Results 1 to 10 of about 16,738 (162)
Evolutionary Computation and Its Applications in Neural and Fuzzy Systems [PDF]
Applied Computational Intelligence and Soft Computing, 2011 Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization.
Biaobiao Zhang +3 more
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Evolutionary Neural Network Based Energy Consumption Forecast for Cloud Computing [PDF]
2015 International Conference on Cloud Computing Research and Innovation (ICCCRI), 2015 The success of Hadoop, an open-source\ud framework for massively parallel and distributed computing, is\ud expected to drive energy consumption of cloud data centers to\ud new highs as service providers continue to add new\ud infrastructure, services and capabilities to meet the market\ud demands.
Cindy Goh, Yong Wee Foo, Yun Li
exaly +2 more sources
Ain Shams Engineering JournalCloud computing offers scalable, on-demand resources but remains highly vulnerable to cyberattacks, where the nonlinear and dynamic nature of network traffic makes detection especially challenging.
R. Ravi Kanth, T. Prem Jacob
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Development of a traditional transport system based on the bee colony algorithm [PDF]
E3S Web of Conferences, 2023 At present, a significant part of optimization problems, particularly questions of combinatorial optimization, are considered NP-complete problems. When solving optimization problems, the neural network approach increases the probability of obtaining an ...
Ziyadullaev Davron +5 more
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Integrating evolutionary computation with neural networks [PDF]
Proceedings Electronic Technology Directions to the Year 2000, 2002 There is a tremendous interest in the development of the evolutionary computation techniques as they are well suited to deal with optimization of functions containing a large number of variables. This paper presents a brief review of evolutionary computing techniques.
Vonk, E. +3 more
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Mathematics, 2022 As one of the important artificial intelligence fields, brain-like computing attempts to give machines a higher intelligence level by studying and simulating the cognitive principles of the human brain.
Chuang Liu +3 more
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Spike Neural Network Learning Algorithm Based on an Evolutionary Membrane Algorithm
IEEE Access, 2021 As one of the important artificial intelligence fields, brain-like computing attempts to give machines a higher intelligence level by studying and simulating the cognitive principles of the human brain.
Chuang Liu +4 more
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Applied Sciences, 2020 A smart grid is a promising use-case of AIoT (AI (artificial intelligence) across IoT (internet of things)) that enables bidirectional communication among utilities that arises with demand response (DR) schemes for demand-side management (DSM) and ...
Yu-Chen Hu, Yu-Hsiu Lin, Chi-Hung Lin
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Evolutionary training and abstraction yields algorithmic generalization of neural computers [PDF]
Nature Machine Intelligence, 2020 Nature Machine ...
Daniel Tanneberg +2 more
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Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems
Scientific Reports, 2021 Efficient search in vast combinatorial spaces, such as those of possible action sequences, linguistic structures, or causal explanations, is an essential component of intelligence.
Dániel Czégel +4 more
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