Design of ANN Based Non-Linear Network Using Interconnection of Parallel Processor

作     者：Anjani Kumar Singha Swaleha Zubair Areej Malibari Nitish Pathak Shabana Urooj Neelam Sharma 

作者机构：Department of Computer ScienceAligarh Muslim UniversityAligarh202002India Department of Industrial and Systems EngineeringCollege of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information TechnologyBhagwan Parshuram Institute of Technology(BPIT)GGSIPUNew Delhi110078India Department of Electrical EngineeringCollege of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence&Machine LearningMaharaja Agrasen Institute of Technology(MAIT)GGSIPUNew Delhi110086India 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第46卷第9期

页      面：3491-3508页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：This research is funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R 151) Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia 

主　　题：Artificial neural network(ANN) multiprocessor hidden node nonlinear optimization parallel processing 

摘      要：Suspicious mass traffic constantly evolves,making network behaviour tracing and structure more *** networks yield promising results by considering a sufficient number of processing elements with strong interconnections between *** offer efficient computational Hopfield neural networks models and optimization constraints used by undergoing a good amount of parallelism to yield optimal *** neural network(ANN)offers optimal solutions in classifying and clustering the various reels of data,and the results obtained purely depend on identifying a *** this research work,the design of optimized applications is presented in an organized *** addition,this research work examines theoretical approaches to achieving optimized results using *** mainly focuses on designing *** optimizing design approach of neural networks analyzes the internal process of the neural *** in developing the network are based on the interconnections among the hidden nodes and their learning *** methodology is proven best for nonlinear resource allocation problems with a suitable design and complex *** ANN proposed here considers more or less 46k nodes hidden inside 49 million connections employed on full-fledged parallel *** proposed ANN offered optimal results in real-world application problems,and the results were obtained using MATLAB.