In this study, optimization based on artificial neural network (ANN) was established to predict the optimal performance parameters of the system, leading to an optimized propulsion system. Optimization related works on propulsion system investigated by researchers are based on specific fuel consumption, emission characteristics, trim and draft optimization using conventional methods amongst others. This creates a gap for a research window in this direction which this work tries to fill by optimizing overall ship propulsion system efficiency using ANN. The models computational development for this research were actualized using ANN tool box in MATLAB. Attention was given to performance parameter that influences the overall performance of the propulsion system. Hence, the overall ship efficiency, η_sp and energy efficiency design index (EEDI) constitute the parameters of interest to be optimized. A comprehensive ANN program code was developed and implemented to create, configure, train and optimize these parameters of interest. Various ANN-based models of a two layered multilayer perceptron (MLP) structure with different configurations were trained and investigated. Results analysis from MATLAB simulation yields η_sp of 0.507398386 and EEDI of 3.490301699 g of CO2/tm. Results show that the MLP configuration of 14-20-7 gives an optimal model for the ANN. The resulting model could predict the optimized performance output of the system with high degree of accuracy with a minimum mean square error (MSE) at 206 epochs. This point gives the lowest MSE performances value of 3.2923e-10 and regression plot between 0.99999 and 1. The percentage parametric optimization of the propulsion system parameters in ANN gives a 2.4% improvement of η_sp and 3.5% improvement of EEDI. These indicate that the use of ANN for parametric optimization of propulsion system is satisfactory

The ever increasing demands for higher thermal efficiency from power plants have resulted to wide range of research in this regard. This work is one of such researches that deal with the performance optimization of a COGAS plant using MATLAB. A mathematical model of the COGAS plant was developed based on thermodynamic analyses and energy balance equations. This was used to develop a program and run in MATLAB environment for analysis and Optimization of the COGAS thermal efficiency. Results show that the program simulation yielded an overall maximum operational thermal efficiency of 69.7% at about 1750K, considering metallurgical limits of the topping cycle turbine components. The resulting model could predict the optimized performance output of the system with high degree of accuracy and reliability. The novelty of this research is essentially in its methodology and will remain invaluable in future works that will focus towards improving the thermal efficiency of power plants.