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 

机构地区：[1]Department of Computer Science,Aligarh Muslim University,Aligarh,202002,India [2]Department of Industrial and Systems Engineering,College of Engineering,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia [3]Department of Information Technology,Bhagwan Parshuram Institute of Technology(BPIT),GGSIPU,New Delhi,110078,India [4]Department of Electrical Engineering,College of Engineering,Princess Nourah bint Abdulrahman University,P.O.Box 84428,Riyadh,11671,Saudi Arabia [5]Department of Artificial Intelligence&Machine Learning,Maharaja Agrasen Institute of Technology(MAIT),GGSIPU,New Delhi,110086,India

出　　处：《Computer Systems Science & Engineering》2023年第9期3491-3508,共18页计算机系统科学与工程（英文）

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.

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

关 键 词：Artificial neural network(ANN) MULTIPROCESSOR hidden node nonlinear optimization parallel processing 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]