Acquisition Geometry Optimisation - Using a Low-Rank Parameterisation and a Genetic Algorithm

Author(s):  
S. Wu ◽  
E. Verschuur ◽  
G. Blaquière
ChemPhysChem ◽  
2002 ◽  
Vol 3 (5) ◽  
pp. 408 ◽  
Author(s):  
Lesley D. Lloyd ◽  
Roy L. Johnston ◽  
Christopher Roberts ◽  
Thomas V. Mortimer-Jones

2018 ◽  
Vol 12 (3) ◽  
pp. 431-438 ◽  
Author(s):  
Mircea Ruba ◽  
Florin Jurca ◽  
Levente Czumbil ◽  
Dan D. Micu ◽  
Claudia Martis ◽  
...  

Author(s):  
Diyajeng Luluk Karlina ◽  
Ilham Bintang

Coal that is often used in Steam Power Plants is a type of Low Rank Coal (Low Rank Coal) which has a caloric value of 4200 kcal / kg with a moisture content of 40%.  Coal with water content that reaches 40% can cause the efficiency process of the plant to be not optimal. Low efficiency values will cause the use of electricity to increase and the combustion process to be incomplete so that it can cause many losses to the Steam Power Plant. From this problem, there needs to be a process of drying coal in order to reduce water content, the technology used in the process of drying coal is coal dryer. Design of coal dryer required source of steam or heat for drying process. Steam Power Plant there is steam waste extraction from turbines that can be used as a heat source to heat coal. If this extraction vapor is utilized, it can reduce the load from the condenser. The amount of turbine extraction steam that can be received by the coal dryer depends on the design of the coal dryer, because the design process of the coal dryer will affect the availability of energy in the coal dryer. This paper will discuss about optimization calculation with genetic algorithm method, to obtain the best design of coal dryer so that the heat received can be maximized so that the drying process becomes faster.


1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan

Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.


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