scholarly journals Digital TV Network Management System Based on WEB

2022 ◽  
Vol 2146 (1) ◽  
pp. 012024
Author(s):  
Wei Qi ◽  
Chun Ying ◽  
Sheng Yong ◽  
Guizhi Zhao ◽  
Lihua Wang
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Control Method ◽  
Digital Tv ◽  
Network Management System ◽  
Snake Robot ◽  
Intelligent Machines ◽  
Artificial Intelligence Technology ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

Abstract With the development and popularization of computer artificial intelligence technology, more and more intelligent machines are gradually produced. These intelligent machines have brought great convenience to people’s lives. This paper studies the control method of snake robot based on environment adaptability, which mainly explains the construction and stability of multi-modal CPG model. In addition, this paper also studies the trajectory tracking and dynamic obstacle avoidance of mobile robot based on deep learning.

scholarly journals An autonomous dynamic collision avoidance control method for unmanned surface vehicle in unknown ocean environment

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141983158 ◽  
Author(s):  
Yunsheng Fan ◽  
Xiaojie Sun ◽  
Guofeng Wang
Keyword(s):  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Control Method ◽  
Unmanned Surface Vehicle ◽  
Time Dynamic ◽  
Collision Avoidance Control ◽  
Dynamic Obstacle Avoidance ◽  
Avoidance Control ◽  
Dynamic Obstacle ◽  
Ocean Environment

There are many unknown obstacles in the sea, so the autonomous navigation of unmanned surface vehicle needs to avoid them as soon as possible even under the condition of low control ability of the controller. To solve the problem, by combining the dynamic collision avoidance algorithm and tracking control, a dynamic collision avoidance control method in the unknown ocean environment is presented. In this article, in consideration of the unknown ocean environment and real-time dynamic obstacle avoidance problem, the collision avoidance controller using a velocity resolution method and backstepping tracking controller based on unmanned surface vehicle maneuvering motion model is designed. Simulation results show that the method is effective and accurate and can provide the reference for the unmanned surface vehicle intelligent collision avoidance control technology.

scholarly journals Application of Artificial Intelligence Technology Optimized by Deep Learning to Rural Financial Development and Rural Governance

2022 ◽  
Vol 30 (7) ◽  
pp. 1-23
Author(s):  
Hongwei Hou ◽  
Kunzhi Tang ◽  
Xiaoqian Liu ◽  
Yue Zhou
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Short Term Memory ◽  
Research Result ◽  
Customer Information ◽  
Rural Governance ◽  
Artificial Intelligence Technology ◽  
Reasonable Prediction

The aim of this article is to promote the development of rural finance and the further informatization of rural banks. Based on DL (deep learning) and artificial intelligence technology, data pre-processing and feature selection are conducted on the customer information of rural banks in a certain region, including the historical deposit and loan, transaction record, and credit information. Besides, four DL models are proposed with a precision of more than 87% by test to improve the simulation effect and explore the application of DL. The BLSTM-CNN (Bi-directional Long Short-Term Memory-Convolutional Neural Network) model with a precision of 95.8%, which integrates RNN (Recurrent Neural Network) and CNN (Convolutional Neural Network) in parallel, solves the shortcomings of RNN and CNN separately. The research result can provide a more reasonable prediction model for rural banks, and ideas for the development of rural informatization and promoting rural governance.

The Application of Artificial Intelligence Technology in the Selective Laster Sintering

2014 ◽  
Vol 1037 ◽  
pp. 236-239
Author(s):  
Li Yuan Cai ◽  
Qing Shun Wang ◽  
Wei Sun
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Bp Neural Network ◽  
Research Method ◽  
Control Method ◽  
Laser Sintering ◽  
Sintering Process ◽  
Optimal Parameters ◽  
Artificial Intelligence Technology ◽  
Neural Network Algorithm

Based on laser sintering constituency as the research object, this paper aimed at the perspective of artificial intelligence technology. It uses the new control theory and research method of BP neural network algorithm and tries to provide reference for optimizing the sintering process of laser district. This paper argues that the application of artificial intelligence technology to laser sintering constituency. Through the simulation, it can make up for the inadequacy of the traditional control method. Under certain conditions, the goal of process optimization will be achieved by finding the optimal parameters.

scholarly journals Design of College Evaluation System Based on Artificial Intelligence and Deep Learning Technology

CONVERTER ◽  
2021 ◽  
pp. 651-658
Author(s):  
Jiang Yan, Wang Peipei
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Performance Appraisal ◽  
Evaluation System ◽  
Learning Technology ◽  
Functional Requirements ◽  
Appraisal System ◽  
Performance Appraisal System ◽  
Artificial Intelligence Technology ◽  
Business Requirements

Artificial intelligence and deep learning technology are important technologies widely used in manufacturing industry.With the help of performance appraisal system to comprehensively evaluate the performance of teachers is a good measure. Therefore, it is very necessary to develop a performance appraisal system for university teachers by using artificial intelligence technology. This paper first demonstrates the feasibility of the development of performance appraisal system, and scientifically divides the user roles. According to the business requirements, the core business process of the system is established, and the system architecture and functional modules are designed. At the same time, this paper establishes the conceptual model and logical model of database. Finally, SSH framework and extjs framework are used to realize the functions of the system. In this paper, the reliability, stability and security of the system are tested to ensure that the system meets the functional and non functional requirements. The operation results show that the system has stable functions, simple operation and convenient maintenance, and basically meets the needs of users at different levels.

Research on the Control Method of Unmanned Helicopter Under the Background of Artificial Intelligence

2021 ◽  
Author(s):  
Wenze Li ◽  
Xuanzi Zhang ◽  
Bo Huang ◽  
Yi Chen ◽  
Ruiqi Zhang ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Reference System ◽  
Control Method ◽  
Performance Ratio ◽  
Cost Ratio ◽  
Complex Data ◽  
Unmanned Helicopter ◽  
Research Activities ◽  
Wide Range

A synopsis of a multidisciplinary research initiative focused on critical strategies for the genuine independent flight of tiny, vertical flying take-off (VTOL) unmanned aerial vehicles (UAVs). The research activities are the flight testbed, a simulation and test environment, and integrated components for onboard navigation, perception, design, and control. The necessity to create an unmanned helicopter system in different new civil applications cannot be overlooked. A highly reliable model may be used in the design, analysis, and implementation. The helicopter is fitted with a reference system for flight test data measurement and recording attitude heading reference system (AHRS) and the accompanying data storage modules. Recently, artificial intelligence-based deep learning (DL) has demonstrated excellent outcomes for a wide range of robotic activities in the areas of perception, planning, location, and management. Its remarkable skills to learn from complex data obtained in actual surroundings make it appropriate for many autonomous robotic applications. At the same time, UHS is currently widely utilized in various civil tasks in security, cinematography, disaster assistance, package delivery, or warehouse management (Unmanned Helicopter System). This paper conducted detailed work on current applications and the most significant advances and their performance and limits for the DL-UHS method. Furthermore, the essential strategies for deep learning are explained in depth — finally, discussing the principal hurdles of applying deep learning for UHS solutions. The proposed DL-UHS enhance outcome to evaluate the control strategies for the unmanned helicopter to achieve the low signal to noise error ratio of 31.3%, the error rate of 33.6%, the high-performance ratio of 91.4%, enhance accurate path planning 97.5%, prediction ratio of 96.3%, less trajectory cost ratio of 17.8% and increased safety tracking rate 93.6% when compared to other popular methods.

Artificial Intelligence and the Temporality of Machine Images

2021 ◽  
Author(s):  
Andrew R. Johnston
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Video Games ◽  
Learning Strategies ◽  
Learning Algorithms ◽  
Computational Time ◽  
Artificial Intelligence Technology ◽  
Learning Test ◽  
The Relationship

DeepMind, a recent artificial intelligence technology created at Google, references in its name the relationship in AI between models of cognition used in this technology‘s development and its new deep learning algorithms. This chapter shows how AI researchers have been attempting to reproduce applied learning strategies in humans but have difficulty accessing and visualizing the computational actions of their algorithms. Google created an interface for engaging with computational temporalities through the production of visual animations based on DeepMind machine-learning test runs of Atari 2600 video games. These machine play animations bear the traces of not only DeepMind‘s operations, but also of contemporary shifts in how computational time is accessed and understood.

The emergence of artificial intelligence in cardiology: current and future applications

2021 ◽  
Vol 17 ◽  
Author(s):  
Prashanth Kulkarni ◽  
Manjappa Mahadevappa ◽  
Srikar Chilakamarri
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Patient Care ◽  
Current Evidence ◽  
Cognitive Computing ◽  
Cardiovascular Medicine ◽  
Artificial Intelligence Technology ◽  
Application Prospects

: Artificial intelligence technology is emerging as a promising entity in cardiovascular medicine, potentially improving diagnosis and patient care. In this article, we review the literature on artificial intelligence and its utility in cardiology. We provide a detailed description of concepts of artificial intelligence tools like machine learning, deep learning, and cognitive computing. This review discusses the current evidence, application, prospects, and limitations of artificial intelligence in cardiology.

scholarly journals FNet: A Two-Stream Model for Detecting Adversarial Attacks against 5G-Based Deep Learning Services

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guangquan Xu ◽  
Guofeng Feng ◽  
Litao Jiao ◽  
Meiqi Feng ◽  
Xi Zheng ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Communication Networks ◽  
Learning Technology ◽  
Stream Network ◽  
Fifth Generation ◽  
Decision Network ◽  
Artificial Intelligence Technology ◽  
Adversarial Examples ◽  
The Difference

With the extensive application of artificial intelligence technology in 5G and Beyond Fifth Generation (B5G) networks, it has become a common trend for artificial intelligence to integrate into modern communication networks. Deep learning is a subset of machine learning and has recently led to significant improvements in many fields. In particular, many 5G-based services use deep learning technology to provide better services. Although deep learning is powerful, it is still vulnerable when faced with 5G-based deep learning services. Because of the nonlinearity of deep learning algorithms, slight perturbation input by the attacker will result in big changes in the output. Although many researchers have proposed methods against adversarial attacks, these methods are not always effective against powerful attacks such as CW. In this paper, we propose a new two-stream network which includes RGB stream and spatial rich model (SRM) noise stream to discover the difference between adversarial examples and clean examples. The RGB stream uses raw data to capture subtle differences in adversarial samples. The SRM noise stream uses the SRM filters to get noise features. We regard the noise features as additional evidence for adversarial detection. Then, we adopt bilinear pooling to fuse the RGB features and the SRM features. Finally, the final features are input into the decision network to decide whether the image is adversarial or not. Experimental results show that our proposed method can accurately detect adversarial examples. Even with powerful attacks, we can still achieve a detection rate of 91.3%. Moreover, our method has good transferability to generalize to other adversaries.

scholarly journals Patent Analysis Using Vector Space Model and Deep Learning Model : A Case of Artificial Intelligence Industry Technology

2021 ◽  
Author(s):  
Yongmin Yoo ◽  
Dongjin Lim ◽  
Kyungsun Kim
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Vector Space ◽  
Rapid Development ◽  
Vector Space Model ◽  
Learning Model ◽  
Patent Data ◽  
Space Model ◽  
Artificial Intelligence Technology ◽  
Deep Learning Model

Thanks to rapid development of artificial intelligence technology in recent years, the current artificial intelligence technology is contributing to many part of society. Education, environment, medical care, military, tourism, economy, politics, etc. are having a very large impact on society as a whole. For example, in the field of education, there is an artificial intelligence tutoring system that automatically assigns tutors based on student's level. In the field of economics, there are quantitative investment methods that automatically analyze large amounts of data to find investment laws to create investment models or predict changes in financial markets. As such, artificial intelligence technology is being used in various fields. So, it is very important to know exactly what factors have an important influence on each field of artificial intelligence technology and how the relationship between each field is connected. Therefore, it is necessary to analyze artificial intelligence technology in each field. In this paper, we analyze patent documents related to artificial intelligence technology. We propose a method for keyword analysis within factors using artificial intelligence patent data sets for artificial intelligence technology analysis. This is a model that relies on feature engineering based on deep learning model named KeyBERT, and using vector space model. A case study of collecting and analyzing artificial intelligence patent data was conducted to show how the proposed model can be applied to real-world problems.

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