標(biāo)題: Titlebook: Enabling Smart Urban Services with GPS Trajectory Data; Chao Chen,Daqing Zhang,Hongyu Huang Book 2021 The Editor(s) (if applicable) and Th [打印本頁(yè)] 作者: Dopamine 時(shí)間: 2025-3-21 19:32
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data影響因子(影響力)
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data影響因子(影響力)學(xué)科排名
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data被引頻次
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data被引頻次學(xué)科排名
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書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data年度引用學(xué)科排名
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data讀者反饋
書(shū)目名稱Enabling Smart Urban Services with GPS Trajectory Data讀者反饋學(xué)科排名
作者: labyrinth 時(shí)間: 2025-3-21 21:49
Trajectory Data Compressione issues, such as storage, communication, and computation. Online trajectory compression becomes a promising way to alleviate these issues. In this chapter, we first propose an online trajectory data compression algorithm which works on the basis of the SD-Matching algorithm. Similar to the SD-Match作者: 希望 時(shí)間: 2025-3-22 02:41 作者: 態(tài)學(xué) 時(shí)間: 2025-3-22 07:34
Hunting or Waiting: Earning More by Understanding Taxi Service Strategiese skills to . for low-performance taxi drivers. Thanks to the widely available large-scale taxi GPS trajectory data, service strategies of taxi drivers that are hidden in their trajectory data can be uncovered by data mining techniques. In this chapter, we investigate taxi service strategies from th作者: daredevil 時(shí)間: 2025-3-22 12:21
GreenPlanner: Planning Fuel-Efficient Driving Routeslized fuel consumption model (PFCM) for each driver, based on the individual driving behaviors embedded in the GPS trajectory data and the physical features (e.g., traffic lights, stop signs, road network topology) along the routes provided by road network data. Furthermore, we build a general PFCM 作者: 瑣事 時(shí)間: 2025-3-22 14:58 作者: 瑣事 時(shí)間: 2025-3-22 17:02
Real-Time Imputing Trip Purpose Leveraging Heterogeneous Trajectory Data, previous studies have paid relatively less attention to the trip purpose imputation at an individual level and required no real-time response. To narrow the gaps, a two-phase probabilistic framework TripImputor is proposed in this chapter, to perform real-time taxi trip purpose imputation and pers作者: 凝結(jié)劑 時(shí)間: 2025-3-22 22:33
GPS Environment Friendliness Estimation with Trajectory Datarent road segments can be further predicted by estimating the negative impact of the urban environment on GPS accuracy, and we refer to this impact as GPS environmental friendliness (GEF). In this chapter, we propose a method for processing and analysing a large amount of historical bus GPS trajecto作者: commodity 時(shí)間: 2025-3-23 02:52 作者: 使聲音降低 時(shí)間: 2025-3-23 07:11 作者: Measured 時(shí)間: 2025-3-23 10:52 作者: 傾聽(tīng) 時(shí)間: 2025-3-23 17:56 作者: BRIBE 時(shí)間: 2025-3-23 20:38
CrowdExpress: Making Citywide Packages Arrive as many as Possiblegh shipping costs. To alleviate such contradiction, crowdsourced logistics is an encouraging solution. In this chapter, we present a new type of crowdsourcing logistics to organize packages and passengers in a shared space, i.e., using a taxi that has already picked up a passenger as a package hitch作者: Oversee 時(shí)間: 2025-3-23 22:46 作者: Interim 時(shí)間: 2025-3-24 04:30 作者: Optimum 時(shí)間: 2025-3-24 09:25
iBOAT: Detecting Anomalous Trajectories On-the-Flyate fraudulent decisions by greedy taxi drivers. At last, a group of experiments has been conducted to evaluate the effectiveness of the isolation-based online anomalous trajectory (iBOAT) algorithm. iBOAT algorithm shows superior performance compared with the baseline methods (AUC?≥?0.99).作者: Platelet 時(shí)間: 2025-3-24 14:27
TripPlanner: Personalized Trip Planning Leveraging Heterogeneous Trajectory Datas are applied to add user’s preferred venues iteratively to the candidate routes, with the objective of maximizing the route score while satisfying both the venue visiting time and total travel time constraints. We validate the efficiency and effectiveness of TripPlanner by extensive evaluations using large-scale real-world data sets.作者: Gobble 時(shí)間: 2025-3-24 16:13
services to benefit a wide range of people including drivers.With the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that ta作者: 奴才 時(shí)間: 2025-3-24 21:30
Clinical Utility (Applications) of SPECT/CTs lies in the scenario that whether a user uploads its trajectory in a bundle or in a sequence. To evaluate the mechanisms, we utilize the real-world traffic trajectories of Shanghai taxis and compare them with existing works. Results show that our methods not only protect users’ privacy, but also preserve the server’s utility.作者: 泄露 時(shí)間: 2025-3-25 00:30 作者: 我要威脅 時(shí)間: 2025-3-25 03:58 作者: 聯(lián)合 時(shí)間: 2025-3-25 08:09
ScenicPlanner: Recommending the Most Beautiful Driving Routes Area in the city of San Francisco, CA, USA. Results show that it obtains high-quality solutions that are reasonably close to the optima but within desirable computation time and considerably better than the baseline solutions of genetic algorithms.作者: gregarious 時(shí)間: 2025-3-25 13:22 作者: 類型 時(shí)間: 2025-3-25 16:50 作者: Kinetic 時(shí)間: 2025-3-25 20:24 作者: Parabola 時(shí)間: 2025-3-26 01:14 作者: noxious 時(shí)間: 2025-3-26 06:23
Clinical Utility (Applications) of SPECT/CTlications in a smart city by using these mobile devices. Intuitively, uploading true locations to the server will improve the quality of services. But this also brings leakage of our location privacy. Even if locations are perturbed before submission, the correlation between successive locations ena作者: 創(chuàng)新 時(shí)間: 2025-3-26 11:21
https://doi.org/10.1007/978-1-4842-0097-1e skills to . for low-performance taxi drivers. Thanks to the widely available large-scale taxi GPS trajectory data, service strategies of taxi drivers that are hidden in their trajectory data can be uncovered by data mining techniques. In this chapter, we investigate taxi service strategies from th作者: 描述 時(shí)間: 2025-3-26 16:13
https://doi.org/10.1007/978-1-4842-3036-7lized fuel consumption model (PFCM) for each driver, based on the individual driving behaviors embedded in the GPS trajectory data and the physical features (e.g., traffic lights, stop signs, road network topology) along the routes provided by road network data. Furthermore, we build a general PFCM 作者: saphenous-vein 時(shí)間: 2025-3-26 20:47 作者: laparoscopy 時(shí)間: 2025-3-26 23:55
https://doi.org/10.1007/978-1-4842-4457-9, previous studies have paid relatively less attention to the trip purpose imputation at an individual level and required no real-time response. To narrow the gaps, a two-phase probabilistic framework TripImputor is proposed in this chapter, to perform real-time taxi trip purpose imputation and pers作者: 嬉耍 時(shí)間: 2025-3-27 04:10
Governance, Adoption, and Training,rent road segments can be further predicted by estimating the negative impact of the urban environment on GPS accuracy, and we refer to this impact as GPS environmental friendliness (GEF). In this chapter, we propose a method for processing and analysing a large amount of historical bus GPS trajecto作者: FLINT 時(shí)間: 2025-3-27 07:23
Managing Record Retention and Dispositionty patterns in cities. In this chapter, we intend to employ taxi GPS traces to explore the issue of night bus route planning. Specifically, a two-phase approach is proposed for bi-directional night-bus route planning. In the first phase, we start by clustering “hot” areas with dense passenger pick-u作者: Manifest 時(shí)間: 2025-3-27 12:09
Signal Averaging for Noise Reductionveraging a combination of location-based social network (i.e., LBSN) and taxi GPS digital footprints. First, based on the information in crowdsourced LBSN and taxi GPS traces, we construct a dynamic point-of-interest network model. Then, a two-phase approach is proposed for personalized trip plannin作者: 違反 時(shí)間: 2025-3-27 16:47 作者: Banister 時(shí)間: 2025-3-27 19:38
What Is Psoriasiform Dermatitis?ackage express shipping. The main barrier may be due to that the speedy usually implies a higher sending frequency. To strike a trade-off between the two conflicting objectives, we propose a new idea that exploits the existing taxi mobility to transport packages collectively (i.e., the relays among 作者: 案發(fā)地點(diǎn) 時(shí)間: 2025-3-27 22:03
The Fourth Project: A Graphing Application,gh shipping costs. To alleviate such contradiction, crowdsourced logistics is an encouraging solution. In this chapter, we present a new type of crowdsourcing logistics to organize packages and passengers in a shared space, i.e., using a taxi that has already picked up a passenger as a package hitch作者: 谷物 時(shí)間: 2025-3-28 03:15 作者: Excitotoxin 時(shí)間: 2025-3-28 08:28
http://image.papertrans.cn/e/image/309164.jpg作者: Stagger 時(shí)間: 2025-3-28 14:06 作者: EXALT 時(shí)間: 2025-3-28 15:14
the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the re978-981-16-0180-4978-981-16-0178-1作者: Servile 時(shí)間: 2025-3-28 19:11
https://doi.org/10.1007/978-1-4613-0687-0ically, at the first stage, the heading direction is used to facilitate the probability computation when finding true positions for GPS points. At the second stage, it is used to accelerate the path-finding when filling the distance gap between two consecutive GPS points. At the final stage, it is u作者: Memorial 時(shí)間: 2025-3-29 00:20
https://doi.org/10.1007/978-1-4615-2752-7by smartphones of drivers by leveraging the idea of mobile edge computing. We conduct experiments to evaluate the effectiveness and efficiency of the proposed HCC algorithm using real-world datasets in the city of Beijing, China. We deploy the system in the real world in the city of Chongqing, China作者: 抱怨 時(shí)間: 2025-3-29 04:44
https://doi.org/10.1007/978-1-4842-0097-1ding more efficient strategy. To demonstrate that the extracted taxi service strategies with our proposed approach well characterize the driving behavior and performance of taxi drivers, we build a regression model and predict the revenue of taxi drivers based on their strategies, achieving a predic作者: 不足的東西 時(shí)間: 2025-3-29 07:36 作者: cuticle 時(shí)間: 2025-3-29 11:36 作者: heckle 時(shí)間: 2025-3-29 16:01
Governance, Adoption, and Training,ulate the GEF of each road based on the GPS positioning performance of all buses. Based on the GPS trajectory data of buses collected from Chengdu, China, we estimate the GEF of 8831 different road segments and verify the rationality of the results by satellite maps, street views, and field tests.作者: Diskectomy 時(shí)間: 2025-3-29 22:07
Managing Record Retention and Dispositionl Probability based Spreading (BPS) algorithm to generate candidate bus routes automatically. Finally, we select the best bi-directional bus route, which expects the maximum number of passengers under the given conditions and constraints. We conduct extensive empirical studies on real-world taxi GPS作者: IOTA 時(shí)間: 2025-3-30 00:49
What Is Psoriasiform Dermatitis?second phase, using the obtained paths and travel times as the reference to guide the adaptive path-finding, we propose an online taxi scheduling algorithm that aims to discover the near-optimal path iteratively upon the newly incoming taxi ride requests. Finally, with the large-scale taxi trajector作者: Harpoon 時(shí)間: 2025-3-30 05:17
The Fourth Project: A Graphing Application, corresponding package routing. Finally, we use the real-world taxi data in the city of New York, US in a month to evaluate the system. The experiment results show that about 9500 packages are delivered successfully daily on time with a success rate of over 94%.作者: 大溝 時(shí)間: 2025-3-30 10:17
Trajectory Data Map-matchingically, at the first stage, the heading direction is used to facilitate the probability computation when finding true positions for GPS points. At the second stage, it is used to accelerate the path-finding when filling the distance gap between two consecutive GPS points. At the final stage, it is u
