EVOLUTIONAL BUILDING DAMAGE PREDICTION

Towards Evolutional Compression

Compressing convolutional neural networks (CNNs) is essential for transferring the success of CNNs to a wide variety of applications to mobile devices. In contrast to directly recognizing subtle weights or filters as redundant in a given CNN, this paper presents an evolutionary method to automatically eliminate redundant convolution filters. We represent each compressed network as a binary indi...

The Evolutional Prediction Model of Carbon Emissions in China Based on BP Neural Network

This paper analyzes and processes the time sequence of carbon emissions from the perspective of the BP neural network, revealing the structure and the law of all kinds of index systems of carbon emissions and describing the dynamic characteristics of carbon emissions system. Based on the synthesis of the energy structure factors, energy efficiency factors, economic development factors, populati...

Prediction of Bioluminescent Proteins Using Auto Covariance Transformation of Evolutional Profiles

Bioluminescent proteins are important for various cellular processes, such as gene expression analysis, drug discovery, bioluminescent imaging, toxicity determination, and DNA sequencing studies. Hence, the correct identification of bioluminescent proteins is of great importance both for helping genome annotation and providing a supplementary role to experimental research to obtain insight into...

Evolutional Entanglement in Nonequilibrium Processes

Entanglement in nonequilibrium systems is considered. A general definition for entanglement measure is introduced, which can be applied for characterizing the level of entanglement produced by arbitrary operators. Applying this definition to reduced density matrices makes it possible to measure the entanglement in nonequilibrium as well as in equilibrium statistical systems. An example of a mul...

A Review of Evolutional Ethics