Blockchain technology dependent on cryptocurrency have lately excited the curiosity of capitalists. They focused on forecasting the financial item's risk and return ratios. As a result, financial items require an ...
Blockchain technology dependent on cryptocurrency have lately excited the curiosity of capitalists. They focused on forecasting the financial item's risk and return ratios. As a result, financial items require an autonomous algorithm to anticipate the return percentage of cryptocurrency. Deep learning (DL) algorithms that were lately developed lay the path for the return percentage forecasting procedure. This paper proposes a blockchain financial product utilizing DL for a smart return rate prediction (RRP-DLBFP) method. The suggested RRP-DLBFP method entails creating a long short-term memory (LSTM) framework for return percentage forecasting. Furthermore, the Adam optimization is used to effectively change the LSTM algorithm's hyperparameters, resulting in improved forecasting accuracy. The Ethereum rate of return has been selected as the aim of guaranteeing the RRP-DLBFP method's superior performance, and its outcomes are studied in various metrics. In terms of several assessment variables, the model's results demonstrated the superiority of the RRP-DLBFP method over the present latest methods. The suggested RRP-DLBFP exhibits MSE values of 0.0435 & 0.0655, accordingly, contrasted with a mean of 0.6139 & 0.723 for comparing techniques in both training and evaluation.
For the automatic tracking of unknown moving targets on the ground,most of the commonly used methods involve circling above the *** such a tracking mode,there is a moving laser spot on the target,which will bring trou...
详细信息
For the automatic tracking of unknown moving targets on the ground,most of the commonly used methods involve circling above the *** such a tracking mode,there is a moving laser spot on the target,which will bring trouble for cooperative manned *** this paper,we propose a new way of tracking,where an unmanned aerial vehicle(UAV) circles on one side of the tracked target.A circular path algorithm is developed for monitoring the relative position between the UAV and the target considering the real-time range and the bearing *** can determine the center of the new circular path if the predicted range between the UAV and the target does not meet the monitoring requirements.A transition path algorithm is presented for planning the transition path between circular paths that constrain the turning radius of the *** transition path algorithm can generate waypoints that meet the flight *** this paper,we analyze the entire method and detail the scope of *** formulate an observation angle as an evaluation index.A series of simulations and evaluation index comparisons verify the effectiveness of the proposed algorithms.
One of the dangerous eye diseases is Glaucoma, over time it can cause blindness. When the disease is discovered early, the more serious condition will be prevented to occur. Increasing intra ocular pressure in eyes ca...
详细信息
The attacks of cyber are rapidly increasing due to advanced techniques applied by hackers. Furthermore, cyber security is demanding day by day, as cybercriminals are performing cyberattacks in this digital world. So, ...
The attacks of cyber are rapidly increasing due to advanced techniques applied by hackers. Furthermore, cyber security is demanding day by day, as cybercriminals are performing cyberattacks in this digital world. So, designing privacy and security measurements for IoT-based systems is necessary for secure network. Although various techniques of machine learning are applied to achieve the goal of cyber security, but still a lot of work is needed against intrusion detection. Recently, the concept of hybrid learning gives more attention to information security specialists for further improvement against cyber threats. In the proposed framework, a hybrid method of swarm intelligence and evolutionary for feature selection, namely, PSO-GA (PSO-based GA) is applied on dataset named CICIDS-2017 before training the model. The model is evaluated using ELM-BA based on bootstrap resampling to increase the reliability of ELM. This work achieved highest accuracy of 100% on PortScan, Sql injection, and brute force attack, which shows that the proposed model can be employed effectively in cybersecurity applications.
The present work retrieves cubic–quartic optical soliton solutions to the complex Ginzburg–Landau equation that is considered with five forms of nonlinear refractive index. The proposed algorithm reveals a full spec...
详细信息
The impurity incorporation in host high spin orbit coupling materials like platinum has shown improved charge to spin conversion by modifying the up-spin and down-spin electron’s trajectories by bending or skewing th...
详细信息
Detecting anomalies for dynamic graphs has drawn increasing attention due to their wide applications in social networks, e-commerce, and cybersecurity. Recent deep learning-based approaches have shown promising result...
详细信息
Admission of new students in 2019 through zoning still faces many obstacles, one of which is the readiness of the application to determine the distance of a student's house from the nearest recommended school. The...
详细信息
暂无评论