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In simple terms, value-added models use mathematical formulas to predict how a group of students will do on each year's tests based on their scores from the previous year, while accounting for factors that include race, gender, income level and other test results.
Some of the forecasting models use mathematical formulas and statistical models such as correlation and regression models.
Process-based growth models use mathematical representations of biotic and abiotic processes to simulate components of both the water and carbon balances.
These models use mathematical expressions ranging from simple analytical expressions to complex mathematical systems written with ordinary differential equations.
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Elsewhere in psychology, logic is employed mostly as an ingredient of various models using mathematical ideas or ideas drawn from such areas as automata or information theory.
Many phenomena in engineering physics, chemistry, and other sciences can be described very successfully by models using mathematical tools.
The methods include building and solving optimization models using mathematical programming, optimization with stochastic search and using P-graph for designing water networks.
In recent years, the fractional calculus used in many phenomena in engineering, physics, biology, fluid mechanics, and other sciences [1, 2, 3, 4, 5, 6, 7, 8] can be described very successfully by models using mathematical tools from fractional calculus.
The model uses mathematical programming to solve the problem.
Constructed wetland hydrodynamics were modeled using mathematical tools generally employed in chemical engineering processes.
This method mainly involves a decomposition scheme that facilitates complex reliability models to the simplified sub-models using mathematical functions (Ebeling 1997; Xu and Rahman 2005).
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