Climbing Out of Our Silos to Improve Practice

Breaking Risk Management Out of its Silos

Intubation in the ICU: we could improve our practice

Comparison of Genetic and Hill Climbing Algorithms to Improve an Artificial Neural Networks Model for Water Consumption Prediction

No unique method has been so far specified for determining the number of neurons in hidden layers of Multi-Layer Perceptron (MLP) neural networks used for prediction. The present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. The data used in the present research for prediction are consumption data of water...

Reaching Out to Shape Our Future

Using Patterns To Improve Our Architectural Vision

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