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3 days ago · Here’s a comprehensive cheat sheet for some commonly used machine learning algorithms, categorized by type and use case. This guide briefly describes key points and typical applications for each algorithm. Machine Learning Algorithms Cheat Sheet. This article provides an overview of key algorithms in each category, their purposes, and best ...
2 days ago · The algorithm that optimizes neural network weights and hyperparameters using traditional genetic algorithms is defined as GA-BPNN, the algorithm that only optimizes neural network weights using ...
4 days ago · Power load data frequently display outliers and an uneven distribution of noise. To tackle this issue, we present a forecasting model based on an improved extreme learning machine (ELM). Specifically, we introduce the novel Pinball-Huber robust loss function as the objective function in training. The loss function enhances the precision by assigning distinct penalties to errors based on their directions. We employ a genetic algorithm, combined with a swift nondominated sorting technique, for ...
5 days ago · Then the genetic algorithm optimized based on the simulated annealing idea is built to solve the final result. The ARIMA model, optimized by the genetic algorithm, forecasts the unknown demand for vascular robot uses in a time series, and determines the optimal number of vessel boats and operators to purchase accordingly.
3 days ago · Task scheduling in cloud computing is one of primary research problem in computer science technology. Finding an optimal solution for task scheduling not only enhances the system/machine performance but also it reduces the total processing cost. There are number of task scheduling algorithms developed by previous researchers, but none of them have been globally accepted because of their own pros and cons. The current study made an attempt to solve task scheduling for optimal utilisation of ...
5 days ago · Based on our proposed approach, we concluded that the predictors of individual flow occurrences are variables linked to surface temperatures, moisture, and nitrogen availability. We have developed an automated Convolutional Neural Network creation approach genetic algorithms approach to handling image classification problems more efficiently.
3 days ago · Introduction. Researchers use Artificial Neural Networks (ANN) algorithms based on brain function to model complicated patterns and forecast issues. The Artificial Neural Network (ANN) is a deep learning method that arose from the concept of the human brain Biological Neural Networks.
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