FORECAST OF METEOROLOGICAL DATA UTILIZING STATE-SPACE MODEL UTILIZING METRIC-MULTI DIMENSIONAL SCALING

Rescaling Non-metric Data to Metric Data Using Multi-Dimensional Scaling

Rescaling of nominaland ordinal-scaled data to interval-scaled data is an important preparatory step prior to applying parametric statistical tests. Without rescaling, the analyst typically must resort to non-parametric tests that are less robust statistically than the metric counterparts. Multi-dimensional scaling (MDS) is a procedure that can be used to perform the desired rescaling. This pap...

Multi-Dimensional Scaling Assignment ‘Non-metric multidimensional scaling on data from the USA Beer Market’

Nonlinear multi-objective receding horizon design utilizing state-dependent formulation

The art of multi-objective design is to extract the best compromise among conflicting requirements. The analytical multi-objective parameter synthesis adopts closed-form specifications that make the multi-objective design in linear systems computationally efficient. In this paper, the analytical multi-objective parameter synthesis method is extended to nonlinear systems via the state-dependent ...

Utilizing Internal State in Multi-Robot Coordination Tasks

The success of a task-achieving multi-robot system (MRS) depends on effective coordination mechanisms to mediate the robots’ interactions in such a way that a given task is achieved. In the MRS community, many elegant coordination mechanisms have been empirically demonstrated. However, there is a lack of systematic procedures for the synthesis of coordinated MRS. In this paper, we address this ...

Classifying patients and controls using multi-dimensional scaling and exploring the metric of semantic space

Multi-dimensional scaling (MDS) has been used to visualize the organization of semantic memory in normal control subjects and in psychiatric conditions such as schizophrenia and Alzheimer's disease. However, the potential for such techniques to classify subjects into diagnostic groups has not been realized. This study attempted to tackle this by developing classification statistics and by explo...