Context-aware taxi demand hotspots prediction
WebJan 1, 2010 · This paper proposes mining historical data to predict demand distributions with respect to contexts of time, weather, and taxi location. The four-step process … WebDec 1, 2010 · This paper proposes mining historical data to predict demand distributions with respect to contexts of time, weather, and taxi location. The four-step process …
Context-aware taxi demand hotspots prediction
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WebJan 1, 2012 · Taxi-Aware Map: Identifying and Predicting Vacant Taxis in the City. Proc., International Joint Conference on Ambient Intelligence 10 , Springer Lecture Notes in Computer Science 6439, Springer-Verlag, Berlin, Germany, 2010, pp. 86–95. Webmash-up application to show that context-aware demand prediction can help improve the management of taxi fleets. Keywords: hotspot mining; data mining; clustering.
WebFeb 10, 2024 · In this paper, we are using the dominating set problem-based solution for detecting the local hotspots that reduce the cruising time for drivers, maximize their revenues, help to find the optimal number of taxis in a city, and also maximize the coverage of taxi services in a city. 3 Context of the Problem WebIn the research a context aware taxi demand hotspots prediction is done using data mining techniques they only consider about finding clusters not the optimum clusters, clusters which are more profitable to taxi drivers. And they have included in their future works to consider the events in that area (social event) that a taxi driver can find
WebSep 1, 2015 · Context-aware taxi demand hotspots prediction. IJBIDM (2010) Wei Chu et al. ... Short-term taxi demand forecasting is of great importance to incentivize vacant cars moving from over-supply regions to over-demand regions, which can minimize the wait time for passengers and drivers. With the consideration of spatiotemporal dependences, … WebiTaxi: Context-Aware Taxi Demand Hotspots Prediction Han-Wen Chang According to the Institude of Traffic (IOT) Survey of Taxi Operation Conditions in Taiwan Area 2006 , …
WebThe experimental results show that the short-term demand prediction model for online car-hailing services based on LS-SVM performs better than the other methods and is compared with lasso linear regression, nearest neighbor regression, decision tree regression, and neural network. The purpose of this paper is to study the short-term demand prediction …
WebChang, H., Tai, Y., Chen, H.W., Hsu, J.Y.: iTaxi: Context-Aware Taxi Demand Hotspots Prediction Using Ontology and Data Mining Approaches. In: Proceedings of the 13th … jeffords steel \\u0026 specialty coWebJan 1, 2010 · This paper proposes mining historical data to predict demand distributions with respect to contexts of time, weather, and taxi location. … jeffords st lab clearwaterWebIn the research a context aware taxi demand hotspots prediction is done using data mining techniques they only consider about finding clusters not the optimum clusters, … jeffords st clearwater flWebFeb 1, 2012 · This paper proposes an improved ARIMA based prediction method to forecast the spatial-temporal variation of passengers in a hotspot. Evaluation with a … oxygen cpap therapyWebSep 1, 2013 · Intelligent transportation systems for taxi dispatching and for finding time-saving routes are already exploring these sensing data. This paper introduces a novel … jeffords steel plattsburgh new yorkhttp://ir.kdu.ac.lk/bitstream/handle/345/2493/Untitled(11).pdf?sequence=1 jeffords steel \u0026 specialty coWebAug 13, 2024 · The development of the intelligent transport system has created conditions for solving the supply–demand imbalance of public transportation services. For example, forecasting the demand for online taxi-hailing could help to rebalance the resource of taxis. In this research, we introduced a method to forecast real-time online … oxygen credit card lyft