Kanaerva's sparse distributed memory (SDM) is an associative memory model based on the mathematical properties of high dimensional binary address spaces. Holland's genetic algorithms are a search technique for high dimensional spaces inspired by evolutional processes of DNA. Genetic Memory is a hybrid of the above two systems, in which the memory uses a genetic algorithm to dynamically reconfigure its physical storage locations to reflect correlations between the stored addresses and data. This architecture is designed to maximize the ability of the system to scale-up to handle real world problems
An information processing task which generates combinatorial explosion and program complexity when i...
Weather systems use extremely complex combinations of mathematical tools for anal-ysis and forecasti...
Analysing large-scale data brings promises of new levels of scientific discovery and economic value....
We describe the use of genetic algorithms to initialize a set of hard locations that constitutes the...
BACKGROUND In recent years, the price drop in off-the-shelf computer systems has enabled small insti...
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solv...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
Analog methods (AMs) allow for the prediction of local meteorological variables of interest(predicta...
Copyright @ Springer-Verlag Berlin Heidelberg 2006.In recent years dynamic optimization problems hav...
The need for reliable predictions in environmental modelling is well-known. Particularly, the predic...
As a Guest Computational Investigator under the NASA administered component of the High Performance ...
AbstractThe need for reliable predictions in environmental modelling is well-known. Particularly, th...
The genetic algorithm (GA) is a popular random search and optimization method inspired by the concep...
This project evaluates a hybridised k-Nearest Neighbour (k-NN) and Genetic Algorithms (GA) classifie...
In meteorology, the small changes in the initial condition of the atmosphere will lead to big change...
An information processing task which generates combinatorial explosion and program complexity when i...
Weather systems use extremely complex combinations of mathematical tools for anal-ysis and forecasti...
Analysing large-scale data brings promises of new levels of scientific discovery and economic value....
We describe the use of genetic algorithms to initialize a set of hard locations that constitutes the...
BACKGROUND In recent years, the price drop in off-the-shelf computer systems has enabled small insti...
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solv...
Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circu...
Analog methods (AMs) allow for the prediction of local meteorological variables of interest(predicta...
Copyright @ Springer-Verlag Berlin Heidelberg 2006.In recent years dynamic optimization problems hav...
The need for reliable predictions in environmental modelling is well-known. Particularly, the predic...
As a Guest Computational Investigator under the NASA administered component of the High Performance ...
AbstractThe need for reliable predictions in environmental modelling is well-known. Particularly, th...
The genetic algorithm (GA) is a popular random search and optimization method inspired by the concep...
This project evaluates a hybridised k-Nearest Neighbour (k-NN) and Genetic Algorithms (GA) classifie...
In meteorology, the small changes in the initial condition of the atmosphere will lead to big change...
An information processing task which generates combinatorial explosion and program complexity when i...
Weather systems use extremely complex combinations of mathematical tools for anal-ysis and forecasti...
Analysing large-scale data brings promises of new levels of scientific discovery and economic value....