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Collection's Items (Sorted by Submit Date in Descending order): 101 to 104 of 104
Issue DateTitleAuthor(s)
2005-03Modelling the correlation between cutting and process parameters in high-speed machining of Inconel 718 alloy using an artificial neural networkEzugwu, E. O.; Fadare, D. A.; Bonney, J.; Da Silva, R. B.; Sales, W. F.
2005Machining of nickel-base, Inconel 718, alloy with ceramic tools under finishing conditions with various coolant supply pressuresEzugwu, E. O.; Bonney, J..; Fadare, D. A.; Sales, W. F
2012-01In this work, three models are used to analyze the electric load capacity of a fast growing urban city and to estimate its future consumption. Ikorodu, the case-study location is a highly populated city whose energy demand is continuously increasing. The ultimate focus of this study is to establish a basis for the comparison of different electric load consumption for the existing populace and to provide estimates for the future planning of the city. In this work, three different models have been used to present more accurate load predictions and to enhance proper comparison of results. Among numerous mathematical and scientific models that are applicable to this kind of task, the compound-growth method, the linear model approach and the cubic model have been chosen to enhance diversity in load analysis. The futuristic scheme to be harnessed will fall within the ranges of values obtained from the three different models used in forecasting. This paper concludes with issues pertaining to economics of load utilization as it affects substantive planning.Eneje, I. S; Fadare, D. A.; Simolowo, O. E.; Falana, A.
2012-04Artificial neural network predictive modeling of uncoated carbide tool wear when turning NST 37.2 steelAsafa, T. B.; Fadare, D. A.
Collection's Items (Sorted by Submit Date in Descending order): 101 to 104 of 104