For the prediction and allocation of cloud resources we use the Ant Lion Optimization Algorithm. Artificial Neural Network (ANN) is used for resource allocation. We discuss the results that depicts we get better results compared to the existing methods with proper allocation of resources and minimal...
AI and deep learning –They design neural networks and other deep learning models to solve games and perform tasks like classifying images. Financial modeling and algorithmic trading –They might develop algorithms to predict stock market movements, assess risks, or execute high-frequency trades. How...
We repeat the above procedure K times to train K number of deep neural networks, each is supervised by annotations generated by one of the algorithms. Then we precede the final stage of our framework, that is, learning a single ensemble model from the K algorithm-trained neural networks....
Using the APF algorithm, a neural network training scheme is proposed by Wang et al. (2021), the robot's workspace is divided into two parts, Global safety area and local hazard area. In the global safety zone, the robot receives only the gravitational force from the target and moves ...
deep-learningscalabilitypytorchfeedforward-neural-networkmulti-layer-perceptrongraph-algorithmgraph-neural-networksgnnefficient-training UpdatedApr 5, 2023 Jupyter Notebook Nebula-Algorithm is a Spark Application based on GraphX, which enables state of art Graph Algorithms to run on top of NebulaGraph and...
classifiers such as decision trees,neural networks, orsupport vector machines(A), where supervised learning methods (S) have been used to learn the relationship between the statistical and informationtheoretic measuresof the instances(F)and the accuracy(Y)of the classifier algorithms. In the ...
(HDPSO) algorithm was proposed to reduce maximum workflow execution time on cloud heterogeneous platforms [1]. To do so, this problem has been formulated into a single objective optimization problem. Although it had great improvement, it has not considered VMs’ monetary costs. An energy-aware ...
Deep learning is a subfield of machine learning, and neural networks make up the backbone of deep learning algorithms. It’s the number of node layers, or depth, of neural networks that distinguishes a single neural network from a deep learning algorithm, which must have more than three. ...
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Except for directional utilization in inverse design, heuristic algorithms can produce training data for neural network [75]. Other group-dependent algorithms, like genetic algorithms, will come to a stage where most of the individuals share the similar structures, which contradicts with purpose of ...