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Using attributes explicitly reflecting user preference in a self-attention network for next POI recommendation / Ruijing Li in ISPRS International journal of geo-information, vol 11 n° 8 (August 2022)
[article]
Titre : Using attributes explicitly reflecting user preference in a self-attention network for next POI recommendation Type de document : Article/Communication Auteurs : Ruijing Li, Auteur ; Jianzhong Guo, Auteur ; Chun Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 440 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] attention (apprentissage automatique)
[Termes IGN] distance
[Termes IGN] filtrage d'information
[Termes IGN] New York (Etats-Unis ; ville)
[Termes IGN] point d'intérêt
[Termes IGN] réseau social géodépendant
[Termes IGN] Tokyo (Japon)Résumé : (auteur) With the popularity of location-based social networks such as Weibo and Twitter, there are many records of points of interest (POIs) showing when and where people have visited certain locations. From these records, next POI recommendation suggests the next POI that a target user might want to visit based on their check-in history and current spatio-temporal context. Current next POI recommendation methods mainly apply different deep learning models to capture user preferences by learning the nonlinear relations between POIs and user preference and pay little attention to mining or using the information that explicitly reflects user preference. In contrast, this paper proposes to utilize data that explicitly reflect user preference and include these data in a deep learning-based process to better capture user preference. Based on the self-attention network, this paper utilizes the attributes of the month of the check-ins and the categories of check-ins during this time, which indicate the periodicity of the user’s work and life and can reflect the habits of users. Moreover, considering that distance has a significant impact on a user’s decision of whether to visit a POI, we used a filter to remove candidate POIs that were more than a certain distance away when recommending the next POIs. We use check-in data from New York City (NYC) and Tokyo (TKY) as datasets, and experiments show that these improvements improve the recommended performance of the next POI. Compared with the state-of-the-art methods, the proposed method improved the recall rate by 7.32% on average. Numéro de notice : A2022-647 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11080440 Date de publication en ligne : 04/08/2022 En ligne : https://doi.org/10.3390/ijgi11080440 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101463
in ISPRS International journal of geo-information > vol 11 n° 8 (August 2022) . - n° 440[article]A model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway / Reza Sanayeia in Geocarto international, vol 37 n° 14 ([20/07/2022])
[article]
Titre : A model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway Type de document : Article/Communication Auteurs : Reza Sanayeia, Auteur ; Alireza Vafaeinejad, Auteur ; Jalal Karami, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 4141 - 4157 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] accident de la route
[Termes IGN] autocorrélation
[Termes IGN] autoroute
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] modèle de simulation
[Termes IGN] réseau neuronal artificiel
[Termes IGN] système d'information géographique
[Termes IGN] Téhéran
[Termes IGN] transformation en ondelettesRésumé : (auteur) The aim of this study is to develop a model to predict temporal daily collision by integrating of Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms. As a case study, the integrated model was tested on 1097 daily traffic collisions data of Karaj-Qazvin freeway from 2009 to 2013 and the results were compared with the conventional ANN prediction model. In this method, initially, the raw collision data were analyzed, normalized, and classified via Geographical Information System (GIS). Partial Autocorrelation Function (PACF) was also utilized to evaluate the temporal autocorrelation for consecutive existing daily data. The results of this study showed that the proposed integrated DWT-ANN method provided higher predictive accuracy in daily traffic collision than ANN model by increasing coefficient of determination (R2) from 0.66 to 0.82. Numéro de notice : A2022-650 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/10106049.2021.1871669 Date de publication en ligne : 19/01/2021 En ligne : https://doi.org/10.1080/10106049.2021.1871669 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101472
in Geocarto international > vol 37 n° 14 [20/07/2022] . - pp 4141 - 4157[article]PS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan / Sajid Hussain in Geocarto international, vol 37 n° 13 ([15/07/2022])
[article]
Titre : PS-InSAR based validated landslide susceptibility modelling: a case study of Ghizer valley, Northern Pakistan Type de document : Article/Communication Auteurs : Sajid Hussain, Auteur ; Sun Hongxing, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3941 - 3962 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] aléa
[Termes IGN] effondrement de terrain
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] PakistanRésumé : (auteur) Northern Pakistan is a rugged mountainous area that is seismically active, high gradients, disintegrated lithology, and glaciers in the high peaks. District Ghizer lies among the most vulnerable areas and experience landslides every year due to different causative factors. This study has carried out to prepare a detailed landslide inventory and to develop a susceptibility model for the area. The most followed and probabilistic approach, Frequency Ratio (FR) model and a semi-qualitative Analytical Hierarchy Process (AHP) approach were applied to find the correlation between causative factors and mapped landslides. Persistent Scatterer Interferometry (PSI) Interferometric Synthetic Aperture Radar (InSAR) technique was applied to check deformation movement in the susceptible zones of extracted models, which showed the high Line of Sight (LOS) deformation velocity in high susceptible zones of both models. The extracted Landslide Susceptibility Index (LSI) models showed 82.82% and 73.43% of prediction accuracy for FR and AHP method calculated by Area Under Curve (AUC) of Receiver operating characteristic (ROC) method. The models revealed Slope, barrenness, and Geology are the main causative factors of landslide activities in the study area. Finally, both Landslide susceptibility index maps were classified into five susceptibility classes. As the study area is very prone to landslide disasters so these susceptibility models will be helpful to delineate hazardous zones for the medication of future landslides disasters in the area as well as it can be used as a tool in the planning strategies by decision-makers in development projects in the area. Numéro de notice : A2022-589 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1870165 Date de publication en ligne : 11/02/2021 En ligne : https://doi.org/10.1080/10106049.2020.1870165 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101363
in Geocarto international > vol 37 n° 13 [15/07/2022] . - pp 3941 - 3962[article]An accurate train positioning method using tightly-coupled GPS + BDS PPP/IMU strategy / Wei Jiang in GPS solutions, vol 26 n° 3 (July 2022)
[article]
Titre : An accurate train positioning method using tightly-coupled GPS + BDS PPP/IMU strategy Type de document : Article/Communication Auteurs : Wei Jiang, Auteur ; Mengyang Liu, Auteur ; Baigen Cai, Auteur Année de publication : 2022 Article en page(s) : n° 67 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] ambiguïté entière
[Termes IGN] Chine
[Termes IGN] filtre de Kalman
[Termes IGN] phase
[Termes IGN] positionnement inertiel
[Termes IGN] positionnement par BeiDou
[Termes IGN] positionnement par GPS
[Termes IGN] positionnement ponctuel précis
[Termes IGN] signal GPS
[Termes IGN] simple différence
[Termes IGN] trainRésumé : (auteur) A new GNSS/IMU tightly coupled positioning system is introduced to train positioning. To fulfil a train control system’s aim of reducing the need to install trackside equipment, the GNSS precise point positioning (PPP) method is applied in place of the conventional differential GNSS method. As the railway environment has the character of long operational mileage and complex GNSS measurement conditions, the GPS and BDS constellations are combined with measurement processing to improve the system’s continuity and stability. Ultra-rapid GNSS orbit and clock product is used for real-time PPP. The GNSS-PPP and IMU are tightly coupled using an Extended Kalman filter with single-differenced ionospheric-free GPS + BDS carrier phase and pseudorange observations. The carrier phase ambiguities are estimated as “float” values every epoch to reduce the impact of GNSS signal loss-of-lock and cycle slips. A train experiment was conducted on the Qinghai-Tibet Railway to evaluate system performance. The results show that the proposed system has a better performance than the conventional methods, including GPS + BDS PPP, LC GPS + BDS PPP/IMU and TC GPS PPP/IMU, with 52.1%, 49.4% and 52.1%, respectively. The tightly-coupled GPS + BDS PPP/IMU system under conditions of partly blocked GNSS coverage was evaluated to evaluate the system's continuity. It was confirmed that the proposed system had more stable positioning results and higher positioning accuracy. Numéro de notice : A2022-361 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-022-01250-2 Date de publication en ligne : 08/04/2022 En ligne : https://doi.org/10.1007/s10291-022-01250-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100580
in GPS solutions > vol 26 n° 3 (July 2022) . - n° 67[article]A comparison of three multi-criteria decision-making models in mapping flood hazard areas of Northeast Penang, Malaysia / Rofiat Bunmi Mudashiru in Natural Hazards, vol 112 n° 3 (July 2022)
[article]
Titre : A comparison of three multi-criteria decision-making models in mapping flood hazard areas of Northeast Penang, Malaysia Type de document : Article/Communication Auteurs : Rofiat Bunmi Mudashiru, Auteur ; Nuridah Sabtu, Auteur ; Rozi Abdullah, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1903 - 1939 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse multicritère
[Termes IGN] carte thématique
[Termes IGN] cartographie des risques
[Termes IGN] Malaisie
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] processus de hiérarchisation analytique floue
[Termes IGN] zone inondableRésumé : (auteur) Flooding is a major and recurring natural disaster in Northeast Penang, Malaysia. The ability to effectively identify flood hazard areas represents an important part of flood risk analysis and management. There is a need for a structured study that incorporates stakeholders’ inputs such as the multi-criteria decision-making (MCDM) model to delineate flood-prone locations to support the management and mitigation measures of flooding in this area. Previous studies have compared the analytic hierarchy process (AHP) and fuzzy AHP methods in flood hazard mapping. Therefore, this study proposes to test the predicting capability of three MCDM models in the determination of flood-prone areas: the AHP, triangular fuzzy AHP (TF-AHP), and trapezoidal fuzzy AHP (TZF-AHP) in this area. The methodology applies nine flood-causative factors (FCFs) which include drainage density, elevation, land use, slope, rainfall, flood depth, distance from rivers, lithology, and distance from inundation. The resulting flood hazard maps showed a closer similarity between the TF-AHP and TZ-AHP methods compared to the AHP method for flood hazard mapping. The sensitivity analysis indicated that the AHP was more accurate than the fuzzy AHP models based on the weight estimation. The validation results showed that 100%, 93%, and 93% of the actual flood events occurred in the ‘moderate’ to ‘very high’ flood hazard areas for the AHP, TF-AHP, and TZF-AHP, respectively. Overall results showed the accuracy of all three models in modeling flood hazard areas. Therefore, the findings can be adopted as a tool in making informed and accurate policies about flood management for effective climate mitigation decision making. Numéro de notice : A2022-558 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-022-05250-w Date de publication en ligne : 28/02/2022 En ligne : https://doi.org/10.1007/s11069-022-05250-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101176
in Natural Hazards > vol 112 n° 3 (July 2022) . - pp 1903 - 1939[article]Detection of diseased pine trees in unmanned aerial vehicle images by using deep convolutional neural networks / Gensheng Hu in Geocarto international, vol 37 n° 12 ([01/07/2022])PermalinkEffects of offsets and outliers on the sea level trend at Antalya 2 tide gauge within the Eastern Mediterranean Sea / Mehmet Emin Ayhan in Marine geodesy, vol 45 n° 4 (July 2022)PermalinkA framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method / Yongyang Xu in Computers, Environment and Urban Systems, vol 95 (July 2022)PermalinkHeat wave-induced augmentation of surface urban heat islands strongly regulated by rural background / Shiqi Miao in Sustainable Cities and Society, vol 82 (July 2022)PermalinkInteractive visual analytics of moving passenger flocks using massive smart card data / Tong Zhang in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)PermalinkQuantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest / Thangavelu Mayamanikandan in Geocarto international, vol 37 n° 12 ([01/07/2022])PermalinkA second-order attention network for glacial lake segmentation from remotely sensed imagery / Shidong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkStreet-view imagery guided street furniture inventory from mobile laser scanning point clouds / Yuzhou Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 189 (July 2022)PermalinkEstimating feature extraction changes of Berkelah Forest, Malaysia from multisensor remote sensing data using and object-based technique / Syaza Rozali in Geocarto international, vol 37 n° 11 ([15/06/2022])PermalinkAssessing and mapping landslide susceptibility using different machine learning methods / Osman Orhan in Geocarto international, vol 37 n° 10 ([01/06/2022])Permalink