Given the large model size, it is important to determine a suitable number of autoregressive lags and which time-lagged values to include in the model.
A PCA model which incorporates time lagged variables is used, and the control objective is expressed in the score space of this PCA model.
The ordinary and helical piles movement is happened after soil surface movement which represents time lag relation and more than 80% took place during period (20 30) days of saturation.
The main experimental trends, which are pronounced time lags between CO2, (CO)a and CH4, could be described satisfactorily.
Inequalities in coverage of health interventions decreased between 1997 and 2006, which due to time lags of effects of certain interventions, such as immunization, on health outcomes may result in reduced inequalities in infant and U5MR in subsequent surveys.
The prototype system was evaluated in the case of earthquake prediction studies where the asynchronous visualization of independent observations could allow a timely identification of the spatial correlations appearing at different time lags, which could be missed using other existing 4D Geographic Information System software.
R&D process is characterized by time lags which mean that inputs do not result in immediate increase in outputs (Sharma and Thomas 2008).
Patients receiving radiotherapy as first adjuvant treatment also experienced longer wait times in nearly all intervals, which could partly reflect time lags associated with the planning of radiotherapy and/or prolonged referral-medical oncology consult.
It consists of a hybrid model composed of a modular morphological neural network (MMNN) combined with a particle swarm optimizer (PSO), which searches for the best time lags to optimally describe the time series phenomenon, as well as estimates the initial (sub-optimal) parameters of the MMNN (weights, architecture and number of modules).
It is inspired on Takens Theorem and consists of an intelligent hybrid model composed of a Modular Morphological Neural Network (MMNN) combined with a Modified Genetic Algorithm (MGA), which searches for the particular time lags capable of a fine tuned characterization of the time series and estimates the initial (sub-optimal) parameters (weights, architecture and number of modules) of the MMNN.
