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The 5th Int’l Conf. on Literature, Humanities, Education, Business & Corporate Social Responsibilities (LHEBC-17);the 4th Int’l Conf. on Innovations in Engineering, Technology, Computers and Industrial Applications (IETCIA-17);the 7th Int’l Conf. on Innovations in Chemical, Biological, Environmental and Food Sciences (ICBEFS-17);the 4th Int’l Conference on Chemical, Materials, Mining and Manufacturing Engineering (CM3E-17);the 7th International Conference on Chemistry, Biofuels and Chemical Engineering (CBCE-17);the 5th Int’l Conf. on Advances in Science, Engineering, Technology and Natural Resources (ICASETNR-17)

作者： Irfan Syamsuddin CAIR Center for Applied ICT Research Dept. of Computer and Networking EngineeringState Polytechnic of Ujung Pandang

Video streaming has emerged as an important tool for business,education,transportation and other *** study acts as a preliminary study on delivering video streaming within a mesh network such as cloud computing *** this situation,bandwidth,jitter and loss of data are still considered as serious issues to be solved with respect to great number of end users with various network characteristics and with a goal to keep the video at appropriate *** intelligent schemes to improve video streaming services have been proposed by researchers through different *** study aims to explore state of the art in intelligent video streaming schemes as a foundation for future applications of video streaming solution that is adaptive with the cloud infrastructure condition.

关键词： Video streaming networking intelligent algorithm survey

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Resource Scheduling Strategy for Data Transmission Task of Data Relay Satellite 23

Resource Scheduling Strategy for Data Transmission Task of D...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Li, Keying Zhu, Shibing Dai, Jianmei Graduate School Space Engineering University Beijing China School of Space Information Space Engineering University Beijing China

ISBN: (纸本)9798350325959

The resource scheduling is vital for the data relay satellites, which plays a backbone role in the architecture of integrated space-ground network for space craft TT &C and communication. However, the resource scheduling strategy is facing more challenges with the increasing number of space-craft and user demands. In this paper, a scenario of multi-satellites collaborative reconnaissance supported by the data relay satellite with a single address access antenna is considered and a maximum sum benefits problem is formulated. To solve the original multi-constraints optimization problem efficiently, an improved artificial bee colony algorithm is proposed. Compared with the baseline approaches, our proposed scheme can achieve better priority and convergence performance with acceptable run duration. © 2023 IEEE.

关键词： Data relay satellite Data transmission task intelligent algorithm Resource scheduling Single address access

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Machine Learning Methods for intelligent Abnormal Brain Identification

Machine Learning Methods for Intelligent Abnormal Brain Iden...

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2017 International Conference on Applied Mathematics, Modelling and Statistics Application（AMMSA2017）

作者： Fangyuan Liu Siyuan Lu Leonid Snetkov School of Computer Science and Technology Department of Computer Technologies and Control Systems ITMO University

This survey paper describes a focused literature survey of machine learning methods in order to detect pathological brain. Based on the published time and emerging methods, this paper introduces in details the methods used in each documents. Because of the requirement to select a good approach in the process of pathological brain analysis, we compare the classification results of different methods and present a promising future.

关键词： pathological brain detection machine learning intelligent algorithm category recognition

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Research on Flexible Flow⁃Shop Scheduling Problem with Lot Streaming in IOT⁃Based Manufacturing Environment

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Transactions of Nanjing University of Aeronautics and Astronautics 2020年第6期37卷 831-838页

作者： DAI Min WANG Lixing GU Wenbin ZHANG Yuwei DORJOY M M H College of Mechanical Engineering Yangzhou UniversityYangzhou 225127P.R.China Department of Mechanical and Electrical Engineering Hohai UniversityChangzhou 213022P.R.China

It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information *** to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling ***,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the *** improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global ***,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.

关键词： IOT-based manufacturing flexible flow-shop scheduling intelligent algorithm lot-streaming strategy

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Image segmentation algorithm based on the second clustering and level set method

Image segmentation algorithm based on the second clustering ...

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2016 4th International Conference on Electrical&Electronics Engineering and Computer Science(ICEEECS 2016)

作者： Hai Jie Wu Li Wu Haiyan Du Hailong School of Electronics and Information Engineering SIAS International University

ISBN: (纸本)9781510835429

Improve the level set algorithm by Lagrangian particle enhanced replanting algorithm and increase the reduced segmentation accuracy brought about by the algorithm for uneven image pixel for medical CT image. Based on Literature [4], the combination of Lagrangian particle enhanced replanting algorithm and level set algorithm is adopted, the convergence of velocity field for singular point is promoted through increase of velocity vector and unit normal vector and the medical CT image segmentation method of hybrid level set(LPRLS) based on Lagrangian particle enhanced replanting algorithm is proposed in the Thesis. Calculate the Lagrangian labeled particle before calculating the formula of horizontal set to rebuild the embedded interface in order to improve the mass conservation property of level set algorithm;improve the convergence of velocity field for singular point and topological change point through increasing velocity vector and unit normal vector in order to handle the singularity of interface and complicated geometric correlation. The simulation results of algorithm indicate that the performance of the proposed algorithm is greatly improved compared with the original algorithm. It can be concluded from the simulation results that the existing insufficiency is the proportion of error identification of the algorithm.

关键词： level set image segmentation intelligent algorithm cluster analysis

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An Improved Fruit Fly Optimization algorithm and Its Application

An Improved Fruit Fly Optimization Algorithm and Its Applica...

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2015 International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2015)

作者： Shi Hui Shu San Ye Zhu Yi Harbin Institute of Technology Control and Simulation Center

ISBN: (纸本)9781510806481

Fruit fly optimization algorithm is a new swarm intelligent algorithm proposed in recent years and has been concerned for its few parameters and high computational efficiency. However, the application of the algorithm is limited for unstable optimization capability. To solve that question, an improved fruit fly optimization algorithm is proposed in this paper. Some factors affecting the performance of the algorithm are improved. The improved algorithm are proved by function optimization and applied to the analog circuit fault diagnosis.

关键词： fruit fly optimization algorithm intelligent algorithm SVM analog circuit fault diagnosis

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Software Test Case Generation Based on the Fault Propagation Path Coverage

Software Test Case Generation Based on the Fault Propagation...

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Annual Reliability and Maintainability Symposium

作者： Wang Kun Wang Yichen Beihang Univ Sci & Technol Reliabil & Environm Engn Lab Beijing 100191 Peoples R China

ISBN: (纸本)9781509002498

In the process of software testing, correlated defects raise researchers' attention worldwide. Some potential defects are hard to be detected in the test. To address these potential defects, this paper adopts an error propagation model to describe the process of defect evolution and applies fault injection method to introduce known seed-defects. Subsequently, seed-defects are activated and related potential defects are induced through test case design. This method employs intelligent algorithms to constantly design test cases to cover paths of seed-defects and paths of propagation. As a result, more undetected and correlated defects can be detected in paths of propagation.

关键词： correlated defects fault injection seed-defect fault propagation path path coverage intelligent algorithm

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The Prediction Model for Transverse Thickness Difference of Electric Steel in 6-High Cold Rolling Mills Based on GA-PSO-SVR Approach

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STEEL RESEARCH INTERNATIONAL 2022年第11期93卷

作者： Song, Chun-Ning Cao, Jian-Guo Wang, Lei-Lei Xiao, Jing Zhao, Qiu-Fang Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Univ Sci & Technol Beijing Inst Artificial Intelligence Beijing 100083 Peoples R China Univ Sci & Technol Beijing Natl Engn Res Ctr Flat Rolling Equipment Beijing 100083 Peoples R China Univ Sci & Technol Beijing Shunde Grad Sch Foshan 528399 Guangdong Peoples R China

To meet the shape quality requirements of "Dead flat" rectangular section of electrical steel in the cold rolling process, the transverse thickness difference (TTD) prediction model of 6-high tandem cold rolling mills (TCMs) based on genetic algorithm, particle swarm optimization, and support vector regression (GA-PSO-SVR) is proposed. The TTD prediction model uses 5000 coils of data obtained from a cold rolling line. The GA-PSO-SVR model is obtained by the GA-PSO hybrid algorithm to search and obtain the optimal parameter of the SVR to improve the prediction model accuracy. The results reveal that using multiple evaluation indicators the GA-PSO-SVR model has preferably adaptability and higher accuracy. Meanwhile, the relative importance of input variables is calculated based on the GA-PSO-SVR model, which indicates that the shape control methods in stands 1-5 have the most important influence on the TTD. The TTD prediction model is continuously applied to 1420 mm 6-high TCMs;the results show that the rate of the TTD less than 7 mu m increased from 29.6% to 63.85%.

关键词： cold rolling mill electric steel intelligent algorithm shape control transverse thickness difference

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Establishment of data-driven multi-objective model to optimize drilling performance

GEOENERGY SCIENCE AND ENGINEERING

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GEOENERGY SCIENCE AND ENGINEERING 2023年 231卷

作者： Qu, Fengtao Liao, Hualin Liu, Jiansheng Lu, Ming Wang, Huajian Zhou, Bo Liang, Hongjun China Univ Petr East China Sch Petr Engn Qingdao 266580 Peoples R China CNPC Tarim Oilfield Co Korla 841000 Peoples R China

Drilling parameters optimization has consistently generated research interest over the years because of the costsaving benefits associated to improve drilling efficiency. However, several physics-based and data-driven models have been developed for drilling parameters optimization, and the majority of the data-driven models are based on regression methods. Obtaining highly accurate and optimized drilling parameters with rapid as well as costeffective simulation runs is difficult to achieve. To accurately and rapidly predict drilling parameters, a multiobjective optimization model was proposed in this study. In the proposed model, the rate of penetration (ROP), unit drilling cost (UDC), and mechanical specific energy (MSE) were considered as the objective functions, while the weight on bit (WOB) and rotations per minute (RPM) were chosen as the optimization variables. Meanwhile, a method for ROP prediction based on improved back propagation neural network (BP) is also presented. Field data presented in this study indicate that when drilling is free of drilling complications, this multi-objective optimization model could optimize WOB and RPM with higher ROP and lower MSE, and UDC.

关键词： Parameter optimization intelligent drilling ROP prediction Big data intelligent algorithm

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Research and Implementation of Financial Decision Model Based on Artificial Intelligence

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AGRO FOOD INDUSTRY HI-TECH 2017年第3期28卷 2576-2579页

作者： Zhao, Desheng Liu, Xiaoyu Langfang Ploytech Inst Langfang Hebei Peoples R China

Artificial intelligence has reached a new level in the global. Because of the improvement of the current neural network depth learning algorithm, some basic artificial intelligence technology has developed rapidly. In the financial sector, artificial intelligence can greatly optimize the process of a series of existing financial transaction, which can be applied and served to customers at the front end to achieve a variety of financial transactions and financial analysis decisions. Based on this, the research and implementation of financial decision model based on artificial intelligence were studied in this paper. The impact of artificial intelligence on the financial industry was introduced first. Technical problems and solutions, theoretical support and key technologies were introduced. Finally, the specific process of financial decision model based on Agent artificial intelligence was introduced in detail. The test results show that the financial decision model based on artificial intelligence can be used for risk prevention and control, which makes our financial services more personalized and intelligent, so that the financial risk control ability is more powerful.

关键词： artificial intelligence financial intelligent algorithm agent

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