In this paper, we focus on the Data Envelopment Analysis (DEA)-based model structures have been used in assessing bank branch efficiency. Probing the methodologies of 75 published studies at the branch level since 1985 to early 2015, we found that these models can be divided into four categories: standard basic DEA models, single level and multi-level models, enriched (hybrid) models and specia...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. this study aimed to use the particle swarm optimization (pso) algorithm for automatic calibration of the hec-hms hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

This paper develops a comprehensive framework to address uncertainty about the correct factor model. Asset pricing inferences draw on composite model that integrates over competing models weighted by posterior probabilities. Evidence shows unconditional record near-zero probabilities, while post-earnings announcement drift, quality-minus-junk, and intermediary capital are potent factors in cond...

Quantile factor models (QFM) represent a new class of for high?dimensional panel data. Unlike approximate (AFM), which only extract mean factors, QFM also allow unobserved factors to shift other relevant parts the distributions observables. We propose quantile regression approach, labeled Factor Analysis (QFA), consistently estimate all quantile?dependent and loadings. Their asymptotic are esta...

This paper discusses different important gas permeation models such as “Maxwell”, “Bruggeman”, “Lewis-Neilson”, and “Pal” models to predict “Mixed Matrix Membranes” (MMMs) performance. The main parameter considered and discussed is the permeability of Hydrogen on Carbon Nanotubes (CNTs)-MMM. For evaluation of the theoretical models, experimental data of permeability for H2 were compa...

This paper discusses different important gas permeation models such as “Maxwell”, “Bruggeman”, “Lewis-Neilson”, and “Pal” models to predict “Mixed Matrix Membranes” (MMMs) performance. The main parameter considered and discussed is the permeability of Hydrogen on Carbon Nanotubes (CNTs)-MMM. For evaluation of the theoretical models, experimental data of permeability for H2 were compa...

the lane change maneuver is among the most popular driving behaviors. it is also the basic element of important maneuvers like overtaking maneuver. therefore, it is chosen as the focus of this study and novel multi-input multi-output adaptive neuro-fuzzy inference system models (manfis) are proposed for this behavior. these models are able to simulate and predict the future behavior of a driver...