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A wide range of research areas are available on workforce optimisation problem, ranging from lot-sizing consideration (Judice et al. 2004; Ighravwe and Oke 2014) to workforce modelling using artificial intelligence tools such as simulated annealing, genetic algorithms and some defined metrics (Safaei et al. 2008; Ighravwe and Oke 2014; Ighravwe et al. 2015, 2016a, b).
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In this paper, the performance of the fuel cell is modelled using artificial neural networks.
In this paper, the characteristics of an electrostatic separator were modeled using artificial neural network (ANN).
In this work, flux decline during crossflow ultrafiltration of macromolecules with ceramic membranes has been modeled using artificial neural networks.
The microbial biomass and abundance of selected Collembola taxa were modeled using artificial intelligence methods (regression trees).
For sensitivity analysis and optimization abilities, the biosorption experiments have been statistically modeled using artificial neural network (ANN) and central composite design (CCD).
In this study, the design of Pt-Co-Ce/Al2O3 catalyst for the low temperature CO oxidation in hydrogen streams was modeled using artificial neural networks.
The methodology is based on the construction of a surrogate model using artificial neural-networks.
This research adds to the literature of agricultural price forecasting models, using artificial intelligence and nonlinear modeling.
These cost drivers are used to construct two predictive models for estimating the construction cost of water treatment plants models using artificial neural networks.
The purpose of this study was to develop a model, using artificial intelligent methods, for estimating air-demand ratio in venturi weirs.
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