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Artificial Neural Network (ANN) is a widely used technique in forecasting applications. An ensemble of ANNs can produce more accurate forecasts than a single ANN. The performance of the ensemble depends on its' member ANN. Member selection for an ensemble is a complicated task that need balancing conflicting conditions. This paper presents a method to optimize the selection of members for an ANN ensemble...
Accurate weather forecasts are essential for various human activities. Weather forecasting is a complex process that can exhaust the resources of many computational devices. Out of numerous weather forecasting techniques Artificial Neural Networks (ANN) methodology is one of the most widely used techniques. In this study the application of Neural Network Ensembles in Rainfall Forecasting is investigated...
Rainfall is a complex process and forecasting rainfall is complicated because it involves a lot of parameters but precise rainfall forecasting is necessary for many human activities. Even though considerable research work has been done in rainfall prediction, comparatively fewer efforts have been made on Sri Lankan monsoon rainfall prediction using large scale climatic teleconnections. In this paper,...
In this paper, a modified particle swarm optimisation algorithm is proposed for protein sequence motif discovery. Protein sequences are represented as a chain of symbols and a protein sequence motif is a short sequence that exists in most of the protein sequence families. Protein sequence symbols are converted into numbers using a one to one amino acid translation table. The simulation uses EGF protein...
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