… As such, in this article we propose an auto-learning framework to achieve intelligent and automatic network optimization by using machine learning (ML) techniques. We review the …
… The authors created DeepDR, a deep neural network model, then trained it to learn the genetic background of tumors based on data from The Cancer Genome Atlas (TCGA). DeepDR …
… Utilizing artificial intelligence (AI) expertise, especially machine and deep learningsolutions… on IoT security intelligence, which is built on machine and deep learning technologies that …
… Similar to learning in biological systems, neural networklearning involves adjustments to the synaptic connections that exist between the neurons. Probabilistic models and fuzzy logic …
… of computer-supported collaborative learning (CSCL). … /or intelligent systems that aim to support collaborative learning (eg, [2]) (a detailed analysis of the design and impact of intelligent …
… so they rely heavily on edge and core networks to manage, process, and analyze data. As a … development of intelligent and effective resource management and network management …
DDN Chorafas, H Steinmann - 1990 - api.taylorfrancis.com
… New intelligentnetworksolutions are evolving because answers to telecommunications needs in the past no longer respond to requirements. Just a few years ago, the feeling among …
… learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network … the learning approach. …
… learning enablers for network systems. In addition, we discuss, in detail, a new use case, ie, deep learning based intelligent … learning for routing in order to facilitate intelligentnetwork …