Use of Genetic Programming for the Estimation of CODLAG Propulsion System Parameters

Abstract

In this paper, the publicly available dataset for the Combined Diesel-Electric and Gas (CODLAG) propulsion system was used to obtain symbolic expressions for estimation of fuel flow, ship speed, starboard propeller torque, port propeller torque, and total propeller torque using genetic programming (GP) algorithm. The dataset consists of 11,934 samples that were divided into training and testing portions in an 80:20 ratio. The training portion of the dataset which consisted of 9548 samples was used to train the GP algorithm to obtain symbolic expressions for estimation of fuel flow, ship speed, starboard propeller, port propeller, and total propeller torque, respectively. After the symbolic expressions were obtained the testing portion of the dataset which consisted of 2386 samples was used to measure estimation performance in terms of coefficient of correlation (R2) and Mean Absolute Error (MAE) metric, respectively. Based on the estimation performance in each case three best symbolic expressions were selected with and without decay state coefficients. From the conducted investigation, the highest R2 and lowest MAE values were achieved with symbolic expressions for the estimation of fuel flow, ship speed, starboard propeller torque, port propeller torque, and total propeller torque without decay state coefficients while symbolic expressions with decay state coefficients have slightly lower estimation performance.

The Change in Low Power Steam Turbine Operating Parameters During Extractions Opening/Closing

“…Further investigation of this low-power steam turbine will be based on steam turbine optimization by using various artificial intelligence methods and techniques such as neural networks [67][68][69], genetic programming [70] or various optimization algorithms [71]. The main aim will be to increase turbine power and (if possible) simultaneously decrease fuel consumption in the steam generator.…”

Marine Power Systems

“…An delić et al [2] collected the publicly available dataset for the Combined Diesel-Electric and Gas (CODLAG) propulsion system, which was used to obtain symbolic expressions for estimation of fuel flow, ship speed, starboard propeller torque, port propeller torque, and total propeller torque using genetic programming (GP) algorithm. The dataset consists of 11,934 samples that were divided into training and testing portions in an 80:20 ratio.…”

“…Although maritime transport is pointed to as an energy-efficient mode of transportation, its emission of GHGs is still high despite new technologies that have been adopted [1]. Optimization and the use of new fuels with new technologies for power generation of such systems are always tasks that are necessary in order to improve efficiency of the power generation system and to reduce GHG emissions [2][3][4][5][6].…”

Thermodynamic Analysis and Improvement Potential of Helium Closed Cycle Gas Turbine Power Plant at Four Loads

“…The high combustion gas temperature at the gas turbine power plant outlet allows heat utilization and efficiency increases for the entire system in which they operate [6,7]. In marine propulsion, gas turbine power plants can be found inside many complex systems [8,9], but due to their high costs, they are rarely found as independent propulsion elements [10]. Gas turbine power plants are also the base elements of aircraft jet engines, regardless of jet engine type (turbojet, turbofan, turboshaft, or turboprop) [11][12][13][14][15][16].…”