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The ability of a real-time optimization (RTO) system to track the changing optimum closely relies on an accurate model for representing the plant behavior.
In the present study, the fuzzy logic model was developed to predict the compressive strength of the asphalt specimens in different scenarios including changing optimum bitumen percentage, adding granular polymer-modified bitumen, and using different percentages of fractured particles.
They proposed to alter the optimum tilt angle twelve times annually in which the output was quantitatively comparable to the daily changing optimum tilt angle.
Where the Lynch and Lande model assumes a population will survive as long as it can keep pace with the changing optimum, Bürger and Lynch (1995) examined how the fitness loss due to the lag in adaptation affects population demography, further increasing the potential for extinction.
In an early attempt to formulate quantitative genetic predictions about extinction risk due to adaptive constraints, Lynch and Lande (1993) examined a model where fitness is determined by a single quantitative trait and the population must adapt to a continuously changing optimum to persist.
It is important to note that equation (1) predicts the maximum possible rate of adaptation, but that low heritability, pleiotropy, environmental stochasticity around the changing optimum, or drift could reduce this prediction considerably (limitations of these types of models are reviewed more thoroughly in Bürger and Krall (2004)).
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If this is the case, allele frequency adjustments within the loci described here, coupled with realistic migration rates and epistasis, may provide the means for tree populations to track the rapidly changing phenotypic optimums imposed by climate change.
Consequently, the population shadows the moving optimum, changing at a corresponding rate k per generation but lagging behind the current optimum by a quantity k/ R (Charlesworth 1993; Lynch and Lande 1993).
The presence of the optimum changing rate of solvent quality for inter-molecular associations is suggested.
Operations optimization seeks to track a changing true plant optimum by maximizing a model-based calculated profit in closed-loop real-time optimization (RTO).
The experiment was repeated with all factors kept at optimum changing except the factor under study, till the optimal conditions are achieved (Robbins [1984]).
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