genes is implemented for developing prediction models of spectral energy demands.

The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively.

A multi-objective genetic programming (MOGP) technique with multiple genes is proposed to formulate the energy performance of residential buildings.

A Genetic Programming (GP) method uses multiple runs, data decomposition stages, to evolve a hierarchical set of vehicle detectors for the automated inspection of infrared line scan imagery that has been obtained by a low flying aircraft.

Equation models based on a genetic programming (GP) algorithm and multiple linear regression (MLR) were used for predicting the temporal dynamics and magnitude of blooms.