All Outputs (4)

Uncertainty reduction in reservoir parameters prediction from multiscale data using machine learning in deep offshore reservoirs. (2020)
Thesis
ARIGBE, O.D. 2020. Uncertainty reduction in reservoir parameters prediction from multiscale data using machine learning in deep offshore reservoirs. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

Developing a complete characterization of reservoir properties involved in subsurface multiphase flow is a very challenging task. In most cases, these properties - such as porosity, water saturation, permeability (and their variants), pressure, wetta... Read More about Uncertainty reduction in reservoir parameters prediction from multiscale data using machine learning in deep offshore reservoirs..

Combining search strategies for distributed constraint satisfaction. (2015)
Thesis
MAGAJI, A.S-M. 2015. Combining search strategies for distributed constraint satisfaction. Robert Gordon University, PhD thesis.

Many real-life problems such as distributed meeting scheduling, mobile frequency allocation and resource allocation can be solved using multi-agent paradigms. Distributed constraint satisfaction problems (DisCSPs) is a framework for describing such p... Read More about Combining search strategies for distributed constraint satisfaction..

Hybrid algorithms for distributed constraint satisfaction. (2010)
Thesis
LEE, D.A.J. 2010. Hybrid algorithms for distributed constraint satisfaction.. Robert Gordon University, PhD thesis.

A Distributed Constraint Satisfaction Problem (DisCSP) is a CSP which is divided into several inter-related complex local problems, each assigned to a different agent. Thus, each agent has knowledge of the variables and corresponding domains of its l... Read More about Hybrid algorithms for distributed constraint satisfaction..

Modifying landscapes with penalties in iterative improvement for solving distributed constraint satisfaction problems. (2006)
Thesis
BASHARU, M.B. 2006. Modifying landscapes with penalties in iterative improvement for solving distributed constraint satisfaction problems. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2807293

The recent growth of the internet and distributed computing facilitated by the internet has created more opportunities for collaboration between individuals and organisations. These new forms of collaborative activity put groups of participants in si... Read More about Modifying landscapes with penalties in iterative improvement for solving distributed constraint satisfaction problems..