Computational modeling is the use of computers to simulate and study complex systems using mathematics physics and computer science. A Computational model contains numerous variables that characterize the system being studied. Simulation is done by adjusting the variable alone or in combination and observing the outcomes. Computer modeling allows scientists to conduct thousands of simulated experiments by computer. The thousands of computer experiments identify the handful of laboratory experiments that are most likely to solve the problem being studied. Computational modelling uses computers to understand and study the behavior of complex systems. This process encompasses subjects such as mathematics, physics and computer science. The goal of computational modeling in behavioral science is to use precise mathematical models to make better sense of behavioral data. The behavioral data most often come in the form of choices, but can also be reaction times, or other easily observable behaviors, and even neural data. The models come in the form of mathematical equations that link the experimentally observable variables (e.g. stimuli, outcomes, past experiences) to behavior in the immediate future. In this sense, computational models instantiate different ‘algorithmic hypotheses’ about how behavior is generated. The book is structured to help readers understand the logic of individual component techniques and their relationships to each other.
Contents: 1. Current Modeling Methods, 2. Mathematical Modeling, 3. Computational Methods, 4. Computer Simulation, 5 Computer industry, 6. Computation of Determinant, 7. Computational Fluid Dynamics, 8. Digital Computer system, 9. Computational Proteomics, 10. Quantum Nano Computation.