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Articles 1 - 7 of 7
Full-Text Articles in Control Theory
Modularity And Boolean Network Decomposition, Matthew Wheeler
Modularity And Boolean Network Decomposition, Matthew Wheeler
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Optimal Intervention Strategies To Minimize Spread Of Infectious Diseases And Economic Impact On A Dynamic Small-World Network, Malindi Whyte, Danielle Dasilva
Optimal Intervention Strategies To Minimize Spread Of Infectious Diseases And Economic Impact On A Dynamic Small-World Network, Malindi Whyte, Danielle Dasilva
Biology and Medicine Through Mathematics Conference
No abstract provided.
De-Coupling Cell-Autonomous And Non-Cell-Autonomous Fitness Effects Allows Solution Of The Fokker-Planck Equation For The Evolution Of Interacting Populations, Steph J. Owen
Biology and Medicine Through Mathematics Conference
No abstract provided.
A Novel Chebyshev Wavelet Method For Solving Fractional-Order Optimal Control Problems, Ghodsieh Ghanbari
A Novel Chebyshev Wavelet Method For Solving Fractional-Order Optimal Control Problems, Ghodsieh Ghanbari
Theses and Dissertations
This thesis presents a numerical approach based on generalized fractional-order Chebyshev wavelets for solving fractional-order optimal control problems. The exact value of the Riemann– Liouville fractional integral operator of the generalized fractional-order Chebyshev wavelets is computed by applying the regularized beta function. We apply the given wavelets, the exact formula, and the collocation method to transform the studied problem into a new optimization problem. The convergence analysis of the proposed method is provided. The present method is extended for solving fractional-order, distributed-order, and variable-order optimal control problems. Illustrative examples are considered to show the advantage of this method in comparison …
Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack
Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack
Honors College Theses
Various techniques are used to create predictions based on count data. This type of data takes the form of a non-negative integers such as the number of claims an insurance policy holder may make. These predictions can allow people to prepare for likely outcomes. Thus, it is important to know how accurate the predictions are. Traditional statistical approaches for predicting count data include Poisson regression as well as negative binomial regression. Both methods also have a zero-inflated version that can be used when the data has an overabundance of zeros. Another procedure is to use computer algorithms, also known as …
Vertical Take-Off And Landing Control Via Dual-Quaternions And Sliding Mode, Joshua Sonderegger
Vertical Take-Off And Landing Control Via Dual-Quaternions And Sliding Mode, Joshua Sonderegger
Doctoral Dissertations and Master's Theses
The landing and reusability of space vehicles is one of the driving forces into renewed interest in space utilization. For missions to planetary surfaces, this soft landing has been most commonly accomplished with parachutes. However, in spite of their simplicity, they are susceptible to parachute drift. This parachute drift makes it very difficult to predict where the vehicle will land, especially in a dense and windy atmosphere such as Earth. Instead, recent focus has been put into developing a powered landing through gimbaled thrust. This gimbaled thrust output is dependent on robust path planning and controls algorithms. Being able to …
An Integrated Computational Pipeline To Construct Patient-Specific Cancer Models, Daniel Plaugher
An Integrated Computational Pipeline To Construct Patient-Specific Cancer Models, Daniel Plaugher
Theses and Dissertations--Mathematics
Precision oncology largely involves tumor genomics to guide therapy protocols. Yet, it is well known that many commonly mutated genes cannot be easily targeted. Even when genes can be targeted, resistance to therapy is quite common. A rising field with promising results is that of mathematical biology, where in silico models are often used for the discovery of general principles and novel hypotheses that can guide the development of new treatments. A major goal is that eventually in silico models will accurately predict clinically relevant endpoints and find optimal control interventions to stop (or reverse) disease progression. Thus, it is …