Optimal school site selection in Urban areas using deep neural networks
Tóm tắt
Từ khóa
Tài liệu tham khảo
Achtert E, Böhm C, Kröger P, Kunath P, Pryakhin A, Renz M (2006) Efficient reverse k-nearest neighbor search in arbitrary metric spaces. In: Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data, SIGMOD ’06, pages 515–526, New York, NY, USA. ACM
Achtert E, Kriegel H-P, Kröger P, Renz M, Züfle A (2009) Reverse k-nearest neighbor search in dynamic and general metric databases. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, EDBT ’09, pages 886–897, New York, NY, USA. ACM
Ahmed BH, Ghabayen AS (2020) Review rating prediction framework using deep learning. J Ambient Intell Hum Comput 2:1–10
Aksenova SS, Zhang D, Lu M (2006) Enrollment prediction through data mining. In: 2006 IEEE International Conference on Information Reuse Integration, pages 510–515
Bamrah IS, Girdhar A (2015) Investigation on impact of reservation policy on student enrollment using data mining. In: 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pages 1–5
Borah MD, Jindal R, Gupta D, Deka GC (2011) Application of knowledge based decision technique to predict student enrollment decision. In: 2011 International Conference on Recent Trends in Information Systems, pages 180–184
Cabello S, Díaz-Báñez JM, Langerman S, Seara C, Ventura I (2005) Reverse facility location problems. In: Conference on Computational Geometry
Castillo VH, Equigua LS, Álvarez JL, Medina DAM (2013) Projecting school enrolments through an integral flow model. In: 2013 8th Iberian Conference on Information Systems and Technologies (CISTI), pages 1–4
Cheema MA, Zhang W, Lin X, Zhang Y (2012) Efficiently processing snapshot and continuous reverse k nearest neighbors queries. VLDB J 21(5):703–728
Cui J, Wang M, Li H, Cai Y (2018) Place your next branch with mile-run: Min-dist location selection over user movement. Inf Sci 463–464:1–20
Ding X, Zhang Y, Chen L, Gao Y, Zheng B (2018) Distributed k-nearest neighbor queries in metric spaces. In: Cai Y, Ishikawa Y, Xu J (eds) Web and big data. Springer International Publishing, Cham, pp 236–252
Du Y, Zhang D, Xia T (2005) The optimal-location query. In: Bauzer Medeiros C, Egenhofer MJ, Bertino E (eds) Advances in spatial and temporal databases. Springer, Berlin, pp 163–180
Emrich T, Kriegel H-P, Kröger P, Niedermayer J, Renz M, Züfle A (2015) On reverse-k-nearest-neighbor joins. GeoInformatica 19(2):299–330
Ferreira KM, de Queiroz TA (2018) Two effective simulated annealing algorithms for the location-routing problem. Appl Soft Comput 70:389–422
Gao Y, Qi S, Chen L, Zheng B, Li X (2015) On efficient k-optimal-location-selection query processing in metric spaces. Inf Sci 298(C):98–117
Goodfellow I, Bengio Y, Courville A (2016) Deep learning. MIT Press, Cambridge
Grip RS, Grip ML (2019) Using multiple methods to provide prediction bands of k-12 enrollment projections. Population Research and Policy Review
Guohui L, Yanhong L, Jianjun L, Shu L, Fumin Y (2010) Continuous reverse k nearest neighbor monitoring on moving objects in road networks. Inf Syst 35(8):860–883
Huang J, Wen Z, Qi J, Zhang R, Chen J, He Z (2011) Top-k most influential locations selection. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM ’11, pages 2377–2380, New York, NY, USA. ACM
Huang J-S, Chen B-Q, Zeng N-Y, Cao X-C, Li Y (2020) Accurate classification of ecg arrhythmia using mowpt enhanced fast compression deep learning networks. Journal of Ambient Intelligence and Humanized Computing. page inpress
Karatas M, Yakıcı E (2018) An iterative solution approach to a multi-objective facility location problem. Appl Soft Comput 62:272–287
Korn F, Muthukrishnan S, Muthukrishnan S (2000) Influence sets based on reverse nearest neighbor queries. SIGMOD Rec 29(2):201–212
Lai C-M (2019) Integrating simplified swarm optimization with ahp for solving capacitated military logistic depot location problem. Appl Soft Comput 78:1–12
Lai C-M, Chiu C-C, Liu W-C, Yeh W-C (2019) A novel nondominated sorting simplified swarm optimization for multi-stage capacitated facility location problems with multiple quantitative and qualitative objectives. Appl Soft Comput 84:105684
Li S (2013) A 1.488 approximation algorithm for the uncapacitated facility location problem. Information and Computation 222:45–58. 38th International Colloquium on Automata, Languages and Programming (ICALP 2011)
Li D, Li H, Wang M, Cui J (2019) k-collective influential facility placement over moving object. In: 2019 20th IEEE International Conference on Mobile Data Management (MDM), pages 191–200
Liu J, Liu J (2019) Applying multi-objective ant colony optimization algorithm for solving the unequal area facility layout problems. Appl Soft Comput 74:167–189
Lu J, Lu Y, Cong G (2011) Reverse spatial and textual k nearest neighbor search. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, pages 349–360
Mitra S, Saraf P, Sharma R, Bhattacharya A, Ranu S (2019) Netclus: A scalable framework to mine top-k locations for placement of trajectory-aware services. In: Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, CoDS-COMAD ’19, pages 27–35, New York, NY, USA. ACM
Pekel E, Kara SS (2019) Solving fuzzy capacitated location routing problem using hybrid variable neighborhood search and evolutionary local search. Appl Soft Comput 83:105665
Prakash S, Sangeetha K (2020) Deep multilayer and nonlinear kernelized lasso feature learning for healthcare in big data environment. J Ambient Intell Hum Comput 2:2
Qi J, Zhang R, Kulik L, Lin D, Xue Y (2012) The min-dist location selection query. In: 2012 IEEE 28th International Conference on Data Engineering, pages 366–377
Qi J, Zhang R, Wang Y, Xue AY, Yu G, Kulik L (2014) The min-dist location selection and facility replacement queries. World Wide Web 17(6):1261–1293
Shang S, Yuan B, Deng K, Xie K, Zhou X (2011) Finding the most accessible locations: reverse path nearest neighbor query in road networks. In: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS ’11, pages 181–190, New York, NY, USA. ACM
Slim A, Hush D, Ojha T, Babbitt T (2018) Predicting student enrollment based on student and college characteristics. In: EDM
Stallings R, Samanta B (2014) Prediction of university enrollment using computational intelligence. In: 2014 IEEE Symposium on Swarm Intelligence, pages 1–8
Stanoi I, Riedewald M, Agrawal D, Abbadi AE (2001) Discovery of influence sets in frequently updated databases. In: Proceedings of the 27th International Conference on Very Large Data Bases, VLDB ’01, page 99–108, San Francisco, CA, USA. Morgan Kaufmann Publishers Inc
Sun Y, Zhang R, Xue AY, Qi J, Du X (2016) Reverse nearest neighbor heat maps: A tool for influence exploration. In: 2016 IEEE 32nd International Conference on Data Engineering (ICDE), pages 966–977
Wang H, Wang H, Guo J, Feng H (2014) A fuzzy time series forecasting model based on yearly difference of the student enrollment number. In: 2nd International Conference on Soft Computing in Information Communication Technology. Atlantis Press
Wang M, Li H, Cui J, Deng K, Bhowmick SS, Dong Z (2017) Pinocchio: Probabilistic influence-based location selection over moving objects. In: 2017 IEEE 33rd International Conference on Data Engineering (ICDE), pages 21–22
Wang Z, Wan Q, Qin Y, Fan S, Xiao Z (2020) Research on intelligent algorithm for alerting vehicle impact based on multi-agent deep reinforcement learning. Journal of Ambient Intelligence and Humanized Computing 1–11
Weber A, Friedrich CJ (1929) Theory of the location of industries. University of Chicago Press, Reading
Williamson DP, Shmoys DB (2011) The design of approximation algorithms, 1st edn. Cambridge University Press, Cambridge
Wong RC-W, Özsu MT, Yu PS, Fu AW-C, Liu L (2009) Efficient method for maximizing bichromatic reverse nearest neighbor. Proc. VLDB Endow 2(1):1126–1137
Wong RC-W, Özsu MT, Fu AW-C, Yu PS, Liu L, Liu Y (2011) Maximizing bichromatic reverse nearest neighbor for lp-norm in two- and three-dimensional spaces. VLDB J 20(6):893–919
Xia T, Zhang D, Kanoulas E, Du Y (2005) On computing top-t most influential spatial sites. In: Proceedings of the 31st International Conference on Very Large Data Bases, VLDB ’05, pages 946–957. VLDB Endowment
Xiao X, Yao B, Li F (2011) Optimal location queries in road network databases. In: Proceedings of the 2011 IEEE 27th International Conference on Data Engineering, ICDE ’11, pages 804–815, Washington, DC, USA. IEEE Computer Society
Xu C, Gu Y, Zimmermann R, Lin S, Yu G (2013) Group location selection queries over uncertain objects. IEEE Trans Knowl Data Eng 25(12):2796–2808
Yamunadevi M, Ranjani SS (2020) Efficient segmentation of the lung carcinoma by adaptive fuzzy-glcm (af-glcm) with deep learning based classification. Journal of Ambient Intelligence and Humanized Computing, page inpress
Yan D, Wong RC-W, Ng W (2011) Efficient methods for finding influential locations with adaptive grids. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, CIKM ’11, pages 1475–1484, New York, NY, USA. ACM
Yang S, Cheema MA, Lin X, Zhang Y (2014) Slice: reviving regions-based pruning for reverse k nearest neighbors queries. In: 2014 IEEE 30th International Conference on Data Engineering, pages 760–771. IEEE
Yang S, Cheema MA, Lin X, Wang W (2015) Reverse k nearest neighbors query processing: experiments and analysis. Proc. VLDB Endow 8(5):605–616
Yang S, Cheema MA, Lin X, Zhang Y, Zhang W (2017) Reverse k nearest neighbors queries and spatial reverse top-k queries. VLDB J 26(2):151–176
Yilmaz E, Elbasi S, Ferhatosmanoglu H (2017) Predicting optimal facility location without customer locations. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’17, pages 2121–2130, New York, NY, USA. ACM
Zhang D, Du Y, Xia T, Tao Y (2006) Progressive computation of the min-dist optimal-location query. In: Proceedings of the 32Nd International Conference on Very Large Data Bases, VLDB ’06, pages 643–654. VLDB Endowment