The main objective of this study is the modelling and optimization of an industrial Hydrocracker Unit (HU) by means of Adaptive Neuro Fuzzy Inference System (ANFIS) model. In this case, some data were collected from an industrial hydrocracker plant. Inputs of an ANFIS include flow rate of fresh feed and recycle hydrogen, temperature of reactors, mole percentage of H2 and H2S, feed flow rate and...

Autoregressive models are among the best performing neural density estimators. We describe an approach for increasing the flexibility of an autoregressive model, based on modelling the random numbers that the model uses internally when generating data. By constructing a stack of autoregressive models, each modelling the random numbers of the next model in the stack, we obtain a type of normaliz...

A conceptual model of a system is an explicit description of the behaviour required of the system. Methods for conceptual modelling include entity-relationship (ER) modelling, data flow modelling, Jackson System Development (JSD) and several object-oriented analysis methods. Given the current diversity of modelling methods, it is important for teaching as well as using these methods to know wha...

Flow through a gross pollutant trap (GPT) with fully blocked screens is investigated experimentally and theoretically using computational fluid dynamics (CFD). Due to the wide range of possible flow regimes, an experimental approach is developed which uses a downstream weir arrangement to control the nature of the flow and the variation in free surface height. To determine the overall flow stru...

the main objective of this study is the modelling and optimization of an industrial hydrocracker unit (hu) by means of adaptive neuro fuzzy inference system (anfis) model. in this case, some data were collected from an industrial hydrocracker plant. inputs of an anfis include flow rate of fresh feed and recycle hydrogen, temperature of reactors, mole percentage of h2 and h2s, feed flow rate and...