Enabling Smart Cities with Cognition Based Intelligent Route Decision in Vehicles Empowered with Deep Extreme Learning Machine
作者机构：School of Computational SciencesKorea Institute for Advanced StudySeoul02455Korea Department of Computer ScienceLahore Garrison UniversityLahore54000Pakistan School of Computer ScienceNational College of Business Administration&EconomicsLahore54000Pakistan Department of Unmanned Vehicle EngineeringSejong UniversitySeoul05006Korea Department of Information TechnologyKhwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2021年第66卷第1期
页 面：141-156页
核心收录：
学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0701[理学-数学] 0801[工学-力学（可授工学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：the KIAS(Research Number:CG076601) in part by Sejong University Faculty Research Fund
主 题：DELM ANN IoT feedforward route decision prediction smart city
摘 要：The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries,including the transportation *** worldwide transport departments face many obstacles following the implementation and integration of different vehicle *** of these tasks is to ensure that vehicles are autonomous,intelligent and able to grow their repository of *** learning has recently been implemented in wireless networks,as a major artificial intelligence branch,to solve historically challenging problems through a data-driven *** this article,we discuss recent progress of applying machine learning into vehicle networks for intelligent route decision and try to focus on this emerging *** Extreme Learning Machine(DELM)framework is introduced in this article to be incorporated in vehicles so they can take human-like *** present GPS compatibility issues make it difficult for vehicles to take real-time decisions under certain *** leads to the concept of vehicle controller making *** proposed DELM based system for self-intelligent vehicle decision makes use of the cognitive memory to store route *** overcomes inadequacy of the current in-vehicle route-finding technology and its *** the relevant route-related information for the ride will be provided to the user based on its *** the DELM method,a high degree of precision in smart decision taking with a minimal error rate is *** investigation,it has been observed that proposed framework has the highest accuracy rate with 70%of training(1435 samples)and 30%of validation(612 samples).Simulation results validate the intelligent prediction of the proposed method with 98.88%,98.2%accuracy during training and validation respectively.
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