the objectives of this study were to identify a suitable mathematical model for describing the growth curve of baluchi sheep based on monthly records of live weight from birth to yearling; and to evaluate the efficacies of nonlinear mixed effect model (nlmm) and the nonlinear fixed effect model (nlm) methodologies. growth models were fitted to a total of 16,650 weight–age data belonging to 2071...

capital asset pricing model (capm) has been among the common models to estimate expected returns rate. since the linearity assumption is considered in the standard version of the capital asset pricing model, estimating beta in nonlinear setting will be inconsistent and bias-oriented. therefore, this study tries to evaluate predictive power of nonlinear capital asset pricing model as well as sta...

The origin of the summertime synoptic wave train in the western North Pacific is investigated with a multilevel, nonlinear baroclinic model. A realistic three-dimensional summer mean state is specified and eigenvectors are calculated by introducing small perturbation initially to the model. Numerical experiments indicate that the origin of the synoptic wave train may arise from instability of t...

There have been many recent articles on the coding properties of nerve cells, with emphasis on the precision and reliability of the processes involved 1−7. In our investigations of stochastic effects in nonlinear biological neuron models , we have examined especially some results obtained on the firing properties of certain neocortical cells 3 in which various currents were injected repetitivel...

The train scheduling problem with the origin-destination (O-D) dependent passenger demands is considered for urban rail transit systems. In this paper, trains are allowed to skip any intermediate stations (except the origin station and the final station) to reduce the passenger travel time and to save energy consumption. A model of train movements with stop-skipping and the O-D dependent passen...

Nonlinear system behavior is not always well characterized by linearized system models, especially if the system is chaotic. This research studies the use of a neural network algorithm structure to model two nonlinear systems, a quadratic system and a chaotic system. An evolutionary programming approach is employed to train the neural nets so that the training process might better avoid selecti...