Application of NARX neural network for predicting marine engine performance parameters

Application of Artificial Neural Network and Genetic Algorithm for Predicting three Important Parameters in Bakery Industries

Farinograph is the most frequently used equipment for empirical rheological measurements of dough. It’suseful to illustrate quality of flour, behavior of dough during mechanical handling and texturalcharacteristics of finished products. The percentage of water absorption and the development time of doughare the most important parameters of farinography for bakery industries during production. H...

Application of artificial neural network for prediction of marine diesel engine performance

application of artificial neural network and genetic algorithm for predicting three important parameters in bakery industries

farinograph is the most frequently used equipment for empirical rheological measurements of dough. it’suseful to illustrate quality of flour, behavior of dough during mechanical handling and texturalcharacteristics of finished products. the percentage of water absorption and the development time of doughare the most important parameters of farinography for bakery industries during production. h...

Artificial Neural Network Model for Predicting Insurance Insolvency

In addition to its primary role of providing financial protection for other industries the insurance industry also serves as a medium for fund mobilization. In spite of the harsh economic environment in Nigeria, the insurance industry has been crucial to the consummation of business plans and wealth creation.  However, the continued downturn experienced by many countries, in the last decade, se...

A Method for Pre-Calibration of DI Diesel Engine Emissions and Performance Using Neural Network and Multi-Objective Genetic Algorithm

Diesel engine emission standards are being more stringent as it gains more publicity in industry and transportation. Hence, designers have to suggest new controlling strategies which result in small amounts of emissions and a reasonable fuel economy. To achieve such a target, multi-objective optimization methodology is a good approach inasmuch as several types of ...