標(biāo)題: Titlebook: Machine Learning Techniques for Smart City Applications: Trends and Solutions; D. Jude Hemanth Book 2022 The Editor(s) (if applicable) and [打印本頁(yè)] 作者: Bunion 時(shí)間: 2025-3-21 16:03
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書目名稱Machine Learning Techniques for Smart City Applications: Trends and Solutions讀者反饋學(xué)科排名
作者: largesse 時(shí)間: 2025-3-21 21:30 作者: 小歌劇 時(shí)間: 2025-3-22 04:07 作者: albuminuria 時(shí)間: 2025-3-22 08:13
D. Jude HemanthPresents an in-depth coverage on different variety of applications related with smart cities.Maximizes reader’s insights about the role of machine learning in different applications of smart cities.In作者: 失望昨天 時(shí)間: 2025-3-22 12:38
Advances in Science, Technology & Innovationhttp://image.papertrans.cn/m/image/620427.jpg作者: 神經(jīng) 時(shí)間: 2025-3-22 14:36 作者: Eulogy 時(shí)間: 2025-3-22 18:51
2522-8714 achine learning in different applications of smart cities.In.This book discusses the application of different machine learning techniques to the sub-concepts of smart cities such as smart energy, transportation, waste management, health, infrastructure, etc. The focus of this book is to come up with作者: Infuriate 時(shí)間: 2025-3-22 22:40 作者: fatty-streak 時(shí)間: 2025-3-23 02:55
Applying Deep Learning to Predict Civic Purpose Development: Within the Smart City Context,model the non-linear relationship between the predictors and outcome variables. Based on the findings, we discussed the implications of the present study within the context of improving citizens’ lives in smart cities.作者: habitat 時(shí)間: 2025-3-23 07:41
Emergency Department Management Using Regression Models,ctor regression are considered for the prediction of the patient flow in Emergency Departments. The hazardous COVID-19 pandemic and its impact on the mounting crisis in the EDs is also discussed. The challenges and suggestive methods are also discussed here.作者: 厭惡 時(shí)間: 2025-3-23 13:11 作者: Interferons 時(shí)間: 2025-3-23 14:32 作者: 人工制品 時(shí)間: 2025-3-23 22:05 作者: 咽下 時(shí)間: 2025-3-23 22:25
Convolution Neural Network Scheme for Detection of Electricity Theft in Smart Grids,te as 0.948 and recall as 1 for ETD, and an overall accuracy of 92.16% was obtained. The performance analysis of the proposed model has been discussed and also been compared with the existing methodologies for ETD.作者: 骨 時(shí)間: 2025-3-24 05:27
Helping Hand: A GMM-Based Real-Time Assistive Device for Disabled Using Hand Gestures,tion and hand shape deformation as the disabled person may not always give a clear view of any shown gesture. The recognition of hand gesture is carried out by comparing the extracted features with the most likely used pre-stored features used by the disabled and elderly like the need for food, wate作者: 諷刺滑稽戲劇 時(shí)間: 2025-3-24 09:27 作者: chastise 時(shí)間: 2025-3-24 13:08
DriveSense: Adaptive System for Driving Behaviour Analysis and Ranking,of Gas Pedal, Light Status and Indicators (turn-light signal). Using these observations, machine-learning models are trained to perform real-time high-accuracy driving behaviour monitoring. Abnormal driving errors centre on human mindsets; as such a national ranking system ‘DriveScore’ has been inco作者: perjury 時(shí)間: 2025-3-24 15:55
Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles, urban traffic in emerging countries. For this purpose, 3 datasets with more than 2.5?million annotated objects are introduced using video sequences captured from UAVs from different views. An analysis of detection ability is carried out by considering traditional methods (prior to deep learning det作者: 態(tài)度暖昧 時(shí)間: 2025-3-24 23:02
Tracking Everyone and Everything in Smart Cities with an ANN Driven Smart Antenna, and corrected if there is a failure as in the case of emergency systems. This chapter discusses the application of AI in the physical layer in addressing connectivity issues of IoT in the wide area network and cellular systems landscape. The chapter address the connectivity of wireless systems of l作者: carbohydrate 時(shí)間: 2025-3-25 01:14 作者: Onerous 時(shí)間: 2025-3-25 03:20
A Survey of Emerging Applications of Machine Learning in the Diagnosis and Management of Sleep Hygine learning algorithms to objectively assess the sleep through signals acquired from conventional equipments and sophisticated equipments with reduced complexity. Further, the recent technological advances in non-contact and unobtrusive monitoring of sleep are presented. The chapter finally proposes作者: Overthrow 時(shí)間: 2025-3-25 08:46
Smart City Traffic Patterns Prediction Using Machine Learning, increase in the number of junctions of the city can alleviate problem being faced on the road by commuters. The Root Mean Square Error (RMSE) of BAG, KNN, MARS, BGLM, GLM are 13.09, 9.23, 23.34, 8.7, and 8.6 respectively. Experimental results demonstrated that GLM attained minimal prediction error 作者: deviate 時(shí)間: 2025-3-25 12:25 作者: 截?cái)?nbsp; 時(shí)間: 2025-3-25 16:11
Learning Analytics for Smart Classroom System in a University Campus,stem was implemented in a web application to assess students along with its model to predict their formative assessment performance. To perform prediction, the three models have been trained using different machine learning algorithms where the most accurate models are deployed in the web applicatio作者: PANIC 時(shí)間: 2025-3-25 20:15 作者: 懶鬼才會(huì)衰弱 時(shí)間: 2025-3-26 00:08
SysML-Based Design of Autonomous Multi-robot Cyber-Physical System Using Smart IoT Modules: A Case em. Finally, SysML modeling is designed for the proposed system and reported in this report, including requirement, activity, state machine, block definition, internal block definition, and parametric diagrams. Hence, the proposed architecture design provides a generic model-based system engineering作者: BUST 時(shí)間: 2025-3-26 07:11 作者: 無孔 時(shí)間: 2025-3-26 09:23
Hyemin Hanen Binnendifferenzierung von Kompetenzen befassen, und Kompetenzniveaumodelle, welche die konkrete inhaltliche Beschreibung von unterschiedlich hohen Auspr?gungen quantitativ erfasster Kompetenzen zum Gegenstand haben. Schlie?lich werden zur Veranschaulichung des Kompetenzbegriffs drei spezifische K作者: 女上癮 時(shí)間: 2025-3-26 13:36
B. Banu Rekha,A. Kandaswamyrg und Nürnberg entstanden, wobei Nürnberg als gr??tes Produktionszentrum Süddeutschlands sich schon seit dem sp?ten Mittelalter der Reviern?he erfreuen konnte; denn die Oberpfalz war das ?Ruhrge- biet” des Sp?tmittelalters und der frühen Neuzeit noch vor dem Siegerland und dem Eisenerzland der Stei作者: 強(qiáng)所 時(shí)間: 2025-3-26 17:52 作者: 排出 時(shí)間: 2025-3-27 00:05 作者: 小淡水魚 時(shí)間: 2025-3-27 01:48 作者: Obscure 時(shí)間: 2025-3-27 09:17
Qasem Abu Al-Haijakonventionellen und regenerativen Umwandlungsanlagen. Dabei werden die technischen und tariflichen M?glichkeiten einer Leistungs- bzw. Lastbedarfssteuerung durch Versorger und Verbraucher aufgezeigt.978-3-540-51063-5978-3-642-51130-1Series ISSN 0172-6463 作者: 不能平靜 時(shí)間: 2025-3-27 09:26 作者: overreach 時(shí)間: 2025-3-27 14:00 作者: Collar 時(shí)間: 2025-3-27 19:04 作者: NATTY 時(shí)間: 2025-3-27 23:25
Sankar Behera,Bhavya Bhardwaj,Aurea Rose,Mohammad Hamdaan,M. Ganesan作者: 樂器演奏者 時(shí)間: 2025-3-28 02:27
Jorge E. Espinosa,Jairo Espinosa,Sergio A. Velastin作者: Crohns-disease 時(shí)間: 2025-3-28 07:28 作者: sulcus 時(shí)間: 2025-3-28 12:47 作者: 認(rèn)為 時(shí)間: 2025-3-28 18:08 作者: 提名的名單 時(shí)間: 2025-3-28 22:29 作者: Intact 時(shí)間: 2025-3-29 01:49 作者: Jubilation 時(shí)間: 2025-3-29 03:33
Applying Deep Learning to Predict Civic Purpose Development: Within the Smart City Context, purpose development during emerging adulthood. We tested whether deep learning more accurately predicted Wave 2 political purpose with Wave 1 predictors compared with traditional regression. A convolutional neural network consisting of two dense and dropout layers was trained to predict the outcome作者: 流眼淚 時(shí)間: 2025-3-29 08:30
Convolution Neural Network Scheme for Detection of Electricity Theft in Smart Grids,cant changes to the conventional grid system to include RTU and intelligent AI-based framework for autonomous operation in real-time. The security issues in smart grid introduced threats to the secure operation of the grid. In this paper, an analysis of threats identified for electricity theft and s作者: amnesia 時(shí)間: 2025-3-29 11:25 作者: 民間傳說 時(shí)間: 2025-3-29 15:51 作者: 生氣地 時(shí)間: 2025-3-29 20:05 作者: misshapen 時(shí)間: 2025-3-30 00:52
Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles,and excessive trip times. Intelligent Transport Systems (ITS) emerge as an important alternative to assist urban planning by monitoring the different urban road corridors. Traditionally, ITS use fixed camera systems which are sometimes insufficient to monitor and extend the traceability of the vehic作者: 補(bǔ)角 時(shí)間: 2025-3-30 07:32 作者: 獨(dú)輪車 時(shí)間: 2025-3-30 12:14 作者: 歌劇等 時(shí)間: 2025-3-30 16:26 作者: ADORN 時(shí)間: 2025-3-30 18:47
Smart City Traffic Patterns Prediction Using Machine Learning,es, the strain generated by traffic jams, sleep, and workouts induced by time spent in traffic. Since motorists cannot see the entire traffic system, the urban traffic system must be anticipated in order to sensitize residents about their mobility choices and the subsequent impact on the environment作者: 易彎曲 時(shí)間: 2025-3-30 23:23 作者: 聯(lián)想記憶 時(shí)間: 2025-3-31 02:08 作者: 無動(dòng)于衷 時(shí)間: 2025-3-31 05:28 作者: 英寸 時(shí)間: 2025-3-31 11:35
Learning Analytics for Smart Classroom System in a University Campus,n the class. LA is thus being incorporated in different educational settings such as in smart classrooms where students’ behaviour and performance are observed and analyzed. This chapter presents LA in a smart classroom using predictive models to assess formative assessment, attendance, and behaviou作者: 兩棲動(dòng)物 時(shí)間: 2025-3-31 13:47 作者: 除草劑 時(shí)間: 2025-3-31 18:57
SysML-Based Design of Autonomous Multi-robot Cyber-Physical System Using Smart IoT Modules: A Case world via sensors and actuators in a feedback loop. Indeed, CPS systems became available everywhere, such as the team of autonomous mobile robots with prescribed tasks and missions. This chapter proposes a detailed architectural model-based design for a cyber-physical system of autonomous multi-diff作者: MELON 時(shí)間: 2025-4-1 01:41
Vulnerabilities and Ethical Issues in Machine Learning for Smart City Applications,logy, however, brings with it new concerns and obstacles. Many aspects of smart cities rely on data transfer, storage and learning technology and cyber-security issues have an impact on how they operate. First part of this chapter is focused on different aspects of vulnerabilities of machine learnin作者: Ambulatory 時(shí)間: 2025-4-1 05:37
d. In der p?adagogischen Psychologie und der Bildungsforschung hat dieser Begriff im Zusammenhang mit der Definition der Ziele von Bildungssystemen eine gro?e Bedeutung gewonnen, so etwa bei der Entwicklung von Bildungsstandards (Klieme et al. 2003; Klieme 2004). Kompetenzen werden in diesem Zusamme
