Determination of MRCP Evocation Model and Its Parameters

2000 ◽  
Vol 12 (6) ◽  
pp. 725-730
Author(s):  
Hisaya Tanaka ◽  
◽  
Ayako Shinokubo ◽  
Hideto Ide
Keyword(s):  
Genetic Algorithms ◽  
Optimum Parameter ◽  
Evoked Potential ◽  
Cortical Potential ◽  
Optimum Parameters

We examined optimum parameters of the charging model and the underdamping model. Those models have represented the evoked potential of MRCP Each parameter has been determined with GAs (Genetic Algorithms). Comparison has been made between the experimental waveform and the theoretical waveform structuring those models, based on the optimum parameter. We have also examined the mechanism of MRCP (Movement-related brain cortical potential).

Determination of Optimum Parameters for Anaerobic Thermophilic Bacterium Injection using Commercial Simulator: Core Flooding Validation and Sensitivity

2020 ◽  
Author(s):  
A. Koto
Keyword(s):  
Oil Recovery ◽  
Simulation Experiment ◽  
Previous Experiment ◽  
Core Sample ◽  
Thermophilic Bacterium ◽  
Injection Rate ◽  
Core Flooding ◽  
Optimum Parameters ◽  
Result Show

The objective of this paper is to determine the optimum anaerobic-thermophilic bacterium injection (Microbial Enhanced Oil Recovery) parameters using commercial simulator from core flooding experiments. From the previous experiment in the laboratory, Petrotoga sp AR80 microbe and yeast extract has been injected into core sample. The result show that the experiment with the treated microbe flooding has produced more oil than the experiment that treated by brine flooding. Moreover, this microbe classified into anaerobic thermophilic bacterium due to its ability to live in 80 degC and without oxygen. So, to find the optimum parameter that affect this microbe, the simulation experiment has been conducted. The simulator that is used is CMG – STAR 2015.10. There are five scenarios that have been made to forecast the performance of microbial flooding. Each of this scenario focus on the injection rate and shut in periods. In terms of the result, the best scenario on this research can yield an oil recovery up to 55.7%.

A novel method for the evaluation of the contamination dispersing ability of lubricants (CONTA-DISP)

2021 ◽  
Vol 68 (3-4) ◽  
pp. 22-28
Author(s):  
Bettina Ronai ◽  
Rainer Franz ◽  
Marcella Frauscher
Keyword(s):  
Lubricating Oils ◽  
Practical Procedure ◽  
Particulate Contamination ◽  
Optimum Parameters ◽  
Analysis Methods ◽  
Lubricant Analysis ◽  
Novel Method ◽  
Dispersing Ability

Water and solid particulate contamination are the two most common contaminants of lubricated systems and may be highly problematic for these systems. To reduce downtime and prevent failure, lubricant formulations contain detergent and dispersant additives that play an important role in terms of contamination tolerance. In lack of a practical procedure for the determination of the relevant properties, a novel method for the evaluation of the dispersing ability of lubricating oils is introduced. Following and combining established lubricant analysis methods, a procedure with optimum parameters was found. An assessment of the method using fresh and artificially altered lubricating oils allowed a differentiation concerning their dispersing ability.

scholarly journals Lecture Scheduling Automation Using Genetic Algorithm

2019 ◽  
Vol 8 (5C) ◽  
pp. 1444-1447
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Test Results ◽  
Scheduling Problems ◽  
Scheduling System ◽  
Parameter Values

This paper aims produce an academic scheduling system using Genetic Algorithm (GA) to solve the academic schedule. Factors to consider in academic scheduling are the lecture to be held, the available room, the lecturers and the time of the lecturer, the suitability of the credits with the time of the lecture, and perhaps also the time of Friday prayers, and so forth. Genetic Algorithms can provide the best solution for some solutions in dealing with scheduling problems. Based on the test results, the resulting system can automate the scheduling of lectures properly. Determination of parameter values in Genetic Algorithm also gives effect in producing the solution of lecture schedule

scholarly journals A GENETIC BASED TECHNIQUE FOR THE DETERMINATION OF POWER SYSTEM TOPOLOGICAL OBSERVABILITY

2014 ◽  
pp. 16-21
Author(s):  
S. Vazquez-Rodriguez ◽  
R. J. Duro
Keyword(s):  
Genetic Algorithms ◽  
Power Systems ◽  
Power System ◽  
Spanning Tree ◽  
Point Of View ◽  
Genetic Operators ◽  
Building Process ◽  
Phenotype Transformation

In this paper we have addressed the problem of observability of power systems from the point of view of topological observability and using genetic algorithms for its determination. The objective is to find a way to determine if a system is observable by establishing if a spanning tree of the system that verifies certain properties with regards to the use of available measurements can be obtained. To this end we have developed a genotype-phenotype transformation scheme for genetic algorithms that permits using very simple genetic operators over integer based chromosomes which after a building process can become very complex trees. The procedure was successfully applied to standard benchmark systems and we present some results for one of them.

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