The proposed study focuses on predicting unidentified malware risks utilizing the Malevis23 dataset. This process involves generating new images through various Generative Adversarial Networks (GANs) and subsequently employing a Convolutional…
Category: 7. Maths
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Machine learning models to identify significant factors of panic buying situation
In this experiment, all of these works have been done in Google Colab, where various classifiers, including LR, DT, RF, Bagging, SVM, AdaBoost, GB, CatBoost, XGBoost, and MLP, were applied to the baseline and converted versions using 5-fold…
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An energy aware cluster inspired routing protocol using multi strategy improved crayfish optimization algorithm for guaranteeing green communication in IoT
This Improved CFOA used for achieving an intelligent clustering mechanism during the process of green communication in IoT completely derives its inspiration from the behaviour of crayfish in the nature. The traditional CFOA was contributed by…
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Evaluating the effectiveness of the forest pests and diseases control methods on the industrial wood production using deep learning
Sevinç, V. Assessment of the effects of the biotic and abiotic harmful factors on the amount of industrial wood production with deep learning. Environ. Sci. Pollut. Res. 30(14), 41999–42015 (2023).
Google…
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A comparative analysis of meshless based simulation optimization models with metaheuristic algorithms for groundwater remediation
Whale optimization algorithm (WOA)
Inspired by the intelligent bubble net technique of feeding on small fishes of the humpback whales, WOA is a powerful metaheuristic algorithm proposed by Mirjalili and Lewis28 capable of converging towards the…
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A mean-field approach to criticality in spiking neural networks for reservoir computing
Mean-field approximation
Under the mean-field approximation, the first term of (1) primarily consists of impulses arriving at a frequency of \(n_k/(\tau N)(1/n_k)=1/(\tau N)\), as each neuron is selected with uniform probability. In the second…
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Towards modular intelligent design method of subway station spatial with PointNet++
Comparison and analysis of prediction results
PointNet++ model prediction is different from model training in that model prediction requires loading all data sets rather than random sampling. The test set contains a total of 60 point cloud…
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Predictive Coding Light | Nature Communications
Network architecture
In the PCL network all feedforward connections are excitatory, while all recurrent or feedback connections are inhibitory (Fig. 1a). A unit in the PCL network can therefore excite some of its targets and inhibit others, i.e.,…
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A linear regression penalty estimator programme for the mitigation of shortcomings in availability based tariff scheme adopted in Indian power grid networks
The proposed penalty indicator programme (PIP) intends to provide an indicative signal for imposing penalty for the unscheduled interchange of power through the ABT mechanism16. This PIP will try to witness the follow through of frequency dips…
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